Encyclopedia of nursing research [Fourth edition.] 9780826133045, 0826133045

Table of contents :
Cover
Title
Copyright
Contents
Preface
Contributors
List of Entries
Share Encyclopedia of Nursing Research, Fourth Edition
Entries A to W
A
Acculturation
Action Science
Acute Care of the Elderly
Addiction Care
Adherence/Compliance
Adolescent Health
Advance Directives
Ageism
Alzheimer’s Disease
Animal-Assisted Therapy
Applied Research
B
Basic Research
Behavioral Research
Biofeedback
Boykin and Schoenhofer: Nursing as Caring Theory
Breastfeeding
C
Cancer in Children
Cardiovascular Risk Factors
Caregiver
Caring
Case Study Method of Research
Causal Modeling
Cerebral Ischemia
Child and Adolescent Delinquents
Childbirth Education
Child Lead Exposure Levels
Chronic Illness
CINAHL Database
Clinical Care Classification System
Clinical Decision Making
Clinical Judgment
Clinical Nursing Research
Clinical Preventive Services
Clinical Trials
Cognitive Appraisal
Cohort Design
Collaborative Research
Comfort Theory
Community Mental Health
Comparative Effectiveness Research
Complementary Health Approaches
Concept Analysis
Conceptual Model
Content Analysis
Continuing Care Retirement Communities
Coronary Artery Bypass Graft Surgery
Cost Analysis of Nursing Care
Critical Care Nursing
Cultural/Transcultural Focus
D
Data Analysis
Data-Collection Methods
Data Management
Data Stewardship
Delirium
Delphi Technique
Depression and Cardiovascular Diseases
Depression in Families
Depression in Older Adults
Depression in Women
Descriptive Research
Diabetes
Discourse Analysis
Doctoral Education
E
Eating Disorders
Elder Mistreatment
Electronic Network
Emergency Nursing
Empathy
End-of-Life Planning
Enteral Tube Placement
Epilepsy
Ethics of Research
Ethnogeriatrics
Ethnography
Evaluation
Evidence-Based Practice
Experimental Research
Exploratory Studies
F
Factor Analysis
Failure to Thrive (Child)
Falls
Family Caregiving and the Seriously Mentally Ill
Family Health
Fatigue
Feminist Research Methodology
Fetal Monitoring
Fever
Fitzpatrick’s Life-Perspective Rhythm Model
Formal Nursing Languages
Functional Health Patterns
G
Genetics
Global Nursing Research
Grandparents Raising Grandchildren
Grantsmanship
Grounded Theory
H
Health Care–Associated Infections
Health Conceptualization
Health Disparities: Focus on Racial and Ethnic Minorities
Health Policy and Health Services Delivery
Health Services Research
Hemodynamic Monitoring
Henderson Model
Hermeneutics
History of Nursing Research
HIV/AIDS Care and Treatment
HIV Risk Behavior
Home Care Technologies
Home Health Systems
Homeless Health
Hospice
Hypertension
I
Immigrant Women
Institutional Review Board and Informed Consent
Instrumentation
Instrument Translation
International Classification of Nursing Practice
Interpersonal Communication
J
Job Satisfaction
Johnson’s Behavioral System Model
K
Kangaroo Care (Skin-to-Skin Contact)
King’s Theory of Goal Attainment
L
Leininger’s Theory of Culture Care Diversity and Universality
M
Maternal Anxiety and Psychosocial Adaptation During Pregnancy
Measurement and Scales
Menopause
Mental Health in Public-Sector Primary Care
Mental Status Measurement
Mentoring
Meta-Analysis
Middle Range Theories
Mild Cognitive Impairment
Moral Distress
Moral Reckoning
Mother–Infant/Toddler Relationships
Music Therapy
N
Narrative Analysis
National Institute of Nursing Research
Neuman’s Systems Model
Neurobehavioral Development
Newman’s Theory of Health
Nightingale, Florence
Nurse Engagement
Nurse-Led Group Clinic Visits
Nurse and Physician Interdisciplinary Collaboration
Nurse Staffing
Nursing Assessment
Nursing Diagnoses, Interventions, and Outcomes
Nursing Education
Nursing Information Systems and Informatics
Nursing Occupational Injury and Stress
Nursing Practice Models
Nursing Process
Nutrition in the Elderly
Nutrition in Infancy and Childhood
O
Obesity
Observational Research Designs
Orem’s Self-Care Theory
Organizational Culture
Organizational Design
Osteoporosis
Outcome Measures
P
Pain
Palliative Care
Parenting
Parse’s Humanbecoming School of Thought
Participant Observation
Patient Care Delivery Models
Patient Contracting
Patient Education
Patient Engagement and Patient-Centered Care
Patient Safety
Patient Satisfaction
Pediatric Primary Care
Pender’s Health-Promotion Model
Peplau’s Theoretical Model
Phenomenology
Philosophy of Nursing
Physical Restraints
Physiology
Pilot Study
Population Health
Postpartum Depression
Pregnancy
Prevention of Preterm Birth, Preterm Labor, and Low Birth Weight
Primary Nursing
Q
Qualitative Research
Quality of Care
Quality of Life
Quality and Safety Education for Nurses
Quantitative Research
Quasi-Experimental Research
R
Reliability
Reminiscence
Replication Studies
Research Dissemination
Research Interviews (Qualitative)
Research in Nursing Ethics
Research Utilization
Resourcefulness
Responsiveness
Rogers’s Science of Unitary Human Beings
Roy Adaptation Model
Rural Health
S
Sampling
Schizophrenia
Secondary Data Analysis
Self-Efficacy
Self-Management
Self-Transcendence
Serious Mental Illness
Shivering
Simulation
Sleep Science
Smoking Cessation
SNOMED Clinical Terms
Social Support
Spirituality
Statistical Techniques
Story Theory
Stress
Stroke
Structural Equation Modeling
Substance Use Disorders in Professional Nurses
Symptom Management Theory
Systematic Review
T
Telehealth
Terminal Illness
Theoretical Framework
Thermal Balance
Time Series Analysis
Transitional Care
Transitions and Health
Translational Research
Triangulation
U
Uncertainty in Illness
Unlicensed Assistive Personnel
V
Validity
Veterans’ Health
Violence
Virtual Nurse Caring
Vulnerable Populations
W
Wandering
Watson’s Human Caring Science
Weight Management
Wellness
Women’s Health
Workplace Violence
Index

Citation preview

Encyclopedia of

Nursing Research

Joyce J. Fitzpatrick, PhD, MBA, RN, FAAN, FNAP, is Elizabeth Brooks Ford Professor of Nursing, Frances Payne Bolton School of Nursing, Case Western Reserve University (CWRU) in Cleveland, Ohio, where she was dean from 1982 through 1997. She is also adjunct professor, Department of Geriatrics, Ichan School of Medicine, Mount Sinai Hospital, New York, New York. She earned a bachelor of science in nursing (Georgetown University), an MS in psychiatric–mental health nursing (The Ohio State University), a PhD in nursing (New York University), and an MBA (CWRU). In 1990, Dr. Fitzpatrick received an honorary doctorate, Doctor of Humane Letters, from Georgetown University. In 2011, she received an honorary doctorate, Doctor of Humane Letters, from Frontier University of Nursing in Hyden, Kentucky. She was elected a fellow in the American Academy of Nursing (AAN; 1981) and a fellow in the National Academies of Practice (1996). She has received the American Journal of Nursing Book of the Year Award 20 times; and has earned the Midwest Nursing Research Society Distinguished Contribution to Nursing Research Award; The Ohio State University Distinguished Alumna Award; Sigma Theta Tau International (STTI) Elizabeth McWilliams Miller Founders Award for Excellence in Nursing Research; and New York University Division of Nursing Distinguished Alumna Award. In 1994 to 1995, she was the AAN/American Nurses Foundation (ANF)/Institute of Medicine Distinguished Scholar, and in 1995 she was a Primary Care Fellow through the Bureau of Health Professions. Dr. Fitzpatrick received the ANF Distinguished Contribution to Nursing Science Award for sustained commitment and contributions to development of the discipline (2002). Recent awards include the STTI Lucie Kelly Mentor Award (2003); STTI Founders Award for Leadership (2005); Fulbright Scholar at University College Cork, Cork, Ireland (2007–2008); Midwest Nursing Research Society Lifetime Achievement Award (2010); International Academy of Nurse Editors Editors Award (2013); and STTI Research Hall of Fame Induction (2014). In 2016, she was named a Living Legend of the AAN. Dr. Fitzpatrick’s work is widely published in nursing and health care literature with more than 300 publications, including more than 80 authored/edited books. She served as a coeditor of the Annual Review of Nursing Research series, vols. 1 to 26, and she currently edits the journals Applied Nursing Research, Archives of Psychiatric Nursing, and Nursing Education Perspectives, the official journal of the National League for Nursing.

Encyclopedia of

Nursing Research Fourth Edition Joyce J. Fitzpatrick, PhD, MBA, RN, FAAN, FNAP Editor

Copyright © 2018 Springer Publishing Company, LLC All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Springer Publishing Company, LLC, or authorization through payment of the appropriate fees to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, [email protected] or on the Web at www.copyright.com. Springer Publishing Company, LLC 11 West 42nd Street New York, NY 10036 www.springerpub.com Acquisitions Editor: Joseph Morita Compositor: Newgen KnowledgeWorks ISBN: 978-0-8261-3304-5 ebook ISBN: 978-0-8261-3305-2 17 18 19 20 21 / 5 4 3 2 1 The author and the publisher of this Work have made every effort to use sources believed to be reliable to provide information that is accurate and compatible with the standards generally accepted at the time of publication. Because medical science is continually advancing, our knowledge base continues to expand. Therefore, as new information becomes available, changes in procedures become necessary. We recommend that the reader always consult current research and specific institutional policies before performing any clinical procedure. The author and publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance on, the information contained in this book. The publisher has no responsibility for the persistence or accuracy of URLs for external or third-party Internet websites referred to in this publication and does not guarantee that any content on such websites is, or will remain, accurate or appropriate. Library of Congress Cataloging-in-Publication Data Names: Fitzpatrick, Joyce J., 1944- , editor. Title: Encyclopedia of nursing research / Joyce J. Fitzpatrick, editor. Description: Fourth edition. | New York, NY : Springer Publishing Company, LLC, [2018] | Includes bibliographical references and index. Identifiers: LCCN 2017016379 | ISBN 9780826133045 (paper back) | ISBN 9780826133052 (e-book) Subjects: | MESH: Nursing Research | Evidence-Based Nursing | Encyclopedias Classification: LCC RT81.5 | NLM WY 13 | DDC 610.73072—dc23 LC record available at https://lccn.loc.gov/2017016379 Contact us to receive discount rates on bulk purchases. We can also customize our books to meet your needs. For more information please contact: [email protected] Printed in the United States of America by Gasch Printing.

Contents Preface

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Contributors

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List of Entries

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Share Encyclopedia of Nursing Research, Fourth Edition Entries A to W Index

1 801

Preface

This fourth edition of the Encyclopedia of Nursing Research (ENR) is a comprehensive, authoritative, yet concise guide to current nursing research literature. The first edition of ENR grew out of Dr. Ursula Springer’s commitment to nursing research and my commitment to nurse scholars globally. The first edition of ENR followed 15 volumes of the Annual Review of Nursing Research (ARNR) journal. The second edition was published incorporating terms from the first 22 volumes of ARNR. The third edition of ENR not only incorporated topics from the first two editions but also added content through the 30 volumes of ARNR that had been published to date. This fourth edition builds on the prior editions to extend the content to current nursing research. In preparing and organizing the content, we were cognizant of the depth of nursing research in many areas and the expansion of nursing research globally. Nurses at all levels of preparation and in all clinical specialties will find this an important introduction to the depths of nursing research. Previous editions have been most helpful to beginning and graduate students. The summative entries provide the reader with an important starting point for understanding the key research in a content area. References that are cited are those that are most current and relevant, thus providing a timely source of information. The alphabetical ordering

of entries is provided to assist the reader in easily locating a topic. Every effort has been made to be inclusive of all relevant terms in nursing research, which were selected on the basis of the review of previous editions and the extant nursing research literature.

ACKNOWLEDGMENTS This work would not have been possible without the dedication of a number of individuals. First, I would like to acknowledge the nurse researchers whose scientific work and resultant publications led to the inception of an encyclopedia. Second, thanks are extended to all contributors from the four editions for their careful review of the literature and their synopses of the research. In compiling this book, I was assisted by Bertha Ku, then a doctoral student, whose extreme attention to detail made my task much easier. Along the way, Deborah Stilgenbauer, also a doctoral student at the time, assisted us with the overall process. We also thank the staff of Springer Publishing Company, led by our senior acquisitions editor, Joseph Morita, for their thoughtful review and editing of this volume. Collectively, we have all contributed to another important work, one that we should proudly exclaim as the culmination of close to a half century of nursing research. Joyce J. Fitzpatrick

Contributors

Lauren S. Aaronson, PhD, RN, FAAN Professor University of Kansas School of Nursing; and Deputy Director Heartland Institute for Clinical and Translational Research University of Kansas Medical Center Kansas City, Kansas Data Analysis, Fatigue, Grantsmanship, Sampling Faye G. Abdellah, EdD, ScD, RN, FAAN (deceased) History of Nursing Research Ivo Abraham, PhD, RN Professor and Director Center for Health Outcomes and Practice Effectiveness, College of Pharmacy University of Arizona Tucson, Arizona Applied Research, Comparative Effectiveness Research, Experimental Research, Quasi-Experimental Research Raeda Fawzi AbuAlRub, PhD, RN Professor, Nursing Service Administration Dean of Nursing, Director of WHO Collaborating Center Faculty of Nursing/Jordan University of Science and Technology Irbid, Jordan Social Support Barbara Alba, PhD, RN, NEA-BC Director of Nursing for Maternal–Child Health New York–Presbyterian—Lower Manhattan Hospital New York, New York Phenomenology

Ivy M. Alexander, PhD, APRN, ANP-BC, FAAN Professor and Director Adult, Family, Gerontological, and Women’s Health and Primary Care Specialty School of Nursing, Yale University New Haven, Connecticut Women’s Health Celeste M. Alfes, DNP, MSN, RN Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio King’s Theory of Goal Attainment Arwa AL-Hamed, RN, MSN, PNP PhD Student Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Symptom Management Theory Cecilia D. Alvarez, DNP, RN Assistant Professor Fairleigh Dickinson University Teaneck, New Jersey Patient Satisfaction Gene Cranston Anderson, PhD, RN, FAAN Edward J. and Louise Mellen Professor Emerita of Nursing Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Professor Emeritus and Courtesy Faculty College of Nursing University of Florida Gainesville, Florida Kangaroo Care (Skin-to-Skin Contact)

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CONTRIBUTORS

Ida Androwich, PhD, RNC, FAAN Professor School of Nursing Loyola University Medical Center Maywood, Illinois Nursing Information Systems and Informatics Karen J. Aroian, PhD, CNAA-BC Katharine Faville Professor of Nursing Research College of Nursing Wayne State University Detroit, Michigan Immigrant Women Carol A. Ashton, PhD, RN Director of Nursing Research LDS Cottonwood, and Alta View Hospitals Salt Lake City, Utah Research Utilization Joan K. Austin, PhD, RN, FAAN Distinguished Professor Emerita School of Nursing Indiana University Indianapolis, Indiana Epilepsy

Marianne Baernholdt, PhD, MPH, RN, FAAN Director Langston Center for Quality, Safety, and Innovation Nursing Alumni Endowed Distinguished Professor School of Nursing Virginia Commonwealth University Richmond, Virginia Rural Health Mei Bai, PhD, RN Assistant Professor School of Nursing Emory University Atlanta, Georgia Chronic Illness Carolyn Baird, DNP, MBA, RN-BC, CARN-AP, ICCDPD Adjunct Faculty Waynesburg University McMurray, Pennsylvania Addiction Care

Kay C. Avant, PhD, RN, FNI, FAAN Professor Emeritus School of Nursing University of Texas Health Science Center San Antonio, Texas Concept Analysis

Tamilyn Bakas, PhD, RN, FAHA, FAAN Professor School of Nursing, Indiana University Indianapolis, Indiana Stroke

Cynthia Guerrero Ayres, PhD, RN Assistant Professor Rutgers College of Nursing Rutgers, The State University of New Jersey Newark, New Jersey Clinical Preventive Services Lioness Ayres, PhD, RN Assistant Professor College of Nursing University of Iowa Iowa City, Iowa Qualitative Research

Suzanne Bakken, DNSc, RN, FAAN, FACMI Alumni Professor of Nursing and Professor of Biomedical Informatics Director Center for Evidence-Based Practice in the Underserved Director Reducing Health Disparities Through Informatics Pre- and Postdoctoral Training Program Columbia University New York, New York Formal Nursing Languages, SNOMED Clinical Terms

Terry A. Badger, PhD, PMHCNS-BC, RN, FAAN Professor and Director Community and Systems Health Science Division College of Nursing University of Arizona Tucson, Arizona Depression in Families

Karen Bauce, DNP, MPA, RN, NEA-BC Clinical Assistant Professor and Associate Dean MSN Online Program Sacred Heart University Fairfield, Connecticut Cultural/Transcultural Focus

CONTRIBUTORS

Cheryl Tatano Beck, DNSc, CNM, FAAN Professor University of Connecticut School of Nursing Storrs, Connecticut Meta Analysis, Phenomenology, Replication Studies Abir K. Bekhet, PhD, RN, HSMI Assistant Professor College of Nursing Marquette University Milwaukee, Wisconsin Depression in Older Adults Amy Berman, BSN, LHD Senior Program Officer The John A. Hartford Foundation New York, New York Acute Care of the Elderly Sandra C. Garmon Bibb, DNSc, RN, FAAN Dean and Professor College of Health Professions Wichita State University Wichita, Kansas Leininger’s Theory of Culture Care Diversity and Universality, Population Health Alyson Blanck, MSN, RN, NEA-BC Director of Nursing Practice Danbury Hospital Danbury, Connecticut Patient Education Sheila M. Blank, MSN, RN Doctoral Student Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Philosophy of Nursing Sharon Boris, MSN, RN Assistant Professor Cuyahoga Community College Strongsville, Ohio Patient Satisfaction

Meg Bourbonniere, PhD, RN Vice President for Nursing Research Thomas Jefferson University Hospital Philadelphia, Pennsylvania Physical Restraints Karyn L. Boyar, DNP, FNP-BC, RN Faculty/Assistant, Clinical Professor Rory Meyers College of Nursing New York University College of Nursing New York, New York Mentoring, Unlicensed Assistive Personnel Beth Boyd, DNP, MSN, RN, CNE Sacred Heart University College of Nursing Fairfield, Connecticut Workplace Violence Diane K. Boyle, PhD, RN School of Nursing University of Kansas Kansas City, Kansas Job Satisfaction

Barbara J. Braband, EdD, CNE, RN Associate Professor University of Portland School of Nursing Portland, Oregon Collaborative Research

Holly B. Bradley, DNP, MS, ANP-BC, APRN Clinical Assistant Professor College of Nursing Sacred Heart University Fairfield, Connecticut Clinical Preventive Services

Geraldine A. Britton, PhD, RN Assistant Research Professor Decker School of Nursing Binghamton University Binghamton, New York Osteoporosis

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CONTRIBUTORS

Dorothy Brooten, PhD, RN, FAAN Professor School of Nursing Florida International University Miami, Florida Clinical Trials Theresa Bucco, PhD, RN-BC Staten Island, New York Boykin and Schoenhofer: Nursing as Caring Theory Christopher J. Burant, PhD, RN Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Factor Analysis Sara L. Campbell, PhD, RN, NEA-BC Professor and Dean School of Nursing Lee University Cleveland, Tennessee Feminist Research Methodology Suzanne Hetzel Campbell, PhD, WHNP-BC, IBCLC Associate Professor University of British Columbia School of Nursing Vancouver, British Columbia, Canada Breastfeeding, Simulation Lucinda Canty, MSN, RN, CNM Assistant Professor of Nursing University of Saint Joseph West Hartford, Connecticut Women’s Health Roger Carpenter, PhD, RN Assistant Professor West Virginia University School of Nursing Morgantown, West Virginia Cognitive Appraisal Eileen J. Carter, PhD, RN Nurse Researcher/Nurse Scientist Columbia University School of Nursing New York-Presbyterian Hospital New York, New York Research Interviews (Qualitative)

Kenrick D. Cato, PhD, RN, CPHIMS Nurse Researcher/Nurse Scientist Columbia University School of Nursing New York-Presbyterian Hospital New York, New York SNOMED Clinical Terms Sandy N. Cayo, DNP, FNP-BC, APRN Clinical Assistant Professor New York University Rory Meyers College of Nursing New York, New York History of Nursing Research Jeeyae Choi, DNSc, RN Clinical Informatician Spaulding Rehabilitation Hospital Boston, Massachusetts Formal Nursing Languages Sean P. Clarke, PhD, RN, FAAN RBC Chair in Cardiovascular Nursing Research Lawrence S. Bloomberg Faculty of Nursing University of Toronto Peter Munk Cardiac Centre University Health Network Toronto, Ontario, Canada Nurse Staffing, Organizational Culture, Organizational Design Elizabeth R. Click, ND, RN, CWP Assistant Professor Frances Payne Bolton School of Nursing Medical Director Case Western Reserve University Cleveland, Ohio Wellness Amy Coenen, PhD, RN, FAAN College of Nursing University of Wisconsin—Milwaukee Milwaukee, Wisconsin International Classification of Nursing Practice Marlene Zichi Cohen, PhD, RN, FAAN Professor and Kenneth E. Morehead Endowed Chair in Nursing Associate Dean for Research College of Nursing University of Nebraska Medical Center Omaha, Nebraska Descriptive Research, Nursing Assessment

CONTRIBUTORS

Rosemary Collier, MSN, RN PhD Student Decker School of Nursing Binghamton University Binghamton, New York Osteoporosis Linda L. Cook, DNP, APRN, NNP-BC, CNL Program Director Clinical Nurse Leader Track Assistant Professor Sacred Heart University Fairfield, Connecticut Failure to Thrive (Child) Inge B. Corless, PhD, RN, FAAN Amelia Peabody Professor of Nursing Research Institute of Health Professions Massachusetts General Hospital Boston, Massachusetts Hospice, Terminal Illness Michele Crespo-Fierro, PhD, RN, MS/MPH, AACRN Clinical Instructor New York University Rory Meyers College of Nursing New York, New York Patient Engagement and Patient-Centered Care Jeff Day, DNP, AGPCNP-BC Clinical Assistant Professor New York University Rory Meyers College of Nursing New York, New York End-of-Life Planning Sabina De Geest, PhD, RN, FAAN Professor and Director Institute of Nursing Science University of Basel Basel, Switzerland Applied Research Alice S. Demi, PhD, RN, FAAN Professor Byrdine F. Lewis School of Nursing, Georgia State University Atlanta, Georgia Delphi Technique

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Sherry C. Detrick, MBA, BSN, RN Nursing Program Coordinator Kent State University at Ashtabula Ashtabula, Ohio Orem's Self-Care Theory Mary Jo Devereaux, MLS, CME Hospital Librarian Community Medical Center Scranton, Pennsylvania Orem’s Self-Care Theory Marguerite A. DiMarco, PhD, RN, CPNP, FAAN Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Nutrition in Infancy and Childhood Rose Ann DiMaria-Ghalili, PhD, RN Associate Professor College of Nursing and Health Professions Drexel University Philadelphia, Pennsylvania Nutrition in the Elderly Marianne Ditomassi, DNP, MBA, RN, NEA-BC Executive Director of Nursing & Patient Care Services Operations and Magnet Recognition Massachusetts General Hospital Boston, Massachusetts Nursing Practice Models Mary A. Dolansky, PhD, RN, FAAN Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Quality and Safety Education for Nurses Moreen Donahue, DNP, RN, NEA-BC Senior Vice President Patient Care Services and Chief Nurse Executive Danbury Hospital Danbury, Connecticut Clinical Judgment Sue K. Donaldson, PhD, RN, FAAN Professor Emory University Atlanta, Georgia Basic Research

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CONTRIBUTORS

Evelyn G. Duffy, DNP, G/ANP-BC, FAANP Associate Professor Director of the Adult-Gerontological Nurse Practitioner Program Associate Director of the University Center on Aging and Health Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Osteoporosis Jacqueline Dunbar-Jacob, PhD, RN, FAAN Professor Nursing Psychology, Epidemiology, and Occupational Therapy Dean School of Nursing University of Pittsburgh Pittsburgh, Pennsylvania Adherence/Compliance, Behavioral Research Patricia C. Dykes, PhD, RN, FAAN, FACMI Senior Nurse Scientist, Program Director Center for Patient Safety Research and Practice Program Director Center for Nursing Excellence Brigham and Women’s Hospital Associate Professor Harvard Medical School Boston, Massachusetts Clinical Judgment, Nursing Information Systems and Informatics Emerson E. Ea, DNP, PhD, APRN, BC, CEN Clinical Assistant Professor and Assistant Dean Rory Meyers College of Nursing New York University New York, New York Acculturation

Azita Emami, PhD, RN, FAAN Dean and Professor University of Washington School of Nursing Seattle, Washington Global Nursing Research Veronica F. Engle Professor College of Nursing and College of Medicine University of Tennessee Health Science Center Memphis, Tennessee Newman’s Theory of Health Carol Diane Epstein, PhD, RN, FCCM Associate Professor, Director Combined Degree Program Lienhard School of Nursing Pace University Pleasantville, New York Critical Care Nursing Research William Scott Erdley, DNS, RN, CHSE Simulation Educational Specialist Behling Simulation Center, Jacobs School of Medicine & Biomedical Sciences University at Buffalo, Buffalo, New York Adjunct Professor, School of Nursing Niagara University, New York Electronic Network Lisa Ericson, MSN, RN, FNP Assistant Professor School of Nursing Bethel College Mishawaka, Indiana Symptom Management Theory

Shelly Eisbach, PhD, RN Morton and Jane Blaustein Postdoctoral Fellow in Mental Health and Psychiatric Nursing School of Nursing Johns Hopkins University Baltimore, Maryland Mother–Infant/Toddler Relationships

Lois K. Evans, PhD, RN, FAAN Van Ameringen Professor in Nursing Excellence School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Physical Restraints

Marsha L. Ellett, PhD, RN Professor School of Nursing Indiana University Indianapolis, Indiana Enteral Tube Placement

Deborah B. Fahs, DNP, MSN, APRN, CPNP Lecturer School of Nursing Yale University New Haven, Connecticut Eating Disorders

CONTRIBUTORS

Melissa Spezia Faulkner, DSN, RN, FAAN Gladys E. Sorensen Endowed Professor Diabetes Research College of Nursing University of Arizona Tucson, Arizona Diabetes Suzanne Feetham, PhD, RN, FAAN Visiting Professor University of Wisconsin Milwaukee, Wisconsin Nursing Research Consultant Children’s National Medical Center Washington, DC Family Health Donna M. Fick, PhD, GCNS-BC, FGSA, FAAN School of Nursing Pennsylvania State University University Park, Pennsylvania Ageism Ellen Fineout-Overholt, PhD, RN, FNAP, FAAN Professor University of Texas Tyler College of Nursing & Health Sciences Tyler, Texas Evidence-Based Practice Mary L. Fisher, PhD, RN, CNAA, BC Associate Professor School of Nursing Indiana University Indianapolis, Indiana Cost Analysis of Nursing Care Joyce J. Fitzpatrick, PhD, MBA, RN, FAAN Elizabeth Brooks Ford Professor of Nursing Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Conceptual Model Jane Flanagan, PhD, ANP-BC Assistant Professor William F. Connell School of Nursing Boston College Chestnut Hill, Massachusetts Nurse Scientist Yvonne L. Munn Center for Nursing Research Massachusetts General Hospital Boston, Massachusetts Functional Health Patterns, Nursing Practice Models

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Ann Fournier, PhD, MS, MSN, RN, ACNP-BC, CNE Instructor of Nursing Saint Anselm College Manchester, New Hampshire Pender’s Health Promotion Model Emily J. Fox-Hill, PhD, RN Assistant Professor College of Nursing University of Tennessee Health Science Center Memphis, Tennessee Newman’s Theory of Health Maureen A. Frey, PhD, RN Director of Research and Advanced Practice Children’s Hospital of Michigan Detroit, Michigan King’s Theory of Goal Attainment Terry Fulmer, PhD, RN, FAAN President John A. Hartford Foundation New York, New York Acute Care of the Elderly, Elder Mistreatment Lori A. Fusco, MSN, RN, CNE Clinical Nursing Instructor Simulation Coordinator Youngstown State University Youngstown, Ohio Philosophy of Nursing Mary Anne Gallagher, MA, RN-BC Director of Nursing for Quality New York-Presbyterian Hospital New York, New York Adjunct Faculty Adelphi University College of Nursing and Public Health Garden City, New York Research Utilization Carol D. Gaskamp, PhD, RN, CNE Assistant Professor of Clinical Nursing Division Chair Family, Public Health Nursing, and Nursing Administration Division School of Nursing University of Texas at Austin Austin, Texas Spirituality

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CONTRIBUTORS

Lisa Ann S. Gittner, PhD Associate Professor Texas Tech University Lubbock, Texas Nutrition in Infancy and Childhood

Sarah E. Givens, BSN, RN-BC PhD Student Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Cohort Design, Pilot Study

Susan A. Goncalves, DNP, MS, RN-BC Assistant Professor Sacred Heart University College of Nursing Fairfield, Connecticut Replication Studies, Research Dissemination, Research in Nursing Ethics, Triangulation

Marion Good, PhD, RN, FAAN Professor Emeritus Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Music Therapy, Pain Patricia A. Grady, PhD, RN, FAAN Director National Institute of Nursing Research National Institutes of Health Bethesda, Maryland National Institute of Nursing Research Judith R. Graves, PhD, RN, FAAN Professor College of Nursing University of Utah Salt Lake City, Utah Secondary Data Analysis Bobbe Ann Gray, PhD, RNC-OB, CNS-BC Associate Professor, Director Doctor of Nursing Practice Program College of Nursing and Health Wright State University Dayton, Ohio Childbirth Education

Mary T. Quinn Griffin, PhD, RN, FAAN, ANEF Professor of Nursing Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Genetics, Health Conceptualization, Institutional Review Board and Informed Consent, Parse’s Humanbecoming School of Thought, Roy Adaptation Model Rebecca Grizzle, PhD, RN, ANP-C Clinical Assistant Professor Sacred Heart University Fairfield, Connecticut Health Care–Associated Infections Deborah Gross, DNSc, RN, FAAN Leonard and Helen Stulman Professor in Mental Health and Psychiatric Nursing School of Nursing and School of Medicine Department of Psychiatry and Behavioral Sciences Johns Hopkins University Baltimore, Maryland Mother–Infant/Toddler Relationships Patricia S. Groves, PhD, RN Associate Professor College of Nursing University of Iowa Iowa City, Iowa Qualitative Research Sarah H. Gueldner, PhD, RN, FAAN (deceased) Osteoporosis Barbara J. Guthrie, PhD, RN, FAAN Professor and Associate Dean School of Nursing Northeastern University Boston, Massachusetts Eating Disorders Barbara K. Haight, DrPH, RNC, FAAN Professor Emeritus, College of Nursing Medical University of South Carolina Charleston, South Carolina Reminiscence

CONTRIBUTORS

Emily J. Hauenstein, PhD, LCP, RN, FAAN Thomas A. Saunders III Family Professor and Director Southeastern Rural Mental Health Research Center School of Nursing University of Virginia Charlottesville, Virginia Depression in Women Laura L. Hayman, PhD, RN, FAAN Associate Dean for Research Professor of Nursing College of Nursing and Health Sciences University of Massachusetts Boston Director of Research GoKids Boston Boston, Massachusetts Cardiovascular Risk Factors, Nutrition in Infancy and Childhood

Martha N. Hill, PhD, RN, FAAN Dean and Professor Emerita Department of Health Systems and Outcomes School of Nursing, Johns Hopkins University Baltimore, Maryland Hypertension Cheryl R. Dennison Himmelfarb, PhD, RN, ANP Associate Professor Department of Health Systems and Outcomes School of Nursing, Division of Health Sciences Informatics School of Medicine Johns Hopkins University Baltimore, Maryland Hypertension Sandra Daack-Hirsch, PhD, RN Associate Professor and Director, PhD Program College of Nursing University of Iowa Iowa City, Iowa Ethnography Marilyn Hockenberry, PhD, RN-CS, PNP, FAAN Professor of Pediatrics Department of Hematology–Oncology Baylor College of Medicine Nurse Scientist, Director Center for Nursing Research Texas Children’s Hospital Houston, Texas Cancer in Children

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Diane Holditch-Davis, PhD, RN, FAAN Marcus Hobbs Distinguished Professor of Nursing Associate Dean for Research Affairs School of Nursing Duke University Durham, North Carolina Neurobehavioral Development, Parenting Cheryl Holly, EdD, RN Associate Professor Codirector New Jersey Center for Evidence-Based Practice Joanna Briggs Institute Collaborating Center School of Nursing Rutgers University Newark, New Jersey Systematic Review Barbara J. Holtzclaw, PhD, RN, FAAN Nurse Scientist, Professor, Associate Director Geriatric Nursing Translational Research Training Donald W. Reynolds Center of Geriatric Nursing Excellence College of Nursing and Graduate College University of Oklahoma Health Sciences Center Oklahoma City, Oklahoma Professor Emeritus School of Nursing University of Texas Health Science Center at San Antonio San Antonio, Texas Fever, Shivering, Thermal Balance June Andrews Horowitz, PhD, RN, FAAN Professor William F. Connell School of Nursing Boston College Chestnut Hill, Massachusetts Postpartum Depression Ann C. Hurley, DNSc, RN, FAAN Senior Nurse Scientist Emerita Center for Nursing Excellence Brigham and Women’s Hospital Boston, Massachusetts Mental Status Measurement

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Sally A. Hutchinson, PhD, RN, FAAN Professor University of Florida College of Nursing Jacksonville, Florida Grounded Theory, Research Interviews (Qualitative) Kathleen Huttlinger, PhD, RN Professor Associate Director for Graduate Programs School of Nursing College of Health and Social Services New Mexico State University Las Cruces, New Mexico Content Analysis, Exploratory Studies, Participant Observation Rose Iannino-Renz, DNP, APRN, FNP-BC Assistant Professor of the Practice EGAN School of Nursing and Health Studies Fairfield University Fairfield, Connecticut Ageism Gail L. Ingersoll, EdD, RN, FAAN Professor and Associate Dean for Research University of Rochester School of Nursing Rochester, New York Evaluation Pamela M. Ironside, PhD, RN, FAAN, ANEF Professor Director of the Center for Research in Nursing Education School of Nursing, Indiana University Indianapolis, Indiana Hermeneutics Molly Jackson, DNP, APRN, AGNP-C, ACHPN Assistant Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Family Caregiving and the Seriously Mentally Ill, Schizophrenia Sharol F. Jacobson, PhD, RN, FAAN Associate Dean for Research and Practice, Professor University of Alabama School of Nursing Tuscaloosa, Alabama Cultural/Transcultural Focus

Annette Jakubisin-Konicki, PhD, APRN, ANP-BC, FNP-BC Associate Clinical Professor Graduate Coordinator Family Nurse Practitioner Primary Care Program School of Nursing University of Connecticut Storrs, Connecticut Women’s Health Connie A. Jastremski, MS, MBA, RN, FCCM Chief Nursing Officer and Vice President Patient Care Services Bassett Healthcare Cooperstown, New York Patient Care Delivery Models Laurie S. Jeffers, DNP, FNP-BC Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Menopause Amy R. Johnson, MAT, MA, LLPC, TLS, CPDT-KA Special Projects Coordinator School of Nursing Oakland University Rochester, Michigan Animal-Assisted Interventions Catherine E. Johnson, PhD, RN, CNE Assistant Professor of Nursing Westfield State University Southwick, Massachusetts Primary Nursing Jarold Johnston, MSN, CNM, IBCLC Assistant Professor of Nursing Methodist University Fayetteville, North Carolina Self-Efficacy Joyce Johnston MBA, RN Practice Manager Hospitalist Department Carilion Clinic Roanoke, Virginia Wellness

CONTRIBUTORS

Dorothy A. Jones, EdD, RN, FAAN Professor William F. Connell School of Nursing Boston College Chestnut Hill, Massachusetts Director Yvonne L. Munn Center for Nursing Research Massachusetts General Hospital Boston, Massachusetts Functional Health Patterns, Nursing Practice Models

Vicki Keough, PhD, RN, ACNP Dean School of Nursing Loyola University Chicago Chicago, Illinois Emergency Nursing Mary E. Kerr, PhD, RN, FAAN Dean and May L. Wykle Endowed Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Cerebral Ischemia

Jeffrey Schwab Jones, DNP, PMHCNS-BC, LNC Board Certified-Psychiatric Clinical Nurse Specialist Legal Nurse Consultant Pinnacle Mental Health Associates, Inc. Mansfield, Ohio Interpersonal Communication

Shaké Ketefian, EdD, RN, FAAN Professor Emerita Office of International Affairs School of Nursing University of Michigan Ann Arbor, Michigan Research in Nursing Ethics

Josette Jones, PhD, RN Assistant Professor School of Informatics–School of Nursing Indiana University Indianapolis, Indiana Telehealth

Hesook Suzie Kim, PhD, RN Professor Emerita College of Nursing University of Rhode Island Kingston, Rhode Island Action Science, Discourse Analysis, Narrative Analysis

Stacen Keating, PhD, RN Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Violence Maureen Keckeisen, MN, RN, CCRN Clinical Nurse Specialist Liver Transplant/Surgical Specialties ICU University of Los Angeles Health System Los Angeles, California Hemodynamic Monitoring Susan J. Kelley, PhD Dean and Professor College of Health and Human Sciences Georgia State University Atlanta, Georgia Grandparents Raising Grandchildren

Tae Youn Kim, PhD, RN Assistant Professor College of Nursing University of Wisconsin—Milwaukee Milwaukee, Wisconsin International Classification of Nursing Practice Chiemi Kochinda, PhD, RN Assistant Professor School of Nursing University of Kansas Kansas City, Kansas Instrument Translation Katharine Kolcaba, PhD, RN Associate Professor (Emerita) The University of Akron Akron, Ohio Owner/Consultant The Comfort Line Chagrin Falls, Ohio Comfort Theory

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Robin S. Krinsky, DNP, RN-BC, CCRN Adjunct Assistant Professor Department of Nursing Lehman College New York, New York Hemodynamic Monitoring

Yi-Hui Lee, PhD, RN Associate Professor College of Nursing and Health Wright State University Dayton, Ohio Depression and Cardiovascular Diseases, HIV Risk Behavior

Heidi V. Krowchuk, PhD, RN, FAAN Associate Professor School of Nursing The University of North Carolina at Greensboro Greensboro, North Carolina Failure to Thrive (Child)

Elizabeth R. Lenz, PhD, RN, FAAN Dean and Professor Emerita College of Nursing Ohio State University Columbus, Ohio Doctoral Education

Tammy Lampley, PhD, RN, CNE Director of Nursing Education Program Sacred Heart University Fairfield, Connecticut Ethics of Research

Eugene Levine, PhD Professor Emeritus Uniformed Services Graduate School of Nursing University of the Health Sciences Bethesda, Maryland Quantitative Research

Marjorie Thomas Lawson, PhD, APRN, BC, FNP Associate Professor and Graduate Coordinator Maine College of Nursing and Health Professions University of Southern Maine Portland, Maine Interpersonal Communication Mark Lazenby, PhD, RN Lecturer School of Nursing Yale University New Haven, Connecticut Chronic Illness Patricia Leahy-Warren, PhD, MSc RPHN, RM, RGN Senior Lecturer Catherine McAuley School of Nursing and Midwifery University College Cork Ireland Postpartum Depression Regina Placzek Lederman, RN, MN Ed, MA, PhD, FAAN Professor Emeritus, UTMB SON Adjunct Professor, UT-Health Science Center, School of Public Health Houston, Texas Maternal Anxiety and Psychosocial Adaptation During Pregnancy

Irene D. Lewis, DNS, APN, FAAN (deceased) Ethnogeriatrics Judith A. Lewis, PhD, RN, WHNP-BC, FAAN Professor Emerita School of Nursing Virginia Commonwealth University Richmond, Virginia Genetics Lisa M. Lewis, PhD, RN, FAAN Assistant Dean for Diversity and Inclusivity Associate Professor University of Pennsylvania School of Nursing Philadelphia, Pennsylvania Health Disparities: Focus on Racial and Ethnic Minorities Suling Li, PhD, RN Director Institute for Emergency Nursing Research, Emergency Nurses Association Burr Ridge, Illinois Emergency Nursing Patricia Liehr, PhD, RN Sharon Raddock Distinguished Professor Christine F. Lynn College of Nursing Florida Atlantic University Boca Raton, Florida Middle-Range Theories, Story Theory

CONTRIBUTORS

Fidelindo Lim, DNP, RN, CCRN Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Rogers’s Science of Unitary Human Beings Deborah F. Lindell, DNP, MSN, RN, CNE, ANEF Associate Professor of Nursing Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Conceptual Model, Content Analysis, Delphi Technique, Grounded Theory, Theoretical Framework, Uncertainty in Illness Adrianne D. Linton, PhD, RN, FAAN Chair and Professor Department of Family and Community Health Systems School of Nursing University of Texas Health Science Center at San Antonio San Antonio, Texas Wandering Pamela B. Linzer, MSN, RN Doctoral Student Connell School of Nursing Boston College Chestnut Hill, Massachusetts Nurse Staffing, Organizational Design Terri H. Lipman, PhD, CRNP, FAAN Miriam Stirl Endowed Term Professor of Nutrition Professor of Nursing of Children School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Clinical Decision Making Jane Lipscomb, PhD, RN, FAAN Professor and Director Work and Health Research Center School of Nursing University of Maryland Baltimore, Maryland Workplace Violence

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Jenna LoGiudice, PhD, CNM, RN Assistant Professor Egan School Fairfield University Fairfield, Connecticut Women’s Health Karen MacDonald, PhD, RN Chief Executive Matrix 45 Earlysville, Virginia Applied Research, Comparative Effectiveness Research, Experimental Research, Quasi-Experimental Research Melissa Lehan Mackin, PhD, RN Assistant Professor College of Nursing University of Iowa Iowa City, Iowa Qualitative Research Gina Maiocco, PhD, RN, CNS-BC Clinical Professor Director, PhD Program West Virginia University School of Nursing Morgantown, West Virginia Veteran’s Health Judith A. Maloni, PhD, RN, FAAN Professor Emerita Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Prevention of Preterm Birth, Preterm Labor, and Low Birth Weight Linda Manfrin-Ledet, DNS, APRN, BC Associate Professor of Nursing Nicholls State University Thibodaux, Louisiana Violence Marie Manthey, MNA, RN, FAAN President Emeritus Creative Healthcare Management Minneapolis, Minnesota Primary Nursing

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Nadine Montisano-Marchi, DNP, RN, CNE, CRRN Instructor Frances Payne Bolton School of Nursing Case Western Reserve University QSEN Institute Teaching Strategies Coordinator Transitional Care Coordinator-Cleveland Clinic Cleveland, Ohio Music Therapy, Nursing Process, Quality and Safety Education for Nurses Jane F. Marek, DNP, MSN, RN Assistant Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Enteral Tube Placement, Osteoporosis Patricia A. Martin, PhD, RN, FAAN Dean and Professor Emerita College of Nursing and Health Wright State University Dayton, Ohio Research Dissemination Marianne Matzo, PhD, GNP-BC, FPCN, FAAN Professor Frances E. and A. Earl Ziegler Chair in Palliative Care Nursing Sooner Palliative Care Institute: Dedicated to Excellence in Palliative Care Education, Research, and Practice Adjunct Professor Department of Geriatric Medicine College of Nursing University of Oklahoma Oklahoma City, Oklahoma Palliative Care

Donna E. McCabe, DNP, APRN-BC, GNP Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Depression and Cardiovascular Diseases, Wandering Geraldine McCarthy, PhD, MSN, MEd, DNS, RGN, RNT Dean and Professor Emerita Catherine McCauley School of Nursing and Midwifery University College Cork Cork, Ireland Mild Cognitive Impairment Ruth McCorkle, PhD, RN, FAAN Florence Wald Prof Nursing and Epidemiology and Public Health School of Nursing Yale University New Haven, Connecticut Chronic Illness Susan H. McCrone, PhD, RN, PMHCHS-BC Professor and Chair Health Promotion/Risk Reduction Department School of Nursing West Virginia University Morgantown, West Virginia Coronary Artery Bypass Graft Surgery Graham J. McDougall, Jr., PhD, RN, FAAN, FGSA Professor Capstone College of Nursing University of Alabama Tuscaloosa, Alabama Alzheimer’s Disease

Linda J. Mayberry, PhD, RN, FAAN Associate Adjunct Professor New York University New York, New York Postpartum Depression

Michele McKelvey, PhD, RN Assistant Professor of Nursing Central Connecticut State University New Britain, Connecticut Women’s Health

Melen R. McBride, PhD, RN, FGSA Associate Director Stanford Geriatric Education Center School of Nursing Stanford University Stanford, California Ethnogeriatrics

Gretchen A. McNally, PhD, RN, ANP-BC Nurse Practitioner–Hematology Dr. John Byrd and Dr. Joseph Flynn Arthur G. James Cancer Hospital Ohio State University Columbus, Ohio Smoking Cessation

CONTRIBUTORS

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Brenda McNeil, MSN, RN, APRN Adjunct Faculty School of Nursing University of Connecticut Storrs, Conneciicut Women’s Health

Bernadette Mazurek Melnyk, PhD, RN, CPNP/ PMHNP, FAANP, FNAP, FAAN Vice President for Health Promotion University Chief Wellness Officer Dean and Professor, College of Nursing Professor of Pediatrics & Psychiatry, College of Medicine Executive Director, the Helene Fuld Health Trust National Institute for EBP President, the National Consortium for Building Healthy Academic Communities (NCBHAC) Columbus, Ohio Evidence-Based Practice

Barbara Medoff-Cooper, PhD, RN, FAAN Ruth M. Colket Professor of Pediatric Nursing Director Biobehavioral Research Center School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Neurobehavioral Development

Victoria Menzies, PhD, RN Center for the Study of Complementary and Alternative Therapies School of Nursing University of Virginia Charlottesville, Virginia Complementary Health Approaches

Paula M. Meek, PhD, RN, FAAN Professor, Senior Scholar Division Chair Adult and Senior Health Health Science Center College of Nursing University of Colorado Denver Aurora, Colorado Instrumentation, Reliability, Responsiveness, Validity

Martha G. Meraviglia, PhD, RN, CNS Associate Professor of Clinical Nursing School of Nursing University of Texas at Austin Austin, Texas Spirituality

Janet C. Meininger, PhD, RN, FAAN Lee and Joseph D. Jamail Distinguished Professor School of Nursing Professor School of Public Health University of Texas Health Science Center at Houston Houston, Texas Observational Research Design

DeAnne K. Hilfinger Messias, PhD, RN, FAAN College of Nursing and Women’s and Gender Studies School of Nursing University of South Carolina Columbia, South Carolina Immigrant Women

Afaf Ibrahim Meleis, PhD, FAAN Professor of Nursing and Sociology and Dean Emeritus University of Pennsylvania Philadelphia, Pennsylvania Global Nursing Research, Immigrant Women, Transitions and Health

Bonnie L. Metzger, PhD, RN, FAAN Professor Emerita School of Nursing University of Michigan Ann Arbor, Michigan Time Series Analysis

Mary J. McNamee, PhD, RN Director Office of Student Equity and Multicultural Affairs Assistant Vice Chancellor for Academic Affairs University of Nebraska Medical Center Omaha, Nebraska Homeless Health

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Raquel M. Meyer, PhD, RN Assistant Professor Lawrence S. Bloomberg Faculty of Nursing University of Toronto Toronto, Ontario, Canada Organizational Culture

Sue Moorhead, PhD, RN Associate Professor and Director for the Center for Nursing Classification and Clinical Effectiveness College of Nursing The University of Iowa Iowa City, Iowa Nursing Diagnoses, Interventions, and Outcomes

Peggy A. Miller, PhD, RN Research Assistant Professor University of Kansas Medical Center Kansas City, Kansas Job Satisfaction

Diana Lynn Morris, PhD, RN, FAAN Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Watson’s Human Caring Science

Susan M. Miovech, PhD, RNC-OB Associate Professor (Retired) Holy Family University Philadelphia, Pennsylvania Fetal Monitoring

Lora J. Morris, PhD, RN Associate Professor Kent State University at Ashtabula Ashtabula, Ohio Orem’s Self-Care Theory

Merle H. Mishel, PhD, RN, FAAN Kenan Professor of Nursing Emerita School of Nursing University of North Carolina Chapel Hill, North Carolina Uncertainty in Illness Ethel L. Mitty, EdD, RN Adjunct Clinical Professor of Nursing College of Nursing New York University New York, New York End-of-Life Planning, Unlicensed Assistive Personnel Kristen S. Montgomery, PhD, RN Assistant Professor University of North Carolina at Charlotte Charlotte, North Carolina Pregnancy Fitzpatrick’s Life-Perspective Rhythm Model, Pregnancy Watson’s Human Caring Science

Shirley M. Moore, PhD, RN, FAAN Professor and Associate Dean for Research Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Theoretical Framework

Barbara Munro, PhD, RN, FAAN Professor School of Nursing, Boston College Chestnut Hill, Massachusetts Data Management, Statistical Techniques Carol M. Musil, PhD, RN, FAAN Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Cohort Design, Pilot Study Cheryl Nadeau, DNP, MPH, FNP, APHN, CNE Assistant Clinical Professor NYU Rory Meyers College of Nursing Staten Island, New York Neuman’s Systems Model Madeline A. Naegle, PhD, APRN, BC, FAAN Professor and Coordinator Advanced Practice Nursing: Psychiatric-Mental Health Rory Meyers College of Nursing New York University International Programs Director WHO Collaborating Center for Geriatric Nursing Education New York University New York, New York Substance Use Disorders in Professional Nurses

CONTRIBUTORS

Jennifer L. Nahum, DNP, RN, PPCNP-BC, CPNP-AC Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Child Lead Exposure Levels Alvita Nathaniel, PhD, FNP-BC, FAANP Associate Professor School of Nursing West Virginia University Charleston, West Virginia Moral Distress, Moral Reckoning Mary D. Naylor, PhD, RN, FAAN Director New Courtland Center for Transitions and Health School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Transitional Care Leslie Neal-Boylan, PhD, APRN, CRRN, APRN-BC, FNP Dean and Professor University of Wisconsin Oshkosh Oshkosh, Wisconsin Home Health Systems M. Janice Nelson, PhD, RN Retired Dean and Professor Emerita Upstate Medical University College of Nursing Syracuse, New York Patient Care Delivery Models Noreen Nelson, PhD, RN, CNS, CNE Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Advance Directives, Continuing Care Retirement Communities Kathleen M. Nokes, PhD, RN, FAAN Professor and Director of the Graduate Nursing Program Hunter-Bellevue School of Nursing Hunter College City University of New York Stone Ridge, New York HIV/AIDS Care and Treatment

Jeanne Marie Novotny, PhD, RN, FAAN Dean and Professor Gayle Greve Hunt School of Nursing Texas Tech University Health Sciences Center El Paso, Texas Nursing Education

Cassandra Okechukwu, ScD, MSN, RN Assistant Professor of Society Human Development and Health Harvard School of Public Health Boston, Massachusetts Workplace Violence

Lister Onsongo, PhD, RN Lecturer School of Nursing Kenyatta University Nairobi, Kenya Ethnography

Patti Hart O’Regan, DNP, ARNP, ANP-C, PMHNP-BC, LMHC President and CEO Village Health LLC Port Richey, Florida Quality of Care

Thaddeus W. W. Pace, PhD Assistant Professor University of Arizona College of Nursing Tucson, Arizona Depression in Families

Beth Palmer, DNP, ACNS-BC, ANP-BC Nurse Practitioner VA San Diego Healthcare System San Diego, California Nurse Engagement

Annette Peacock-Johnson, DNP, RN  Associate Professor of Nursing Saint Mary’s College Notre Dame, Indiana Empathy

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Heather Peralta, DHSc, MSN, RN Adjunct Nursing Faculty Sacred Heart University and University of Central Florida Apopka, Florida Henderson Model Margaret Dexheime Pharris, PhD, RN, CNE, FAAN Professor St. Catherine University St. Paul, Minnesota Newman’s Theory of Health John Phillips Professor Emeritus, School of Education, New York University, New York, New York Rogers’s Science of Unitary Human Beings Sally Phillips, PhD, RN Director Public Health Emergency Preparedness Program Agency for Health Care Research and Quality Rockville, Maryland Caring, Nursing Process Ubolrat Piamjariyakul, PhD, RN Research Associate Professor School of Nursing University of Kansas Kansas City, Kansas Caregiver, Nurse-Led Group Clinic Visits Denise F. Polit, FAAN Professor School of Nursing Griffith University Gold Coast, Australia President Humanalysis, Inc. Saratoga Springs, New York Data-Collection Methods Sue A. Popkess-Vawter, PhD, RN Professor University of Kansas School of Nursing Kansas City, Kansas Weight Management

Demetrius J. Porche, DNS, PhD, APRN-FNP, FAANP, FAAN Dean and Professor Health Sciences Center School of Nursing Louisiana State University New Orleans, Louisiana Violence MariLou Prado-Inzerillo, DNP, RN, NEA-BC Corporate Director of Nursing NewYork-Presbyterian Hospital New York, New York Nurse Engagement Diane Shea Pravikoff, PhD, RN, FAAN Director of Research/Professional Liaison CINAHL Information Systems Glendale, California CINAHL Database Tara C. Prescott, DNP, RN Quality Division Exeter Hospital Exeter, New Hampshire Nurse and Physician Interdisciplinary Collaboration Jana L. Pressler, PhD, RN Professor and Assistant Dean UNMC College of Nursing Lincoln, Nebraska Fitzpatrick’s Life-Perspective Rhythm Model Pamela G. Reed, PhD, RN, FAAN Professor College of Nursing University of Arizona Tucson, Arizona Peplau’s Theoretical Model Karen M. Reeder, PhD, RN Senior Research Associate School of Nursing University of Kansas Kansas City, Kansas Quality of Life, Self-Management

CONTRIBUTORS

Sally Reel, PhD, RN Clinical Professor and Associate Dean for Practice College of Nursing University of Arizona Tucson, Arizona Comparative Effectiveness Research Andrew P. Reimer, PhD, RN, CFRN Assistant Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland Clinic Cleveland, Ohio Health Policy and Health Services Delivery, Health Services Research Barbara Resnick, PhD, CRNP, FAAN, FAANP Professor and Chairperson School of Nursing University of Maryland Baltimore, Maryland Continuing Care Retirement Communities, Self-Efficacy Brandon N. Respress, PhD, MPH, RN Clinical Assistant Professor University of Texas at Arlington Arlington, Texas Health Disparities: Focus on Racial and Ethnic Minorities Staci S. Reynolds, PhD, RN, ACNS-BC, CCRN, CNRN, SCRN Clinical Associate Duke University Hospital Durham, North Carolina Stroke Angela A. Richard, PhD, RN Assistant Professor University of Colorado Anschutz Medical Campus Brighton, Colorado Responsiveness Virginia Richardson, PhD, RN, CPNP, FAANP Associate Professor School of Nursing Indiana University Indianapolis, Indiana Pediatric Primary Care

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Anka Roberto, DNP, APRN, PMHNP-BC, MP Assistant Professor Egan School of Nursing Fairfield University Fairfield, Connecticut Mother–Infant/Toddler Relationships Beverly L. Roberts, PhD, FAAN, FGSA Annabel Davis Jenks Professor of Nursing School of Nursing University of Florida Gainesville, Florida Falls Cheryl Rodgers, PhD, CPNP, CPON Clinical Instructor Department of Pediatrics Baylor College of Medicine Pediatric Nurse Practitioner Texas Children’s Cancer Center Houston, Texas Cancer in Children Karla Rodriguez, DNP, RN, CNE Clinical Assistant Professor Rory Meyers College of Nursing New York University New York, New York Weight Management Bonnie Rogers, DrPH, COHN-S, LNCC Director NC Occupational Safety and Health Education and Research Center and OHN Program School of Public Health University of North Carolina Chapel Hill, North Carolina Nursing Occupational Injury and Stress Carol A. Romano, PhD, RN, BC, NEA, FAAN, FACMI Associate Dean for Academic Affairs and Professor Graduate School of Nursing Uniformed Services University of the Health Sciences Bethesda, Maryland Data Stewardship

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Eileen Virginia Romeo, DNP, RN Doctoral Student Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Orem's Self-Care Theory Linda Rose, PhD, RN Associate Professor School of Nursing Johns Hopkins University Baltimore, Maryland Serious Mental Illness Heather H. Ryan, MS, RN Doctoral Student College of Nursing and Health Sciences University of Massachusetts Boston, Massachusetts Cardiovascular Risk Factors Virginia K. Saba, EdD, RN, FAAN, FACMI Distinguished Scholar, Adjunct Georgetown University Washington, DC CEO and President SabaCare Inc. Arlington, Virginia Clinical Care Classification System Jonathan C. Sague, MSN, RN Doctoral Student Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Transitional Care Ali Salman, PhD, MD, DNP, RN Professor Faculty of Health Studies Brandon University Brandon, Manitoba Depression and Cardiovascular Diseases, HIV Risk Behavior Laura J. Samuel, MSN, RN, FNP School of Nursing Johns Hopkins University Baltimore, Maryland Hypertension

Elizabeth A. Schlenk, PhD, RN Assistant Professor School of Nursing University of Pittsburgh Pittsburgh, Pennsylvania Patient Contracting Karen L. Schumacher, PhD, RN Associate Professor College of Nursing University of Nebraska Omaha, Nebraska Transitions and Health Jingjing Shang PhD, RN Assistant Professor of Nursing Columbia University School of Nursing New York, New York Patient Safety Joan L. Shaver, PhD, RN, FAAN Professor and Dean College of Nursing University of Arizona Tucson, Arizona Sleep Science Caryn A. Sheehan, DNP, APRN-BC Associate Professor School of Nursing Saint Anselm College Manchester, New Hampshire Pender’s Health Promotion Model Deborah Shelton, PhD, RN, NE-BC, CCHP, FAAN Professor School of Nursing/Department of Medicine Director, Research and Evaluation–Correctional Managed Health Care University of Connecticut Storrs, Connecticut Child and Adolescent Delinquents Elaine K. Shimono, MA, RN Clinical Director Psychiatry Care Center Mount Sinai Medical Center New York, New York Rogers’s Science of Unitary Human Beings

CONTRIBUTORS

Mary Cipriano Silva, PhD, RN, FAAN Professor Emeritus College of Nursing and Health Science George Mason University Fairfax, Virginia Ethics of Research, Philosophy of Nursing Michael Simon, MSN, RN Research Assistant Professor Manager Research and Development National Database of Nursing Quality Indicators (NDNQI) School of Nursing University of Kansas Kansas City, Kansas Outcome Measures Arlene Smaldone, DNSc, CPNP, CDE Assistant Professor of Nursing Center for Health Policy School of Nursing Columbia University New York, New York Patient Safety Carol E. Smith, PhD, RN Professor School of Nursing Professor Preventive Medicine and Public Health School of Nursing University of Kansas Medical Center Kansas City, Kansas Caregiver, Home Care Technologies, Nurse-Led Group Clinic Visits, Virtual Nurse Caring Marlaine C. Smith, PhD, RN, AHN-BC, FAAN Associate Dean and Helen K. Persson Eminent Scholar Christine E. Lynn College of Nursing Florida Atlantic University Boca Raton, Florida Caring Mary Jane Smith, PhD, RN, FAAN Professor School of Nursing West Virginia University Morgantown, West Virginia Middle-Range Theories, Story Theory Ann M. Stalter, PhD, RN Assistant Professor College of Nursing and Health Wright State University Dayton, Ohio Vulnerable Populations

Theresa Standing, PhD, RN Assistant Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Triangulation Nicole D. Stark, RN Research Assistant College of Nursing Marquette University Milwaukee, Wisconsin Depression in Older Adults Deborah J. Stilgenbauer, DNP, RN, NEA-BC Director Finance, Nursing New York-Presbyterian Hospital New York, New York Stress Patricia W. Stone, PhD, RN, FAAN Professor of Nursing Director of the Center for Health Policy School of Nursing Columbia University New York, New York Patient Safety Ora Lea Strickland, PhD, RN, DSc(Hon.), FAAN Professor and Dean Florida Atlantic University Miami, Florida Measurement and Scales Neville E. Strumpf, PhD, RN, FAAN Professor Emerita School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Physical Restraints Sheri Stucke, PhD, RN Las Vegas Medical Center Las Vegas, Nevada Osteoporosis Grace Su, DNP, RN New York-Presbyterian Hospital New York, New York Data Stewardship

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Carolyn Sun, PhD, RN, ANP-BC Nurse Researcher/Nurse Scientist Columbia University School of Nursing NewYork-Presbyterian Hospital New York, New York Clinical Nursing Research Marianna K. Sunderlin, MSN, ACNS-BC Nurse Educator American Psychiatric Nurses Association Adjunct Faculty, Wright State University Dayton, Ohio Reminiscence, Self-Transcendence Hsin-Yi (Jean) Tang, PhD, PMHNP-BC, APRN Assistant Professor College of Nursing Seattle University Seattle, Washington Biofeedback Anita J. Tarzian, PhD, RN Associate Professor Family and Community Health School of Nursing University of Maryland Program Coordinator Maryland Health Care Ethics Committee Network Law and Health Care Program School of Law University of Maryland Baltimore, Maryland Descriptive Research, Nursing Assessment Ann Gill Taylor, EdD, RN, FAAN Betty Norman Norris Professor of Nursing and Director Center for the Study of Complementary and Alternative Therapies University of Virginia School of Nursing Charlottesville, Virginia Complementary Health Approaches Diana Taylor, PhD, RNP, FAAN Professor Emerita UCSF School of Nursing Director, Research and Evaluation UCSF Primary Care Initiative: Advancing New Standards in Reproductive Health Program (ANSIRH) UCSF Bixby Center for Global Reproductive Health Oakland, California Menopause

Debera Jane Thomas, DNS, RN, ANP/FNP Professor School of Nursing, Northern Arizona University Flagstaff, Arizona Case Study Method of Research Arlene R. Travis, MSN, RN, ANP-BC Adjunct Assistant Professor Lienhard School of Nursing Pace University New York, New York Falls Toni Tripp-Reimer, PhD, RN, FAAN Professor College of Nursing University of Iowa Iowa City, Iowa Ethnography, Qualitative Research Susan Tullai-McGuinness, MPA, PhD, RN Adjunct Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Health Policy and Health Services Delivery Mark P. Tyrrell, MEd, BNS, RGN, RPN, RNT Lecturer Catherine McCauley School of Nursing and Midwifery University College Cork Cork, Ireland Mild Cognitive Impairment Wendy Umberger, PhD, PMHCNS Associate Dean for Graduate Programs Kent State University College of Nursing Kent, Ohio Community Mental Health Janet H. Van Cleave, PhD, RN NRSA Postdoctoral Research Fellow Individualized Care for At-Risk Older Adults National Institute of Nursing Research Bethesda, Maryland Transitional Care

CONTRIBUTORS

Connie Vance, EdD, RN, FAAN Professor School of Nursing The College of New Rochelle New Rochelle, New York Mentoring

Deborah Vinesky, MSN, RN Doctoral Student France Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Nightingale, Florence; Patient Satisfaction

Lovelyamma Varghese, DNP, MS, FNP, RN Director of Nursing Montefiore Medical Center Professor School of Nursing SUNY Rockland West Nyack, New York Diabetes

Ladislav Volicer, MD, PhD Courtesy Full Professor School of Aging Studies University of South Florida Tampa, Florida Mental Status Measurement

Rosemary Ventura, DNP, MA, RN-BC Director of Nursing Informatics New York-Presbyterian Hospital New York, New York Nursing Information Systems and Informatics Patricia E. H. Vermeersch, PhD, RN, CNP College of Nursing Kent State University Kent, Ohio Delirium Joyce A. Verran, PhD, RN, FAAN Research Professor College of Nursing University of Arizona Tucson, Arizona Instrumentation, Reliability, Validity

Patricia Hinton Walker, PhD, RN, FAAN Vice President for Nursing Policy Professor Graduate School of Nursing University of the Health Sciences Bethesda, Maryland Neuman’s Systems Model Suzy Mascaro Walter, PhD,FNP-BC Assistant Professor Morgantown Campus West Virginia University School of Nursing Morgantown, West Virginia Adolescent Health Marilyn Wegehaupt, MSN, RN Homeless Shelter Nurse Visiting Nurses Association Omaha, Nebraska Homeless Health

Antonia M. Villarruel, PhD, RN, FAAN Professor and Margaret Bond Simon Dean of Nursing Senior Fellow, Leonard Davis Institute of Health Economics University of Pennsylvania School of Nursing Philadelphia, Pennsylvania Health Disparities: Focus on Racial and Ethnic Minorities

James Weidel, PhD, RN, FNP-BC, PMHNP Rory Meyers College of Nursing New York University New York, New York Substance Use Disorders in Professional Nurses

Anna L. D. Villena, PhD, RN, FNP, BC Assistant Professor of Clinical Nursing College of Nursing The Ohio State University Columbus, Ohio Mental Health in Public-Sector Primary Care

Mary Ellen Wewers, PhD, MPH, RN, FAAN Professor College of Public Health The Ohio State University Columbus, Ohio Smoking Cessation

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CONTRIBUTORS

Kathleen M. White, PhD, RN, NEA-BC, FAAN Associate Professor School of Nursing Johns Hopkins University Baltimore, Maryland Translational Research Sharon A. Wilkerson, PhD, RN, CNE, ANEF Dean and Professor College of Nursing Texas A&M Health Science Center Bryan, Texas Johnson’s Behavioral System Model Danny G. Willis, DNS, PMHCNS-BC Assistant Professor William F. Connell School of Nursing Boston College Chestnut Hill, Massachusetts Violence Celia E. Wills, PhD, RN Grayce M. Sills Professor in Interdisciplinary Behavioral Health Nursing Associate Professor College of Nursing The Ohio State University Columbus, Ohio Mental Health in Public-Sector Primary Care Teresa Wills, DN, MSc, BNS, RM, RGN College Lecturer School of Nursing and Midwifery Brookfield Health Sciences Complex University College Cork Cork, Ireland Obesity

Chris Winkelman, PhD, RN, CCRN, ACNP Associate Professor Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Physiology Nancy Fugate Woods, PhD, RN, FAAN Professor Emerita Biobehavioral Nursing and Dean Emeritus School of Nursing University of Washington Seattle, Washington Menopause Andrea M. Yevchak, GCNS-BC, RN Doctoral Candidate, John A. Hartford Foundation BAGNC Predoctoral Scholar School of Nursing Pennsylvania State University University Park, Pennsylvania Ageism JoAnne M. Youngblut, PhD, RN, FAAN Professor School of Nursing, Florida International University Miami, Florida Causal Modeling, Structural Equation Modeling

Holly Skodol Wilson, PhD, RN, FAAN (deseased) Grounded Theory, Research Interviews (Qualitative)

Jaclene A. Zauszniewski, PhD, RNC, FAAN Kate Hanna Harvey Professor in Community Health Nursing Frances Payne Bolton School of Nursing Case Western Reserve University Cleveland, Ohio Depression in Older Adults, Factor Analysis, Resourcefulness

Kaye Wilson-Anderson, DNSc, RN Associate Professor University of Portland School of Nursing Portland, Oregon Collaborative Research

Tamara L. Zurakowski, PhD, CRNP Practice Associate Professor of Nursing School of Nursing University of Pennsylvania Philadelphia, Pennsylvania Nightingale, Florence

List of Entries

Bobbe Ann Gray

Acculturation Emerson E. Ea

Childbirth Education

Action Science Hesook Suzie Kim

Child Lead Exposure Levels Jennifer L. Nahum

Acute Care of the Elderly Amy Berman

Terry Fulmer and

Chronic Illness Mark Lazenby, Mei Bai, and Ruth McCorkle Diane Shea Pravikoff

Addiction Care Carolyn Baird

CINAHL Database

Adherence/Compliance Jacqueline Dunbar-Jacob

Clinical Care Classification System Virginia K. Saba

Suzy Mascaro Walter

Adolescent Health Advance Directives

Noreen Nelson

Ageism Andrea M. Yevchak, Donna M. Fick, and Rose Iannino-Renz Alzheimer’s Disease

Graham J. McDougall, Jr.

Animal-Assisted Therapy Amy R. Johnson Applied Research Ivo Abraham, Sabina De Geest, and Karen MacDonald

Clinical Decision Making

Terri H. Lipman

Clinical Judgment Patricia C. Dykes and Moreen Donahue Clinical Nursing Research

Carolyn Sun

Clinical Preventive Services Cynthia Guerrero Ayres and Holly B. Bradley Clinical Trials Dorothy Brooten Cognitive Appraisal Roger Carpenter

Basic Research

Sue K. Donaldson

Behavioral Research Biofeedback

Jacqueline Dunbar-Jacob

Hsin-Yi (Jean) Tang

Boykin and Schoenhofer: Nursing as Caring Theory Theresa Bucco Breastfeeding

Suzanne Hetzel Campbell

Cancer in Children Marilyn Hockenberry and Cheryl Rodgers Cardiovascular Risk Factors and Heather H. Ryan

Laura L. Hayman

Caregiver Ubolrat Piamjariyakul and Carol E. Smith Caring Marlaine C. Smith and Sally Phillips Case Study Method of Research Jane Thomas Causal Modeling

Debera

JoAnne M. Youngblut

Cerebral Ischemia Mary E. Kerr Child and Adolescent Delinquents Deborah Shelton

Cohort Design Sarah E. Givens and Carol M. Musil Collaborative Research Kaye Wilson-Anderson and Barbara J. Braband Comfort Theory Katharine Kolcaba Community Mental Health Wendy Umberger Comparative Effectiveness Research Ivo Abraham, Sally Reel, and Karen MacDonald Complementary Health Approaches Ann Gill Taylor and Victoria Menzies Concept Analysis Kay C. Avant Conceptual Model Deborah F. Lindell and Joyce J. Fitzpatrick Content Analysis Deborah F. Lindell and Kathleen Huttlinger Continuing Care Retirement Communities Noreen Nelson and Barbara Resnick Coronary Artery Bypass Graft Surgery Susan H. McCrone Cost Analysis of Nursing Care

Mary L. Fisher

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LIST OF ENTRIES

Critical Care Nursing Carol Diane Epstein Cultural/Transcultural Focus and Karen Bauce

Data Analysis

Sharol F. Jacobson

Lauren S. Aaronson

Data-Collection Methods

Denise F. Polit

Data Management Barbara Munro Carol A. Romano and Grace Su

Data Stewardship Delirium

Patricia E. H. Vermeersch

Delphi Technique Alice S. Demi

Deborah F. Lindell and

Depression and Cardiovascular Diseases Ali Salman, Yi-Hui Lee, and Donna E. McCabe Depression in Families Terry A. Badger and Thaddeus W. W. Pace Depression in Older Adults Abir K. Bekhet, Jaclene A. Zauszniewski, and Nicole D. Stark

Experimental Research Ivo Abraham and Karen MacDonald Exploratory Studies Kathleen Huttlinger Factor Analysis Christopher J. Burant and Jaclene A. Zauszniewski Failure to Thrive (Child) Heidi V. Krowchuk and Linda L. Cook Falls

Arlene R. Travis and Beverly L. Roberts

Family Caregiving and the Seriously Mentally Ill Molly Jackson Family Health Fatigue

Suzanne Feetham

Lauren S. Aaronson

Feminist Research Methodology Sara L. Campbell Fetal Monitoring Susan M. Miovech Fever Barbara J. Holtzclaw

Depression in Women Emily J. Hauenstein

Fitzpatrick’s Life-Perspective Rhythm Model Jana L. Pressler and Kristen S. Montgomery

Descriptive Research Anita J. Tarzian and Marlene Zichi Cohen

Formal Nursing Languages Jeeyae Choi

Diabetes Melissa Spezia Faulkner and Lovelyamma Varghese

Functional Health Patterns Dorothy A. Jones and Jane Flanagan

Suzanne Bakken and

Discourse Analysis Hesook Suzie Kim Doctoral Education

Elizabeth R. Lenz

Eating Disorders Deborah B. Fahs and Barbara J. Guthrie Elder Mistreatment Terry Fulmer

Genetics Mary T. Quinn Griffin and Judith A. Lewis Global Nursing Research Azita Emami

Afaf Ibrahim Meleis and

Grandparents Raising Grandchildren J. Kelley

Susan

Lauren S. Aaronson

Electronic Network

William Scott Erdley

Grantsmanship

Emergency Nursing

Vicki Keough and Suling Li

Grounded Theory Holly Skodol Wilson, Sally A. Hutchinson, and Deborah F. Lindell

Empathy Annette Peacock-Johnson End-of-Life Planning Ethel L. Mitty and Jeff Day Enteral Tube Placement Jane F. Marek Epilepsy

Marsha L. Ellett and

Joan K. Austin

Health Care-Associated Infections Rebecca Grizzle Health Conceptualization Mary T. Quinn Griffin

Ethics of Research Mary Cipriano Silva and Tammy Lampley

Health Disparities: Focus on Racial and Ethnic Minorities Antonia M. Villarruel, Brandon N. Respress, and Lisa M. Lewis

Ethnogeriatrics Melen R. McBride and Irene D. Lewis

Health Policy and Health Services Delivery Susan Tullai-McGuinness and Andrew P. Reimer

Ethnography Toni Tripp-Reimer, Sandra Daack-Hirsch, Lister Onsongo

Health Services Research Andrew P. Reimer

Evaluation

Gail L. Ingersoll

Evidence-Based Practice Bernadette Mazurek Melnyk and Ellen Fineout-Overholt

Hemodynamic Monitoring Robin S. Krinsky and Maureen Keckeisen Henderson Model Heather Peralta Hermeneutics Pamela M. Ironside

LIST OF ENTRIES

History of Nursing Research and Sandy N. Cayo

Faye G. Abdellah

HIV Risk Behavior

Yi-Hui Lee and Ali Salman

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Mentoring Connie Vance and Karyn L. Boyar Meta-Analysis

HIV/AIDS Care and Treatment Kathleen M. Nokes

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Cheryl Tatano Beck

Middle Range Theories Patricia Liehr and Mary Jane Smith

Home Care Technologies Carol E. Smith

Mild Cognitive Impairment Mark P. Tyrrell and Geraldine McCarthy

Home Health Systems Leslie Neal-Boylan

Moral Distress Alvita Nathaniel

Homeless Health Mary J. McNamee and Marilyn Wegehaupt

Moral Reckoning Alvita Nathaniel

Hospice

Inge B. Corless

Mother–Infant/Toddler Relationships Deborah Gross, Shelly Eisbach, and Anka Roberto

Hypertension Laura J. Samuel, Cheryl R. Dennison Himmelfarb, and Martha N. Hill

Music Therapy Marion Good and Nadine Montisano-Marchi

Immigrant Women Afaf Ibrahim Meleis, DeAnne K. Hilfinger Messias, and Karen J. Aroian

Narrative Analysis

Institutional Review Board and Informed Consent Mary T. Quinn Griffin Instrumentation Joyce A. Verran and Paula M. Meek Instrument Translation Chiemi Kochinda International Classification of Nursing Practice Tae Youn Kim and Amy Coenen Interpersonal Communication Jeffrey Schwab Jones and Marjorie Thomas Lawson Job Satisfaction Peggy A. Miller and Diane K. Boyle Johnson’s Behavioral System Model Sharon A. Wilkerson Kangaroo Care (Skin-to-Skin Contact) Gene Cranston Anderson King’s Theory of Goal Attainment Alfes and Maureen A. Frey

Celeste M.

Leininger’s Theory of Culture Care Diversity and Universality Sandra C. Garmon Bibb Maternal Anxiety and Psychosocial Adaptation During Pregnancy Regina Placzek Lederman

Hesook Suzie Kim

National Institute of Nursing Research Patricia A. Grady Neuman’s Systems Model Patricia Hinton Walker

Cheryl Nadeau and

Neurobehavioral Development Barbara MedoffCooper and Diane Holditch-Davis Newman’s Theory of Health Emily J. Fox-Hill, Veronica F. Engle, and Margaret Dexheime Pharris Nightingale, Florence Tamara L. Zurakowski and Deborah Vinesky Nurse Engagement Beth Palmer and MariLou Prado-Inzerillo Nurse-Led Group Clinic Visits Ubolrat Piamjariyakul and Carol E. Smith Nurse and Physician Interdisciplinary Collaboration Tara C. Prescott Nurse Staffing Sean P. Clarke and Pamela B. Linzer Nursing Assessment Anita J. Tarzian

Marlene Zichi Cohen and

Nursing Diagnoses, Interventions, and Outcomes Sue Moorhead Nursing Education

Jeanne Marie Novotny

Measurement and Scales Ora Lea Strickland

Nursing Information Systems and Informatics Rosemary Ventura, Patricia C. Dykes, Ida Androwich, and Virginia K. Saba

Menopause Diana Taylor, Nancy Fugate Woods, and Laurie S. Jeffers

Nursing Occupational Injury and Stress Bonnie Rogers

Mental Health in Public-Sector Primary Care Celia E. Wills and Anna L. D. Villena

Nursing Practice Models Dorothy A. Jones, Marianne Ditomassi, and Jane Flanagan

Mental Status Measurement Ladislav Volicer

Ann C. Hurley and

Nursing Process Sally Phillips and Nadine Montisano-Marchi

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LIST OF ENTRIES

Nutrition in the Elderly Rose Ann DiMaria-Ghalili

Physiology Chris Winkelman

Nutrition in Infancy and Childhood Lisa Ann S. Gittner, Marguerite A. DiMarco, and Laura L. Hayman

Population Health Sandra C. Garmon Bibb

Pilot Study

Sarah E. Givens and Carol M. Musil

Postpartum Depression Linda J. Mayberry, June Andrews Horowitz, and Patricia Leahy-Warren Pregnancy Kristen S. Montgomery

Obesity Teresa Wills Observational Research Designs Janet C. Meininger Orem’s Self-Care Theory Eileen Virginia Romeo, Mary Jo Devereaux, Sherry C. Detrick, and Lora J. Morris Organizational Culture Raquel M. Meyer

Sean P. Clarke and

Organizational Design Sean P. Clarke and Pamela B. Linzer Osteoporosis Evelyn G. Duffy, Geraldine A. Britton, Sheri Stucke, Rosemary Collier, Sarah H. Gueldner, and Jane F. Marek Outcome Measures Pain

Prevention of Preterm Birth, Preterm Labor, and Low Birth Weight Judith A. Maloni Primary Nursing Marie Manthey and Catherine E. Johnson Qualitative Research Toni Tripp-Reimer, Lioness Ayres, Patricia S. Groves, and Melissa Lehan Mackin Quality of Care Quality of Life

Patti Hart O’Regan Karen M. Reeder

Quality and Safety Education for Nurses Nadine Montisano-Marchi and Mary A. Dolansky Quantitative Research Eugene Levine Quasi-Experimental Research Karen MacDonald

Michael Simon

Marion Good

Ivo Abraham and

Reliability Paula M. Meek and Joyce A. Verran

Palliative Care Marianne Matzo Parenting Diane Holditch-Davis

Reminiscence Barbara K. Haight and Marianna K. Sunderlin

Parse’s Humanbecoming School of Thought Mary T. Quinn Griffin

Replication Studies Susan A. Goncalves and Cheryl Tatano Beck

Participant Observation Kathleen Huttlinger

Research Dissemination Patricia A. Martin

Patient Care Delivery Models and Connie A. Jastremski Patient Contracting Patient Education

M. Janice Nelson

Elizabeth A. Schlenk Alyson Blanck

Patient Engagement and Patient-Centered Care Michele Crespo-Fierro Patient Safety Jingjing Shang, Patricia W. Stone, and Arlene Smaldone

Susan A. Goncalves and

Research Interviews (Qualitative) Sally A. Hutchinson, Holly Skodol Wilson, and Eileen J. Carter Research in Nursing Ethics Susan A. Goncalves

Shaké Ketefian and

Research Utilization Carol A. Ashton and Mary Anne Gallagher Resourcefulness

Jaclene A. Zauszniewski

Patient Satisfaction Cecilia D. Alvarez, Deborah Vinesky, and Sharon Boris

Responsiveness Angela A. Richard and Paula M. Meek

Pediatric Primary Care Virginia Richardson

Rogers’s Science of Unitary Human Beings John Phillips, Elaine K. Shimono, and Fidelindo Lim

Pender's Health-Promotion Model and Caryn A. Sheehan Peplau’s Theoretical Model Phenomenology Barbara Alba

Ann Fournier

Pamela G. Reed

Roy Adaptation Model Mary T. Quinn Griffin Rural Health Marianne Baernholdt

Cheryl Tatano Beck and

Philosophy of Nursing Mary Cipriano Silva, Lori A. Fusco, and Sheila M. Blank Physical Restraints Lois K. Evans, Meg Bourbonniere, and Neville E. Strumpf

Sampling Lauren S. Aaronson Schizophrenia

Molly Jackson

Secondary Data Analysis Self-Efficacy

Judith R. Graves

Jarold Johnston and Barbara Resnick

LIST OF ENTRIES

Karen M. Reeder

Self-Management Self-Transcendence

Marianna K. Sunderlin

Serious Mental Illness Linda Rose Shivering

Barbara J. Holtzclaw

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Transitional Care Janet H. Van Cleave, Mary D. Naylor, and Jonathan C. Sague Transitions and Health Afaf Ibrahim Meleis and Karen L. Schumacher

Simulation Suzanne Hetzel Campbell

Translational Research Kathleen M. White

Sleep Science Joan L. Shaver

Triangulation Susan A. Goncalves and Theresa Standing

Smoking Cessation Gretchen A. McNally and Mary Ellen Wewers SNOMED Clinical Terms Suzanne Bakken and Kenrick D. Cato Raeda Fawzi AbuAlRub

Social Support

Spirituality Martha G. Meraviglia and Carol D. Gaskamp Statistical Techniques Barbara Munro Story Theory Stress

Mary Jane Smith and Patricia Liehr

Deborah J. Stilgenbauer

Stroke Tamilyn Bakas and Staci S. Reynolds Structural Equation Modeling JoAnne M. Youngblut Substance Use Disorders in Professional Nurses Madeline A. Naegle and James Weidel Symptom Management Theory and Lisa Ericson

Arwa AL-Hamed

Systematic Review Cheryl Holly

Terminal Illness Inge B. Corless

Thermal Balance

Unlicensed Assistive Personnel Ethel L. Mitty and Karyn L. Boyar Validity Paula M. Meek and Joyce A. Verran Veterans’ Health Gina Maiocco Violence Linda Manfrin-Ledet, Danny G. Willis, Demetrius J. Porche, and Stacen Keating Virtual Nurse Caring Carol E. Smith Vulnerable Populations Ann M. Stalter Wandering Adrianne D. Linton and Donna E. McCabe Watson’s Human Caring Science Diana Lynn Morris and Kristen S. Montgomery Weight Management Sue A. Popkess-Vawter and Karla Rodriguez Wellness Joyce Johnston and Elizabeth R. Click

Telehealth Josette Jones Theoretical Framework Deborah F. Lindell

Uncertainty in Illness Deborah F. Lindell and Merle H. Mishel

Shirley M. Moore and

Barbara J. Holtzclaw

Time Series Analysis Bonnie L. Metzger

Women’s Health Ivy M. Alexander, Annette Jakubisin-Konicki, Lucinda Canty, Jenna LoGiudice, Michele McKelvey, and Brenda McNeil Workplace Violence Jane Lipscomb, Cassandra Okechukwu, and Beth Boyd

A ACCULTURATION The transformational experience of an individual when moving from a familiar culture or place of birth to a different culture, country, or region is referred to as acculturation (Berry, 2003). This process is multidimensional, individualized, dynamic, and interrelated (Berry, 2003; Schwartz, Unger, Zamboanga, & Szapocznik, 2010). Many scholars cite Berry’s (2003) conceptualization of acculturation, which he described as having several interacting phases that include an initial contact, a conflict resolution phase, and an adaptation phase. Berry (2003) further categorized adaptation to include assimilation, separation, integration, and marginalization. Assimilation refers to the adoption of the receiving country’s culture and relinquishing one’s original culture; separation indicates one retains his or her cultural heritage and rejects the host culture’s practices; integration suggests biculturalism, meaning an individual adopts some behaviors and traits of the receiving country while retaining his or her cultural heritage; and marginalization suggests rejection of both the host and heritage cultures (Berry, 2003). These categories suggest that acculturation is influenced by individual and societal factors, particularly those inherent in host countries (Berry, 2003). The global nursing shortage has been a major catalyst for the international mobility of nursing professionals. The factors that influence global nurse migration are multifactorial and are commonly described in the literature as push-and-pull factors (Kingma, 2001). Pull factors are those conditions found in receiving countries that attract migrants,

causing them to relocate, whereas push factors are those intrinsic and extrinsic conditions that drive individuals to leave their homeland (Kingma, 2001). However, international nurse migration is predominantly unidirectional, which has significantly impacted the health care delivery systems of both the host and donor countries (Ea, Griffin, L’Eplattenier, & Fitzpatrick, 2008). Economically advantaged countries, such as the United States, the United Kingdom, Australia, and some countries in the Middle East, have become magnet destinations for registered nurses coming from economically disadvantaged countries in Asia, Africa, and the Caribbean (Ea et al., 2008; Ea, Itzhaki, Ehrenfeld, & Fitzpatrick, 2010). Examples of push-and-pull factors that influence the migration of nurses include improved employment opportunities and increased professional opportunities overseas, a search for a better quality of life, an inherent personal desire to experience other cultures, and the need to seek safe working and living conditions (Kingma, 2001). There is robust literature that examines how immigrant nurses adjust to the host country’s culture. Most of these studies are conducted in host countries, such as the United States, the United Kingdom, and Australia. Similar to Berry’s conceptualization, the process of acculturation among immigrant nurses could also be characterized by several phases of adjustment that are dynamic and individualized (Ea, 2007; Magnusdottir, 2005; Xu, 2007). Findings of several nursing studies show that those who have adopted some of the host culture’s traits, behaviors, and attitudes overall have increased levels of job and life satisfaction (DiCicco-Bloom, 2004; Ea et al., 2008; Magnusdottir, 2005; Xu, 2007). This

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could have significant implications in the delivery and enhancement of safe, quality care among immigrant nurses in their host countries. The process of acculturation is also associated with periods of stress and adjustment that could profoundly impact physical and mental health states among immigrants (Lassetter & Callister, 2009; Lee, O’Neill, Ihara, & Chae, 2013; Sanou et al., 2014; Steffen, Smith, Larson, & Butler, 2006; Zemore, 2007). Chronic health conditions associated with acculturation include hypertension, obesity, depression, increased use of alcohol, and smoking (Alegría et  al., 2008; Allen, Elliott, Fuligni, Morales, Hambarsoomian, & Schuster, 2008; Choi, Rankin, Stewart, & Oka, 2008; Lassetter & Callister, 2009; Lee et al., 2013; Sanou et al., 2014; Steffen et al., 2006; Zemore, 2007). However, a major criticism of most of these studies is their reliance on the use of single-proxy measures or instruments that conceptualize acculturation as unidimensional (Schwartz et al., 2010). It is not clear if these outcomes were the result of adopting the receiving country’s cultural and societal norms or relinquishing the original culture’s practices or both (Schwartz et al., 2010). The phenomenon of global migration has profound effects on the individual, on the community, and on the host and donor countries. As globalization intensifies, there is a critical need to continue to understand this complex experience and to continue to explore the impact of acculturation on the overall physical and mental health and wellbeing of the immigrant. There is also a need to investigate the influence of acculturation among immigrant nurses on patient-related outcomes.

Emerson E. Ea Alegría, M., Canino, G., Shrout, P. E., Woo, M., Duan, N., Vila, D., . . . Meng, X. L. (2008). Prevalence of mental illness in immigrant and

non-immigrant U.S. Latino groups. American Journal of Psychiatry, 165(3), 359–369. Allen, M. L., Elliott, M. N., Fuligni, A. J., Morales, L. S., Hambarsoomian, K., & Schuster, M. A. (2008). The relationship between Spanish language use and substance use behaviors among Latino youth: A social network approach. Journal of Adolescent Health, 43(4), 372–379. Berry, J. W. (2003). Conceptual approaches to acculturation. In K. M. Chun, A. Balls Organista, & G. Marin (Eds.), Acculturation: Advances in theory, measurement, and applied research (pp.  17– 37). Washington, DC: American Psychological Association. Choi, S., Rankin, S., Stewart, A., & Oka, R. (2008). Effects of acculturation on smoking behavior in Asian Americans: A meta-analysis. Journal of Cardiovascular Nursing, 23(1), 67–73. Dicicco-Bloom, B. (2004). The racial and gendered experiences of immigrant nurses from Kerala, India. Journal of Transcultural Nursing, 15(1), 26–33. Ea, E. (2007). Facilitating acculturation of foreign-educated nurses. Online Journal of Issues in Nursing, 13(1), 5. doi:0.3912/OJIN .Vol13No01PPT03 Ea, E., Itzhaki, M., Ehrenfeld, M., & Fitzpatrick, J. (2010). Acculturation among immigrant nurses in Israel and the United States of America. International Nursing Review, 57(4), 443–448. Ea, E. E., Griffin, M. Q., L’Eplattenier, N., & Fitzpatrick, J. J. (2008). Job satisfaction and acculturation among Filipino registered nurses. Journal of Nursing Scholarship, 40(1), 46–51. Kingma, M. (2001). Nursing migration:  Global treasure hunt or disaster-in-the-making? Nursing Inquiry, 8(4), 205–212. Lassetter, J. H., & Callister, L. C. (2009). The impact of migration on the health of voluntary migrants in Western societies. Journal of Transcultural Nursing, 20(1), 93–104. Lee, S., O’Neill, A. H., Ihara, E. S., & Chae, D. H. (2013). Change in self-reported health status among immigrants in the United States: Associations with measures of acculturation. PloS One, 8(10), e76494. Magnusdottir, H. (2005). Overcoming strangeness and communication barriers:  A  phenomenological study of becoming a foreign nurse. International Nursing Review, 52(4), 263–269.

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Sanou, D., O’Reilly, E., Ngnie-Teta, I., Batal, M., Mondain, N., Andrew, C., . . . Bourgeault, I. L. (2014). Acculturation and nutritional health of immigrants in Canada: A scoping review. Journal of Immigrant and Minority Health, 16(1), 24–34. Schwartz, S. J., Unger, J. B., Zamboanga, B. L., & Szapocznik, J. (2010). Rethinking the concept of acculturation: Implications for theory and research. American Psychologist, 65(4), 237–251. Steffen, P.  R., Smith, T. B., Larson, M., & Butler, L. (2006). Acculturation to Western society as a risk factor for high blood pressure: A metaanalytic review. Psychosomatic Medicine, 68(3), 386–397. Xu, Y. (2007). Strangers in strange lands: A metasynthesis of lived experiences of immigrant Asian nurses working in Western countries. Advances in Nursing Science, 30(3), 246–265. Zemore, S.  E. (2007). Acculturation and alcohol among Latino adults in the United States:  A  comprehensive review. Alcoholism, Clinical and Experimental Research, 31(12), 1968–1990.

ACTION SCIENCE Action science is an approach for inquiry initially developed by Argyris and Schön (1974) and expanded by Argyris, Putnam, and Smith (1985), aimed at generating knowledge for and improving individual and organizational learning. Action science has been applied in the field of management, specifically for organizational learning, and in various professional practice fields, such as education, nursing, social work, and medicine, for individual learning in practice. It is an approach used to generate knowledge for practice and to transform practice by engaging practitioners in the process of inquiry through reflection on their own behavioral worlds of practice (Argyris et al., 1985; Lipshitz, Friedman, & Popper, 2007; Schön, 1983). Action science has been further developed by Torbert (1991) as an “action

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inquiry,” the terms are used interchangeably in the literature. Although action science and action research, participatory action research, in particular, are viewed by many to be in the same inquiry family within the social sciences, sharing the notion that the inquiry is oriented to change and in solving practical problems through participation of involved people, action science differs from participatory action research by focusing on the learning models that are at the base for human actions as the locus for producing changes (Argyris & Schön, 1989). In action science, changes in human actions are sought by examining and correcting the fundamental mechanisms and reasons for adhering to certain repertoires of behaviors that result from a closed-up mode of learning. A branch of action science has been advanced by Seidman (2012) as action science of social settings, which focuses on the study of social regularities and status quo with an ultimate aim to transform social settings for better social transactions. Action science presented in this section should not be confused with the “action science” that has been consolidated into a field of study referring to the study of human action from various cognitive perspectives (Prinz, Beisert, & Herwig, 2013). Putnam (1999) suggested that action science is based on three philosophical premises: (a) human practice involves meaning making, intentionality in action, and normativity from the perspective of human agency; (b) human practice goes on in an interdependent milieu of behavioral norms and institutional politics; and (c) the epistemology of practice calls for the engagement of practitioners in generating knowledge. Action science thus is a method and philosophy for improving practice and generating knowledge. Argyris (1980) further suggested that action science is an interventionist approach in which three prerequisites must be established for the research to ensue: (a) a creation of normative models of rare universes that are free of defensive routines, (b) a theory of

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intervention that can move practitioners and organizations from the present to a new desirable universe, and (c) a theory of instruction that can be used to teach new skills and create new culture. Action science holds that actions in professional practice are based on practitioners’ theories of action. Theories of action are learned and organized as repertoires of concepts, schemata, and propositions and are the basis on which behavioral worlds of practitioners are created in specific situations of practice. Argyris et al. (1985) identified espoused theories and theories in use as two types of theories of action. Espoused theories of action are the rationale expressed by practitioners as guiding their actions in a situation of practice, whereas theories in use refer to theories that are actually used in practice. Theories in use are only inferable from the actions themselves, and practitioners usually are not aware of or not able to articulate their theories in use except through careful reflection and self-dialogue. Argyris and Schön (1974) and Argyris et al. (1985) identified model 1 theories in use as a type that seals practitioners from learning and produces routinization and ineffective practice. Humans act in general to satisfy the governing variables (to be in control, to strive to win, to suppress negative feelings, and to act rationally), representing model 1 theory in use, which often result in defensiveness, misunderstanding, and self-fulfilling and self-sealing processes (Argyris, 1982; Argyris et al., 1985; Argyris & Schön, 1996). On the other hand, model 2 theory in use encompasses principles of valid information, free and informed choice in action, and internal commitment. Model 1 theory in use represents single-loop learning, whereas model 2 theory in use aligns with double-loop learning. Thus, action science aims to change people from single-loop learning of model 1 to double-loop learning of model 2 through the processes of reflection and learning, engaging both practitioners and researchers for the

transformation (Argyris, 1993, 2002; Argyris et al., 1985; Argyris & Schön, 1996). Knowledge of practitioners’ theories in use and espoused theories provides a descriptive understanding about the patterns of inconsistencies between theories in use and espoused theories recalled in actual practice. Through action science, practitioners engaged in model 2 theories in use produce practice knowledge that informs their approach to practice without routinization or the self-sealing mode. In addition, action science generates knowledge regarding the process involved in self-awareness and the learning of new theories in use through reflective practice and practice design. Research process in action science calls for the cooperative participation of practitioner and researcher through the phases of description, discovery of theories in use through reflection, and intervention. The core process in this inquiry is the cooperative offline reflection (Rudolph, Taylor, & Foldy, 2001). Action Design (1996) suggested the use of the ladder of inference as a tool to discover practitioners’ modes of thinking and action as revealed in transcripts or narratives. The key research process is the analysis of action transcripts or narratives in postpractice faceto-face discussions (interviews) between the researcher and the practitioner. Such sessions are used to get at the reconstructed reasoning of practitioners regarding critical moments of the practice and to provide opportunities for reflection on the thinking and doing that were involved in the practice. Through such sessions, the researcher also acts as an interventionist by engaging the practitioner to move toward new learning. Nursing practice is a human-to-human service that occurs in the context of health care. Nursing practice occurs within online conditions that are complex not only with respect to clients’ problems but also in terms of organizational elements of the health care environment. Nursing practice is not based simply on linear translations of relevant theoretical

ACTION SCIENCE

knowledge that governs the situation of practice, but has to be derived and designed from the nurse’s knowledge of and responses to the competing and complex demands of the situation (Kim, 2015). In addition, as the action scientists suggest, nursing practice in general as well as particular nursing actions may be entrenched with routinization or frozen within model 1 theories in use. Studies of nursing practice with the action science design have shown ways to improve mental health practice in general (Vatne, Bjorneren, & Hoem, 2009) and particular nursing strategies, such as pain assessment (Kim, Sjöström, & Schwartz-Barcott, 2006) and the use of limit-setting interventions in mental health nursing (Vatne & Fagermoen, 2007). The general aim of action science for nursing then is to improve nursing practice by freeing nurses from self-sealing practices and by engaging them in the process of learning and participatory research. An extended model of inquiry based on action science, such as critical reflective inquiry (Kim, 1999), can be applied to develop knowledge for improving nursing practice.

Hesook Suzie Kim Action Design. (1996). Organizational learning in action: New perspectives and strategies. Weston, MA: Action Design. Argyris, C. (1980). Inner contradictions of rigorous research. San Diego, CA: Academic Press. Argyris, C.  (1982). Reasoning, learning, and action: Individual and organizational. San Francisco, CA: Jossey-Bass. Argyris, C.  (1993). Knowledge for action. San Francisco, CA: Jossey-Bass. Argyris, C.  (2002). Double-loop learning. Teaching and research. Learning & Education, 1, 206–219. Argyris, C., Putnam, R., & Smith, D. M. (1985). Action science: Concepts, methods, and skills for research and intervention. San Francisco, CA: Jossey-Bass. Argyris, C., & Schön, D. A. (1974). Theory in practice. San Francisco, CA: Jossey-Bass.

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Argyris, C., & Schön, D.  A. (1989). Participatory action research and action science compared. American Behavioral Scientist, 32, 612–623. Argyris, C., & Schön, D. A. (1996). Organizational learning II: Theory, method, and practice. Reading, MA: Addision-Wesley. Kim, H. S. (1999). Critical reflective inquiry for knowledge development in nursing practice. Journal of Advanced Nursing, 29(5), 1205–1212. Kim, H.  S. (2015). The essence of nursing practice:  Philosophy and perspective. New  York, NY: Springer Publishing. Kim, H. S., Sjöström, B., & Schwartz-Barcott, D. (2006). Pain assessment in the perspective of action science. Research and Theory for Nursing Practice, 20(3), 215–228. Lipshitz, R., Friedman, V. J., & Popper, M. (2007). Demystifying organizational learning. Thousand Oaks, CA: Sage. Prinz, W., Beisert, M., & Herwig, A. (Eds.). (2013). Action science:  Foundations of an emerging discipline. Boston, MA: MIT Press. Putnam, R.  (1999). Transforming social practice: An action science perspective. Management Learning, 30, 177–187. Rudolph, J. W., Taylor, S. S., & Foldy, E. G. (2001). Collaborative off-line reflection:  A  way to develop skill in action science and action inquiry. In P.  Reason & H.  Bradbury (Eds.), Handbook of action research: Participative inquiry and practice (pp. 405–412). London, UK: Sage. Schön, D. A. (1983). Reflective practitioner: How professionals think in action. New  York, NY:  Basic Books. Seidman, E. (2012). An emerging action science of social settings. American Journal of Community Psychology, 50(1–2), 1–16. Torbert, W.  R. (1991). The power of balance: Transforming self, society, and scientific inquiry. Newbury Park, CA: Sage. Vatne, S., Bjornerem, H., & Hoem, E. (2009). Development of professional knowledge in action:  Experiences from an action science design focusing on acknowledging communication in mental health. Scandinavian Journal of Caring Sciences, 23(1), 84–92. Vatne, S., & Fagermoen, M. S. (2007). To correct and to acknowledge:  Two simultaneous and conflicting perspectives of limit-setting in mental health nursing. Journal of Psychiatric and Mental Health Nursing, 14(1), 41–48.

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ACUTE CARE OF THE ELDERLY

ACUTE CARE OF THE ELDERLY Older people have a greater prevalence of chronic diseases and disorders that lead to hospitalization. On average, people older than 65 are hospitalized more than three times as often as younger individuals, and the length of their stay is estimated to be 50% longer than that of younger individuals. Nursing research that defines the evidence for practice interventions is needed for patients of all ages, and especially for the elderly (Boltz, Capezuti, Fulmer, & Zwicker, 2016). Nursing research that provides the basis for best practice for hospitalized elders is often embedded in interdisciplinary studies. Several studies have recently documented the essential nature of continuity of care across settings for optimal acute care outcomes (Boyd et al., 2010; Counsell, Callahan, Tu, Stump, & Arling, 2009). Increasingly, critical care of older adults has received attention, given the demographic shifts nationally and the advancing age of those in intensive care units, emergency rooms, and other critical care areas (Foreman, Fulmer, & Milisen, 2010). Acute care of the elderly (ACE) units, which developed in the early 1990s, have shown improved outcomes among older patients who have been hospitalized. These units focus on precise and ongoing assessment of older adults, especially related to functional capacity and decline and follow the evidence to create individualized care plans (Malone et al., 2010). A classic study conducted by Landefeld, Palmer, Kresevic, Fortinsky, and Kowal (1995) demonstrated that patients admitted to an ACE unit were more likely to improve in activities of daily living and were less likely to be institutionalized. The three core components of the framework for care on ACE units are interdisciplinary teaming, enhancements in the physical design focused on safety and function of older adults, and attention to common geriatric syndromes, such as sleep problems, incontinence, and

falls identified in the Fulmer SPICES assessment (Fulmer, 2007; Siegler, Glick, & Lee, 2002). (SPICES is an acronym for the common syndromes of the elderly requiring nursing intervention: S is for sleep disorders, P is for problems with eating or feeding, I is for incontinence, C is for confusion, E is for evidence of falls, and S is for skin breakdown.) In a prospective study of 804 patients who were 80 years of age or older, 42% of the elderly patients with no baseline dependencies at the time of admission had developed one or more limitations within 2 months (Hart, Birkas, Lachmann, & Saunders, 2002). Individuals who are older than 65 are more likely to be admitted to acute care from the emergency department than other age groups. The hospitalized elderly are at an increased risk for poor outcomes, such as increased length of stay, readmissions, functional decline, and iatrogenic complications, as compared with other age groups. Fifty-eight percent of patients who are hospitalized will experience at least one iatrogenic complication (Sourdet et al., 2015) There is a significant and serious readmission rate for older adults, ranging from 18% to 33% within 1 to 3 months and with complications, such as acute confusion and nosocomial infections, which are common among the elderly, resulting in increased morbidity and mortality (Lindenauer et al., 2010). The cost of avoidable hospital admissions for older adults in the United States is serious and expensive. Among the almost 2.3 million hospitalizations for older adults in 2009, more than 600,000 (or 26%) were considered potentially avoidable, with an average cost of $8,783. The overall Medicare and Medicaid costs for these potentially avoidable hospitalizations were $5.4 billion (Segal, Rollins, Hodges, & Roozeboom, 2014). The composition of hospital staff has been shown to make a difference in patient outcomes (Cho et al., 2015). Nurse accountability and models of patients and nursing administration also have been examined (Baggs, 2007; Piquette, Reeves, & Leblanc, 2009; StallingsWelden & Shirey, 2015). These studies provide

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some information regarding outcomes for the elderly, but intensive effort needs to be focused on understanding the differences between outcomes for younger individuals versus older individuals in the case of hospital care. For example, do older adults have different cardiac output after coronary artery bypass surgery than younger individuals when other variables are held constant, such as premorbid conditions? Such parameters are needed for the improvement of care for the elderly. The Cochrane Collaboration published a review on interprofessional education that examined the effects on professional practice and health care outcomes and reported that data from six studies produced positive outcomes in satisfaction, collaboration, reduction of clinical error, and management of care for selected patient groups (Zwarenstein, Goldman, & Reeves, 2009). Although not specific to geriatrics only, the data are promising for improving care for hospitalized elderly given that the majority of patients in hospitals are older adults. Historically, older adults were not considered to be “suitable candidates” for surgeries and treatments that today are considered routine. In the early 1970s, individuals older than 65 were excluded from surgical intensive care units, as it was felt that the cost-benefit was not going to be in favor of the older patient. Today, individuals in their 80s and 90s undergo open heart surgery and require appropriate postoperative care that only a surgical intensive care unit can provide (Silverstein, 2010). Furthermore, creative strategies for predicting postoperative cognitive dysfunction are being employed (Deiner, Luo, Silverstein, & Sano, 2015). The ACE unit model continues to evolve. Recent innovations include health systems, such as Summa in Akron, Ohio, which implemented an ACE Hearth Failure Unit, an ACE Pulmonary Unit, and an ACE Stroke and Neuroscience Unit. The Summa ACE adaptation uses a geriatric advanced practice nurse and a primary nurse in its design. Increasingly, hospitals are looking to make the entire facility a “virtual” ACE unit. At

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Mount Sinai Hospital in New York City, a mobile ACE unit (or MACE) was established to bring interdisciplinary geriatric expertise to the bedside of high-risk older adults across the hospital (Hung, Ross, Farber, & Siu, 2013). Aurora Health in Wisconsin developed ACE Tracker (Vollbrecht et al., 2015) software, which extracts key data from the electronic medical record to identify older adults at risk for functional decline and poor outcomes. Those identified at risk are followed by a specially trained interdisciplinary team. Ethical issues abound regarding elders during a hospitalization. For example, if there is an insufficient number of beds in an intensive care unit, should older individuals be sent out to the floor before younger individuals? Are scarce resources allocated to younger individuals before they are used to care for the elderly? Furthermore, elder abuse, a serious and potentially fatal syndrome, is frequently overlooked when elders come into the hospital with severe symptoms, such as bilateral bruising, histories incompatible with injuries, and overt fear of caregivers. These issues are a part of ACE and need to be addressed with rigorous research studies. Studies involving younger individuals need to be replicated among older adults to discern differences among the age cohorts. As hospitals offer a wider array of invasive tests and burdensome treatment modalities, ACE units offer an optimal environment to study the effects of a focus on goals of care. What is the care people and families want, and, if provided, does this lead to better quality of life and value for the health care system? We are just beginning to understand the potential of engaging with our most vulnerable elders in defining what care should look like (Berman, 2012).

Terry Fulmer Amy Berman Baggs, J. G. (2007). Nurse-physician collaboration in intensive care units. Critical Care Medicine, 35(2), 641–642.

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Berman, A. (2012). Living life in my own way— And dying that way as well. Health Affairs, 31(4), 871–874. Boltz, M., Capezuti, E., Fulmer, T.  T., & Zwicker, D.  (2016). Evidence-based geriatric nursing protocols for best practice. New York, NY: Springer Publishing. Boyd, C. M., Reider, L., Frey, K., Scharfstein, D., Leff, B., Wolff, J., . . . Boult, C. (2010). The effects of guided care on the perceived quality of health care for multi-morbid older persons: 18-month outcomes from a cluster-randomized controlled trial. Journal of General Internal Medicine, 25(3), 235–242. Cho, E., Sloane, D. M., Kim, E. Y., Kim, S., Choi, M., Yoo, I. Y., . . . Aiken, L. H. (2015). Effects of nurse staffing, work environments, and education on patient mortality:  An observational study. International Journal of Nursing Studies, 52(2), 535–542. Counsell, S. R., Callahan, C. M., Tu, W., Stump, T. E., & Arling, G. W. (2009). Cost analysis of the geriatric resources for assessment and care of elders care management intervention. Journal of the American Geriatrics Society, 57(8), 1420–1426. Deiner, S., Luo, X., Silverstein, J. H., & Sano, M. (2015). Can intraoperative processed EEG predict postoperative cognitive dysfunction in the elderly? Clinical Therapeutics, 37(12), 2700–2705. doi:10.1016/j.clinthera.2015.11.004 Foreman, M. D., Milisen, K., & Fulmer, T. T. (2010). Critical care nursing of older adults: Best practices (3rd ed.). New York, NY: Springer Publishing. Fulmer, T. (2007). How to try this: Fulmer SPICES. American Journal of Nursing, 107(10), 40–48; quiz 48. Hart, B. D., Birkas, J., Lachmann, M., & Saunders, L. (2002). Promoting positive outcomes for elderly persons in the hospital:  Prevention and risk factor modification. AACN Clinical Issues, 13(1), 22–33. Hung, W. W., Ross, J. S., Farber, J., & Siu, A. L. (2013). Evaluation of the Mobile Acute Care of the Elderly (MACE) service. JAMA Internal Medicine, 173(11), 990–996. Landefeld, C. S., Palmer, R. M., Kresevic, D. M., Fortinsky, R. H., & Kowal, J. (1995). A randomized trial of care in a hospital medical unit especially designed to improve the functional outcomes of acutely ill older patients. New England Journal of Medicine, 332(20), 1338–1344.

Lindenauer, P. K., Bernheim, S. M., Grady, J. N., Lin, Z., Wang, Y., Wang, Y., . . . Krumholz, H. M. (2010). The performance of US hospitals as reflected in risk-standardized 30-day mortality and readmission rates for medicare beneficiaries with pneumonia. Journal of Hospital Medicine, 5(6), E12–E18. Malone, M. L., Vollbrecht, M., Stephenson, J., Burke, L., Pagel, P., & Goodwin, J. S. (2010). Acute care for elders (ACE) tracker and e-Geriatrician: Methods to disseminate ACE concepts to hospitals with no geriatricians on staff. Journal of the American Geriatrics Society, 58(1), 161–167. Piquette, D., Reeves, S., & Leblanc, V. R. (2009). Interprofessional intensive care unit team interactions and medical crises: A qualitative study. Journal of Interprofessional Care, 23(3), 273–285. Segal, M., Rollins, E., Hodges, K., & Roozeboom, M. (2014). Medicare–Medicaid eligible beneficiaries and potentially avoidable hospitalizations. Medicare & Medicaid Research Review, 4(1), E1–E10. Siegler, E. L., Glick, D., & Lee, J. (2002). Optimal staffing for acute care of the elderly (ACE) units. Geriatric Nursing, 23(3), 152–155. Silverstein, J. H. (2010). Perioperative care of the elderly. In M. D. Foreman, K. Milisen, & T. T. Fulmer (Eds.), Critical care nursing of older adults (3rd ed., pp. 531–552). New York, NY: Springer Publishing. Sourdet, S., Lafont, C., Rolland, Y., Nourhashemi, F., Andrieu, S., & Vellas, B. (2015). Preventable iatrogenic disability in elderly patients during hospitalization. Journal of the American Medical Directors Association, 16(8), 674–681. Stallings-Welden, L. M., & Shirey, M. R. (2015). Predictability of a professional practice model to affect nurse and patient outcomes. Nursing Administration Quarterly, 39(3), 199–210. Vollbrecht, M., Malsch, A., Hook, M. L., Simpson, M. R., Khan, A., & Malone, M. L. (2015). Acute care for elders (ACE) tracker and e-geriatrician telemedicine programs geriatrics models of care. In M. L. Malone, E. A. Capezuti, & R. M. Palmer (Eds.), Geriatric models of care (pp. 51– 56). New York, NY: Springer Publishing. Zwarenstein, M., Goldman, J., & Reeves, S. (2009). Interprofessional collaboration: Effects of practice-based interventions on professional practice and healthcare outcomes. Cochrane Database of Systematic Reviews, 3(3), CD000072. doi:10.1002/14651858.CD000072.pub2

ADDICTION CARE

ADDICTION CARE According to the American Society of Addiction Medicine, addiction is usually defined as a “primary, chronic disease of brain reward, motivation, memory and related circuitry” (www.asam.org/quality -practice/definition-of-addiction). It is characterized by the compulsive nature of the use of mood-altering substances and behaviors. Over time, the structure and the function of the brain are changed (American Psychiatric Association [APA], 2000; Angres & BettinadiAngres, 2008; Kleber et al., 2006; National Institute on Drug Abuse [NIDA], 2010). The individual may begin to display physical, cognitive, and behavioral symptoms. The course of the disease is marked by periods of use and abstinence with symptoms of withdrawal and the development of tolerance. Frequently, physical and/or additional psychological disorders are also present. Historically, the terms “substance abuse” and “substance dependence” have been used and the resulting disorders were classified as psychological disorders. Current usage follows the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; APA, 2013) and refers to these disorders as substancerelated and addictive disorders and further defines them as mild, moderate, or severe depending on the level of severity of symptomatology and number of diagnostic criteria met. Since 2015, these disorders have been coded using the World Health Organization (WHO) International Classification of Diseases (10th edition; ICD-10; WHO, 1992) system of coding for mental and behavioral disorders due to psychoactive substance use. Severity is identified using the levels of harmful use or dependence syndrome (www .who.int/ substance_ abuse/ terminology/ ICD10ClinicalDiagnosis.pdf). Treatment has been typically provided in a substance use or psychiatric setting, but individuals experience a variety of symptoms

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and enter care through many different portals. Nurses are usually the direct care provider at all points of entry. This would suggest that all nurses should have at least a basic understanding of the disease of addiction. Even so, nursing has seen addiction care as a specialty on its own or under mental health. There are professional nursing organizations dedicated to the specialties of addictions and psychiatric nursing. The International Nurses Society on Addictions (IntNSA) was established in 1975. Addictions nursing certifications were offered through the Addictions Nursing Certification Board at the generalist level (certified addictions registered nurse) starting in 1989 and at the advanced practice level (certified addictions registered nurse—advanced practice) in 2000. In the past few years, other nursing specialty organizations, for example, the Association of Nurses in AIDS Care and the American Society of Pain Management Nurses have been adding a focus on substance abuse disorders because of the comorbidity of their disorder with addiction. Other specialty nursing organizations focus on addiction because of the risk for substance-related disorders that their members experience. In 1998, as a result of statistics supporting that all health care provider groups have a 10% prevalence for substance-related disorders and that 6% to 8% of the providers may use to the extent that their practice is negatively affected, the American Association of Colleges of Nursing introduced a position statement that outlined the importance of including substance abuse education in all curricula in all schools of nursing. More recently, a survey of 302 nurses revealed that 48% of those responding reported that they use drugs or alcohol at work. Forty percent were concerned that their competency level might be affected and 27% acknowledged that their substance use had put their patients at risk one or more times. Drugs had been diverted from their workplace by 25% of those surveyed (Cares, Pace, Denious, & Crane, 2015).

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State Boards of Nursing sanction approximately one third of 1% of actively working nurses each year because of substance abuse or dependency (National Council of State Boards of Nursing, 2011). Professional organizations, such as the IntNSA, the American Nurses Association (ANA), and the American Association of Nurse Anesthetists (AANA), have become active in advocating for proactive policies and providing education on substance abuse, risk factors, and workplace stressors. A greater focus is being put on recovery than on sanctions through programs that offer an alternative to discipline. In the early 1930s, alcoholism was explained by attributing it to an allergy (Angres & Bettinadi-Angres, 2008). One of the best-known figures in the study of addiction, Bill Wilson, was inspired to start Alcoholics Anonymous after experiencing treatment under that theory. Hospitals in Minnesota attempted to partner with Alcoholics Anonymous, giving rise to an altered concept of substance abuse called the Minnesota model. This was the beginning of a disease concept for addiction. Twenty years later, E. Morton Jellinek would conduct research with male alcoholics and develop the Jellinek Curve (Niedermayer, 2012), which became the basis for his disease concept of alcoholism. Then, as now, diagnosis of this disease depends on the evaluation of presenting signs and symptoms reported by the affected individual, which are then fitted into a defined set of elements or criteria (APA, 2013; Doweiko, 2006). Although a great deal of stigma persists due to the myth that substance-related disorders originate from poor choices, acceptance of the disease model has allowed health care professionals to work from a theory of addiction that can be accepted regardless of the specialty area or expertise of the practitioners. This work is difficult and definitions and terminology can vary from area to area. The Center for Substance Abuse Treatment, a part of the Substance Abuse Mental Health Services Administration, the NIDA, and the

National Institute on Alcohol Abuse and Alcoholism are the main resources for funding of research and information about substance abuse and dependence. Additional resources can be obtained from the Centers for Disease Control and Prevention (CDC) and the American Society of Addiction Medicine (ASAM). Many educational documents have been made available through publications available on their websites. One of these documents, the 2014 National Survey on Drug Use and Health (NSDUH) for Americans 12 years and older, estimated that 27 million Americans, or one in 10, used an illicit drug in the past 30 days. This is higher for 2014 than in any year since 2002. This is attributed to the use of marijuana and the nonmedical use of prescription pain relievers. Although nonmedical use of prescription pain relievers continues to be the second most common form of illicit use among all age categories, it is being replaced by heroin. Alcohol use is very similar to use in 2009 to 2013 (139 million) and, although tobacco use has been declining from 2002 to 2013 (66.9 million), adolescent use of electronic nicotine delivery systems (ENDS) has increased threefold from 2013 to 2014 (Bunnell et al., 2015). The 2014 NSDUH used the DSM-IV (APA, 1994), and assessed that approximately 21.5 million people aged 12 years or older met criteria for a substance use disorder, 17.0 million with an alcohol use disorder, and 7.1 million with an illicit drug use disorder. Of these, around 2.6 million people aged 12 years or older met criteria for both an alcohol use disorder and an illicit drug use disorder (Center for Behavioral Health Statistics and Quality, 2015). The abuse of tobacco, alcohol, and illicit drugs costs this country more than $700 billion annually due to lost productivity, crime, and associated health care. From 2001 to 2014, the numbers of national overdose deaths have been climbing and are currently considered an epidemic with 78 deaths a day (CDC, 2016). Prescription drugs accounted for 25,760 overdoses, a 2.8-fold increase, with prescription

ADDICTION CARE

opioid pain relievers responsible for 18,893 of these deaths or a 3.4-fold increase. Seven thousand, nine hundred and forty-five deaths were attributed to benzodiazepines, a fivefold increase. Cocaine was identified in 5,415 overdose deaths, for a 42% increase. And heroin was the primary drug used in overdoses; it resulted in 10,574 deaths, a sixfold increase (NIDA, 2016). At the same time, ENDS, once thought to be a tool in reducing the use of smoked tobacco, are beginning to cause concern. From 2011 to 2014, the use of ENDS increased ninefold from 1.5% to 13.4%, or one in seven high school students. More than a quarter of a million adolescents were introduced to nicotine for the first time in an e-cigarette (CDC, 2015a, as cited in CDC, 2015b); most users of ENDS also smoked tobacco as cigarettes, becoming dual users; and health concerns, such as lung damage and cancer, have been identified from the humectants used in ENDS products (CDC, 2015b). Every segment of the population is equally susceptible to the disease of addiction. Adolescence seems to be the period when use is the highest; but concern is growivng about substance abuse in the 76 million members of the baby boomer generation as age-adjusted rates for opioid overdose deaths increase in that age group (Rudd, Aleshire, Zibbell, & Gladden, 2016). Educational programming has been directed toward prevention and intervention. More effort needs to be directed toward educating the community and health care providers about recognizing the signs and symptoms of use and abuse. Efforts must continue to be made to integrate systems of service, that is, mental health, substance abuse, and primary care. Consideration is being given to understanding the dynamics of substance-related disorders and the impact they have on different populations and in the development of treatment approaches and guidelines specific to those population issues. The goals of nursing and addiction care research are closely aligned because they

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are based on clinically relevant research and clinical expertise guided by the unique preferences of the patient (Institute of Medicine [IOM], 2001; McCarty, 2010). According to the National Quality Forum (2007), research to this point has focused on four general areas: identifying substance use conditions, approaches for initiating and engaging participation, therapeutic interventions, and coordination of care. Some of the changes are integrated screening; protocols for addressing positive screens, brief interventions, and referrals; treatments and pharmacotherapy based on empirical data; and established performance and outcomes measurements (Baird & Fornili, 2008; McCarty, 2010). Federal projects are addressing integrated treatment for comorbid mental health and substance abuse disorders; screening, brief intervention, and referral to treatment for primary care providers; clinical nursing guidelines for the use of Suboxone; clinical guidelines for opioid addiction treatment; and issues with addiction and criminal justice. Nurses practicing in the specialty areas of addiction and mental health can participate in, conduct, or collect data for a variety of research improving quality of addiction care and increasing knowledge about the disease.

Carolyn Baird American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: American Psychiatric Publishing. Angres, D. H., & Bettinadi-Angres, K. (2008, October). The disease of addiction:  Origins, treatment and recovery. Disease a Month, 54(10), 696–721. Retrieved from http://www.diseaseamonth .com/article/S0011-5029(08)00092-8/abstract Baird, C., & Fornili, K.  (2008). Effective health care delivery and integrated behavioral health

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screening. Journal of Addictions Nursing, 19(3), 174–177. Bunnell, R. E., Agaku, I. T., Arrazola, R. A., Apelberg, B. J., Caraballo, R. S., Corey, C. G., . . . King, B. A. (2015). Intentions to smoke cigarettes among never-smoking US middle and high school electronic cigarette users: National Youth Tobacco Survey, 2011-2013. Nicotine & Tobacco Research, 17(2), 228–235. Cares, A., Pace, E., Denious, J., & Crane, L. A. (2015). Substance use and mental illness among nurses: Workplace warning signs and barriers to seeking assistance. Substance Abuse, 36(1), 1–4. doi:10.1080/08897077.2014.933725 Center for Behavioral Health Statistics and Quality. (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15–4927, NSDUH Series H-50). Retrieved from http://www .samhsa.gov/data Centers for Disease Control and Prevention. (2015a). Tobacco use among middle and high school students—United States, 2011–2014. Morbidity and Mortality Weekly Report, 64(14), 381–385. Retrieved from http://www.cdc.gov/ mmwr/preview/mmwrhtml/mm6414a3.htm Centers for Disease Control and Prevention, Office on Smoking and Health. (2015b, July). Electronic nicotine delivery systems: Key facts. Retrieved from http://www.cdc.gov/tobacco/ stateandcommunity/pdfs/ends-key-facts.pdf Centers for Disease Control and Prevention. (2016). Injury prevention and control: Opioid overdose. Retrieved from http://www.cdc .gov/drugoverdose/epidemic/index.html Doweiko, H. E. (2006). Concepts of chemical dependency. Pacific Grove, CA: Thomson Brooks/Cole. Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academies Press. Kleber, H. D., Weiss, R. D., Anton, R. F., George, T. P., Greenfield, S. F., Kosten, T. R., . . . Reigier, D. (2006, August). Practice guideline for the treatment of patients with substance use disorders (2nd ed.). Washington, DC: American Psychiatric

Association Steering Committee on Practice Guidelines. Retrieved from http://www .psychiatryonline.com/ pracGuide/prac GuideTopic_5.aspx McCarty, D. (2010). Response 4: The realities of evidence-based practices for addiction treatment. The Bridge: Science to Service, 1(2), 13. Retrieved from http://www.nattc.org/find/ news/attcnews/epubs/v1i2_article04.asp National Council of State Boards of Nursing. (2011). Substance use disorder in nursing: A resource manual and guidelines for alternative and disciplinary monitoring programs. Chicago, IL: Author. National Institute on Drug Abuse. (2010, August). Drugs, brains and behavior: The science of addiction. Retrieved from http://www .drugabuse.gov/ scienceofaddiction/ sciofaddiction.pf National Institute on Drug Abuse. (2016). Trends & statistics. Retrieved from https://www.drugabuse .gov/related-topics/trends-statistics National Quality Forum. (2007). National voluntary consensus standards for the treatment of substance use conditions:  Evidence-based treatment practices. A  consensus report. Retrieved from http://www.qualityforum .org/Search.aspx?keyword=substance+abuse+ treatment+consensus+document Niedermayer, D. (2012). Revisiting the disease model of alcoholism. Retrieved from http://www .addictioninfo.org/articles/3101/1/Revisiting -the-Disease-Model-of-Alcoholism/Page1.html Pincus, H. A., Page, A. E. K., Druss, B., Appelbaum, P.  S., Gottlieb, G., & England, M.  J. (2007, May). Can psychiatry cross the quality chasm? Improving the quality of health care for mental health and substance use conditions. American Journal of Psychiatry, 164, 712–719. Retrieved from http://ajp.psychiatryonline.org/cgi/ content/full/164/5/712 Rudd, R. A., Aleshire, N., Zibbell, J. E., & Gladden, R. M. (2016). Increases in drug and opioid overdose deaths—United States, 2000–2014. Morbidity and Mortality Weekly Report, 64 (50–51), 1378–1382.

ADHERENCE/COMPLIANCE

ADHERENCE/COMPLIANCE Adherence is defined as the degree to which behavior corresponds to a recommended therapeutic regimen. Numerous terms have been used to describe this behavior, including compliance, therapeutic alliance, and patient cooperation. Although the literature is filled with discussion of the acceptability of these terms and the differences among them, most investigators view the terms as synonymous and independent of the decision to engage in a particular therapeutic regimen. The most complete literature can be obtained from a structured database with the term patient compliance. Adherence to health care regimens has been discussed in the literature since the days of Plato. However, little systematic attention was given to this phenomenon until the 1970s, when there was a proliferation of research. One of the first reviews of the literature was published in Nursing Research in 1970, by Marston. Since that time, there has been a profusion of research from a variety of disciplines. The majority of the research has been focused on patient adherence, although there is a smaller body of literature on the adherence of research staff to clinical protocols and a growing body of literature on provider adherence to treatment guidelines. Studies on adherence have focused primarily at the stage of maintaining a prescribed and adopted treatment regimen. Adherence, however, is important from the time of regimen advice to the acquisition of the medication, food, exercise equipment, and so forth, required to carry out that advice to the initiation of care, to the design and accurate management of the regimen, to the contribution over the short and long term. These preceding stages have not been well studied. One of the issues that continues to arise in discussions of patient adherence is patient autonomy. Is nonadherence a patient right or is adherence a patient responsibility? This argument presumes that the patient is aware

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of his or her own behavior and has consciously decided not to follow a treatment regimen. The literature suggests that fewer than 20% of patients with medication regimens consciously decide not to engage in a treatment program. Those patients who have decided to follow the regimen but do not carry it out are unaware of episodic lapses in behavior or have difficulty in integration of the health care regimen into their lives. The most common reasons given by patients for lapses in adherence are forgetting and being too busy. This group comprises on an average 40% to 50% or more of patients in a treatment regimen. The problem of nonadherence is costly in terms of dollars and lives. The National Pharmaceutical Council estimates that nonadherence to pharmacological therapies costs $100 to $300 billion annually. Although the cost of nonadherence to nonpharmacological therapies has not been estimated, the contribution to morbidity and mortality is high. Failures to quit smoking, to lose and maintain weight, to exercise regularly, to engage in safe sex practices, to avoid excess alcohol, and to use seat belts contribute significantly to declines in functional ability as well as to early mortality. Further data suggest that nonadherence to pharmacological as well as nonpharmacological therapies contributes to excess hospitalization and complication rates. Poor adherence then is a significant problem of direct relevance to nursing. Nurse practitioners may prescribe or recommend therapies. Home health and community nurses provide education and assistance in carrying out health care advice. Hospital, clinic, and office nurses provide education regarding treatment plans. There is a need for intervention studies that guide practice as nurses prepare and support patients in the conduct of treatment regimens. Research on adherence has been focused heavily on the determination of the extent of the problem and on predictors or contributing factors. The 2010 report on medication adherence by the Cochrane Collaboration suggested that just 70 randomized controlled

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studies have evaluated interventions to improve medication adherence and examine both adherence and clinical indicators as outcomes, out of which 36 reported improvement in adherence, and 25 in outcome. Most of these used general educational or behavioral counseling interventions. Improving convenience, system-wide interventions have shown modest improvements with the use of case managers. Fewer studies have examined adherence to lifestyle behaviors One problem in evaluating the interventions and identifying the relevant predictors is that of measurement. Most clinical studies have relied on self-report of adherence. There is a growing body of evidence indicating that individuals do not report accurately and those reports are biased toward an overestimate of performance. Thus, alternative strategies are being used to obtain better information, such as electronic monitors, personal digital assistants (PDAs), and other technologies. Future research on adherence should address strategies by which nurses can improve adherence to treatment regimens with attention directed toward various age groups, clinical populations, and regimen behaviors across the range from decision to adopt to longterm maintenance. The research would benefit from theoretical approaches to the problem of patient adherence and the design of intervention strategies. Effective strategies delivered by nurses have considerable promise of a favorable impact on health outcomes and costs.

Jacqueline Dunbar-Jacob

ADOLESCENT HEALTH Adolescence occurs between the ages of 11 and 20 years and consists of three distinct phases: early adolescence (ages 11–14 years), middle adolescence (ages 15–17 years), and late adolescence (ages 18–20 years; Kollar, 2013). It is marked by the gradual appearance

of secondary sex characteristics (11–12 years of age) and ends with the cessation of body growth (18–20 years of age; Kollar, 2013). However, categorizing adolescence simply as a period of sexual maturation simplifies a stage of life that involves physical, cognitive, emotional, and social maturation, which are all critical for later life health and wellness (Kleinert & Horton, 2016; Kollar, 2013; Patton et al., 2016). Adolescent health typically refers to a healthy period of life in which the major causes of morbidity and mortality are associated with risky health behaviors rather than diseases (Kollar, 2013). There are six categories of health behaviors among adolescents that are of priority: (a) behaviors contributing to unintentional injury and violence, (b) tobacco use, (c) alcohol and other drug use, (d) sexual behaviors, (e) unhealthy dietary behaviors, and (f) physical inactivity (Kann et al., 2016). Behaviors that contribute to unintentional injuries in adolescents include: not wearing a bicycle helmet, not using a seatbelt, riding with a driver who has been drinking alcohol, driving a car after drinking alcohol, and texting/e-mailing while driving (Kann et al., 2016). Bicycling is one of the most common causes of sport injuries in adolescents, and a significant risk factor for severe injury is not wearing a helmet (Hagel, Romanow, Enns, Williamson, & Rowe, 2015). Reported barriers to helmet use include the following: (a) lack of access to a helmet, (b) poor fit of helmets, and (c) lack of knowledge regarding helmet use (Pierce, Palombaro, & Black, 2014). Education programs that teach adolescents the importance of helmets in preventing injuries as well as the importance of proper fit can be implemented in communities, schools, and outpatient practice settings (Elwell, Kulp, & McCue, 2014; Hooshmand, Hotz, Neilson, & Chandler, 2014). Adolescents with a history of motor vehicle crash (MVC)-related injuries have higher rates of risk-taking behaviors, which include riding with a friend who uses using

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substances, alcohol-related injuries, and not wearing a seatbelt (Jelalian, Alday, Spirito, Rasile, & Nobile, 2000). Seatbelt use is associated with a significantly lower mortality than unrestrained victims and MVC victims wearing seat belts have shorter hospital stays, decreased lengths of stay in the intensive care unit, and significant reductions in injury severity in all body areas (Nash et al., 2016). Health care providers need to discuss the leading causes of teen crashes: inexperience, driving with teen passengers, nighttime driving, not using seatbelts, distracted driving, drowsy driving, reckless driving, and impaired driving (Centers for Disease Control and Prevention [CDC], 2015). Graduated driver licensing programs are a proven method to help teens become safer drivers (Zhu, Zhao, Long, & Curry, 2016). Youth violence (ages 15–24 years) is the third leading cause of death in young people in the United States (CDC, 2016b). Behaviors that contribute to violence include carrying a weapon, physical fights, dating violence, suicidal behavior, and bullying (Kann et al., 2016). Many youth involved in these behaviors require medical care for nonfatal injuries, including cuts, bruises, broken bones, and gunshot wounds (CDC, 2016b). Health care providers can start counseling at an early age and possibly “interrupt the trajectory” of risky behaviors that lead to violence (Riese, Gao, Baird, Mello, & Ranney, 2017). During 2016, 8.6% of students (grades 9–12) in the United States attempted suicide in the previous 12 months (Kann et al., 2016). Mental health problems arise in childhood and, given that suicide is the second leading cause of death for children (15–19 years old), providers caring for adolescents must be comfortable screening patients for suicide; mood disorders; and substance abuse and dependence (Shain, 2007). Adolescence is a time that sets the stage for later life use of tobacco, alcohol, and other drugs. Approximately 6.6% of adolescent tobacco users had smoked a whole cigarette before age 13; 17.2% of adolescents

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report taking their first drink before age 13, and, nationwide, students (9th–10th grades) reported having used each of the following at one or more times in their life: marijuana (38.6%), hallucinogenic drugs (6.4%), cocaine (5.2%), ecstasy (5.0%), heroin (2.1%), and methamphetamines (3.0%; Kann et al., 2016). The aforementioned statistics are important as early initiation of tobacco, alcohol, and marijuana is associated with continued use of these substances and other illegal drugs into adulthood (Heinrich et al., 2016; Johnston, Liberato, & Thomas, 2012; Nkansah-Amankra & Minelli, 2016). Health care providers have the opportunity to be proactive and to facilitate discussions teaching youth about the negative health effects of tobacco and alcohol for which prevention is most important. Health-promotion and illness-prevention literature prioritize targeting at-risk youth and developing interventions that lead to behavior change (Mason et al., 2016; Stanton & Grimshaw, 2013). Prevention is the key to avoiding drug use in our adolescent population (CDC, 2010). A national drug-control strategy was developed, which offers a balanced approach to drug control and emphasizes communitybased prevention, integration of evidencebased treatment into the health care system, innovations in the criminal justice system, and international partnerships to disrupt drug-trafficking organizations (CDC, 2010). Nationwide, 3.9% of students who were surveyed reported having sexual intercourse for the first time before 13 years of age and 11.5% reported having sexual intercourse with four or more persons (Kann et al., 2016). These behaviors put adolescents at risk for HIV, other sexually transmitted diseases (STDs) and unintended pregnancies (CDC, 2016a). In 2013, 10,000 young people (aged 13–24 years) were diagnosed with HIV infection and 273,000 babies were born to teen girls (aged 15–19 years) in the United States (CDC, 2016a). During well-child visits, health care providers are in key positions to educate adolescents on the negative outcomes (HIV,

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others STDs, unintended pregnancies) associated with risky sexual behaviors. Adolescents tend to put themselves at risk for nutritional problems resulting from poor dietary behaviors, including skipping meals, snacking between meals (chips, candy), drinking soft drinks and energy drinks, as well as inadequately consuming fruits and vegetables (Brown, Skelton, Perrin, & Skinner, 2016; Carmona, 2006; Dowdell & Santucci, 2004; Loughridge & Barratt, 2005). Some adolescents use meal skipping as a means to lose weight and, in doing so, risk nutritional deficiencies during this critical stage of growth (Brown et al., 2016; Calderon, Yu, & Jambazian, 2004). Breakfast consumption is thought to benefit cognitive function, academic performance, school attendance rates, psychosocial function and mood (Rampersaud, Pereira, Girard, Adams, & Metzl, 2005; Wesnes, Pincock, & Scholey, 2012) However, only 38.1% of high school students reported eating breakfast daily for the past 7 days (CDC, 2014). In a study evaluating adolescent snacking behaviors and dietary intake, adolescents who snacked while watching television consumed fewer daily servings of fruit and vegetables and more daily servings of sugar-sweetened beverages as compared with those who never had a snack while watching television (Larson, Miller, Watts, Story, & Neumark-Sztainer, 2016). Adolescent health is not only influenced by dietary behaviors but also by physical activity (Elgar, Roberts, Moore, & TudorSmith, 2005). In a 2013 survey, only 27.1% of high school students participated in at least 60 minutes per day (all 7  days before the survey) of physical activity and only 29% attended physical education class daily (CDC, 2014). Physical activity is associated with body mass index (BMI) and physically inactive adolescents with elevated BMIs are more likely to develop cardiovascular disease as adults. When physical activity behaviors are formed in adolescence, these behaviors are more likely to persist into adulthood

(Dobbins, Husson, DeCorby, & LaRocca, 2013). Schools can foster appropriate dietary and physical activity behaviors by creating environments that encourage healthy eating habits and provide opportunities for physical activities (CDC, 2011). The school nurse can play an integral role in promoting the guidelines for healthy eating and physical activity in schools as outlined by the CDC (Bartol, 2016; CDC, 2011). Given the evidence of risky health behaviors and the importance of health promotion and prevention in the adolescent population, it is imperative that health care providers actively take a role in addressing these behaviors during health care encounters. Research on brain maturation is starting to reveal important relationships in terms of emotion regulation, behavioral responses, and risktaking activities in relation to ongoing brain development (development of the prefrontal cortex, limbic system, immune system, and neuroendocrine processes) during the adolescent period (Ahmed, Bittencourt-Hewitt, & Sebastian, 2015; Brenhouse & Schwarz, 2016). These complex developmental relationships should be taken into consideration as interventions are developed that target the six categories of adolescent health behaviors.

Suzy Mascaro Walter Ahmed, S. P., Bittencourt-Hewitt, A., & Sebastian, C.  L. (2015). Neurocognitive bases of emotion regulation development in adolescence. Developmental Cognitive Neuroscience, 15, 11–25. Bartol, T.  G. (2016). Recreating healthcare begins with the school nurse. Retrieved from http:// www.medscape.com/viewarticle/865849 Brenhouse, H.  C., & Schwarz, J.  M. (2016). Immunoadolescence:  Neuroimmune development and adolescent behavior. Neuroscience and Biobehavioral Reviews, 70, 288–299. Brown, C. L., Skelton, J. A., Perrin, E. M., & Skinner, A. C. (2016). Behaviors and motivations for weight loss in children and adolescents. Obesity, 24, 446–452. Calderon, L. L., Yu, C. K., & Jambazian, P. (2004). Dieting practices in high school students.

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Journal of the American Dietetic Association, 104(9), 1369–1374. Carmona, R. H. (2006). Healthy children:  Putting prevention first. Journal of the American Dietetic Association, 106(1), 17. Centers for Disease Control and Prevention. (2010). A new, balanced, and collaborative approach to drug control. Office of the Associate Director for Communication, Digital Media Branch, Division of Public Affairs (Online). Retrieved from http:// www.cdc.gov/Features/SubstanceAbuse Centers for Disease Control and Prevention. (2011). School health guidelines to promote healthy eating and physical activity. National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health (Online). Retrieved from http://www .cdc.gov/healthyschools/npao/strategies.htm Centers for Disease Control and Prevention. (2015). Teen drivers: Get the facts. National Center for Injury Prevention and Control, Division of Unintentional Injury Prevention (Online). Retrieved from http://www.cdc .gov/ MotorVehicleSafety/ Teen_ Drivers/ teendrivers_factsheet.html Centers for Disease Control and Prevention. (2016a). Bringing high-quality HIV and STD prevention to youth in schools. National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Division of Adolescent and School Health (Online). Retrieved from http://www .cdc.gov/ healthyyouth/ about/ pdf/ hivstd_ prevention.pdf Centers for Disease Control and Prevention. (2016b). National Center for Injury Prevention and Control. Wed-Based Injury Statistics Query and Reporting System (WISQARS) (Online). Retrieved from http://www.cdc.gov/injury/ wisqars/index.html Dobbins, M., Husson, H., DeCorby, K., & LaRocca, R. L. (2013). School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18. Cochrane Database of Systematic Reviews, 2013(2), CD007651. doi:10.1002/14651858.CD007651.pub2 Dowdell, E. B., & Santucci, M. E. (2004). Health risk behavior assessment: Nutrition, weight, and tobacco use in one urban seventh-grade class. Public Health Nursing, 21(2), 128–136. Elgar, F. J., Roberts, C., Moore, L., & Tudor-Smith, C. (2005). Sedentary behaviour, physical

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activity and weight problems in adolescents in Wales. Public Health, 119(6), 518–524. Elwell, S., Kulp, H., & McCue, J. (2014). Creating a comprehensive bicycle safety program. Journal of Trauma Nursing, 21(6), 309–313. Hagel, B. E., Romanow, N. T., Enns, N., Williamson, J., & Rowe, B. H. (2015). Severe bicycling injury risk factors in children and adolescents: A casecontrol study. Accident Analysis and Prevention, 78, 165–172. Heinrich, A., Müller, K. U., Banaschewski, T., Barker, G. J., Bokde, A. L., Bromberg, U., . . . Nees, F.; IMAGEN Consortium. (2016). Prediction of alcohol drinking in adolescents:  Personalitytraits, behavior, brain responses, and genetic variations in the context of reward sensitivity. Biological Psychology, 118, 79–87. Hooshmand, J., Hotz, G., Neilson, V., & Chandler, L. (2014). BikeSafe: Evaluating a bicycle safety program for middle school aged children. Accident Analysis and Prevention, 66, 182–186. Jelalian, E., Alday, S., Spirito, A., Rasile, D., & Nobile, C. (2000). Adolescent motor vehicle crashes: The relationship between behavioral factors and self-reported injury. Journal of Adolescent Health, 27(2), 84–93. Johnston, V., Liberato, S., & Thomas, D. (2012). Incentives for preventing smoking in children and adolescents. Cochrane Database of Systematic Reviews, 2012(10), CD008645. doi:10.1002/14651858.CD008645.pub2 Kann, L., Kinchen, S., Shanklin, S. L., Flint, K. H., Kawkins, J., Harris, W. A., . . . Zaza S.; Centers for Disease Control and Prevention. (2014). Youth risk behavior surveillance—United States, 2013. Morbidity and Mortality Weekly Report, 63(4), 1–168. Kann, L., McManus, T., Harris, W. A., Shanklin, S. L., Flint, K. H., Hawkins, J., . . . Zaza, S. (2016). Youth risk behavior surveillance—United States, 2015. Morbidity and Mortality Weekly Report, 65(6), 1–174. Kleinert, S., & Horton, R. (2016). Adolescent health and wellbeing: A key to a sustainable future. Lancet, 387(10036), 2355–2356. Kollar, L. M. (2013). Health promotion of the adolescent and family. In M. J. Hockenberry & D. Wilson (Eds.), Wong’s essentials of pediatric nursing (9th ed., pp. 476–497). St. Louis, MO: Elsevier.

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Larson, N. I., Miller, J. M., Watts, A. W., Story, M. T., & Neumark-Sztainer, D. R. (2016). Adolescent snacking behaviors are associated with dietary intake and weight status. Journal of Nutrition, 146(7), 1348–1355. Loughridge, J. L., & Barratt, J. (2005). Does the provision of cooled filtered water in secondary school cafeterias increase water drinking and decrease the purchase of soft drinks? Journal of Human Nutrition and Dietetics, 18(4), 281–286. Mason, M., Mennis, J., Way, T., Zaharakis, N., Campbell, L. F., Benotsch, E. G., . . . King, L. (2016). Text message delivered peer network counseling for adolescent smokers: A randomized controlled trial. Journal of Primary Prevention, 37(5), 403–420. Nash, N. A., Okoye, O., Albuz, O., Vogt, K. N., Karamanos, E., Inaba, K., & Demetriades, D. (2016). Seat belt use and its effect on abdominal trauma: A National Trauma Databank Study. American Surgeon, 82(2), 134–139. Nkansah-Amankra, S., & Minelli, M. (2016). “Gateway hypothesis” and early drug use:  Additional findings from tracking a population-based sample of adolescents to adulthood. Preventive Medicine Reports, 4, 134–141. Patton, G. C., Sawyer, S. M., Santelli, J. S., Ross, D. A., Afifi, R., Allen, N. B., . . . Viner, R. M. (2016). Our future: A Lancet commission on adolescent health and wellbeing. Lancet, 387(10036), 2423–2478. Pierce, S. R., Palombaro, K. M., & Black, J. D. (2014). Barriers to bicycle helmet use in young children in an urban elementary school. Health Promotion Practice, 15(3), 406–412. Rampersaud, G. C., Pereira, M. A., Girard, B. L., Adams, J., & Metzl, J. D. (2005). Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. Journal of the American Dietetic Association, 105(5), 743–60; quiz 761. Riese, A., Gao, H., Baird, J., Mello, M. J., & Ranney, M. L. (2017). Including youth violence screening on previsit questionnaires and the effect on other health risk behavior discussions. Clinical Pediatrics, 56(3), 284–287. Shain, B. N., & American Academy of Pediatrics Committee on Adolescence. (2007). Suicide and suicide attempts in adolescents. Pediatrics, 120(3), 669–676. Stanton, A., & Grimshaw, G. (2013). Tobacco cessation interventions for young people.

Cochrane Database of Systematic Reviews, 2013(8), CD003289. doi:10.1002/14651858.CD003289 .pub5 Wesnes, K. A., Pincock, C., & Scholey, A. (2012). Breakfast is associated with enhanced cognitive function in schoolchildren. An internet based study. Appetite, 59(3), 646–649. Zhu, M., Zhao, S., Long, D. L., & Curry, A. E. (2016). Association of graduated driver licensing with driver, non-driver, and total fatalities among adolescents. American Journal of Preventive Medicine, 51(1), 63–70.

ADVANCE DIRECTIVES Advance directives, also known as health care advance directives, are patient-initiated legal documents and refer to a living will and durable power of attorney for health care. Advance directives vary for each state and are accessible via online download. It is important to note that each state has its own laws regarding the process of completion of advance directives. Therefore, advance directives may not be honored from one state to another and nurses should be knowledgeable about these forms within their state of practice. Depending on the state, these documents may be combined into one document. These documents should be reviewed and updated periodically and completion of them should be considered for all individuals older than 18 years (Rao, Anderson, Lin, & Laux, 2014). Although advance directives are often thought of as being used for older adults, younger persons should consider completing them to assure that their wishes are honored, especially in the event of unexpected trauma. Assigning a proxy, representative, agent, or surrogate decision maker through the completion of a durable power of attorney for health care ensures that an individual’s values, beliefs, and wishes will be conveyed to the health care practitioners caring for him or her even in the absence of a living will. A

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durable power of attorney for health care is only valid when an individual has lost the ability to make sound, competent decisions. On the other hand, a living will is a written legal document in which an individual indicates whether he or she wishes to have treatments to prolong life or not to prolong life. In order for a living will to best reflect an individual’s choices, a basic understanding of possible scenarios and associated choices must be understood by the individual. Nurses play an important role, as part of the health care team, in assessing an individual’s understanding of care and treatment and are a valued resource for teaching individuals about these options and understanding terminology. Today, advance directives differ from the historical templates created in 1976 when California enacted the Natural Death Act affording terminally ill residents the right to authorize living will directives to prevent their life from being prolonged by life-sustaining equipment (Jecker, Jonsen, & Pearlman, 2012). Over the next 16 years, similar laws were enacted in all 50 states, and the advance directive document changed to reflect evolving circumstances in which a living will would be honored. In addition, states also recognized the use and the legal acceptance of a health care proxy, more recently known as a durable power of attorney for health care. The Patient Self-Determination Act (PSDA), a federal law, became effective in 1991 in response to a number of lawsuits, either because of the lack of clarity within the advance directives, or because an individual did not have one when he or she became incapacitated and families were divided about care decisions (Guido, 2010). In the absence of advance directives, and when an individual is placed on life support in a vegetative state, a decision to remove life support or withhold life-sustaining treatments can lead to legal battles among family members. As a result of these legal battles, in a landmark decision in 2005, the rule of intestacy was applied. A

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spouse or significant other carries the greatest weight in surrogate decision making, followed by the children, and then the parents (Allen, 2013). Furthermore, the PSDA requires hospitals receiving federal funding to ask, on admission, whether a patient has advance directives or whether he or she needs help to complete them. Possession of an advance directive is recorded in the electronic medical record (EMR). However, discussion of an individual’s understanding may not necessarily be recorded (Johnson, Zhao, Newby, Granger, & Granger, 2012). Studies on the impact on caregivers for chronically and critically ill individuals, without advance directives, have shown that decisional burden can result in stress and depression for those making decisions on behalf of another (Hickman & Pinto, 2014). Nurses, although in a unique position to provide decision support interventions (Hickman, Daly, Clochesy, O’Brien, & Leuchtag, 2016), should consider earlier discussions about advance directives during the palliative care trajectory. In the early 1990s, clarification of what to include in physician orders for life-sustaining treatment (POLST) was initiated in Oregon and has continued to be implemented nationwide. POLST is a separate but complementary document than an advance directive and is written in cases of advanced or end-stage illness to provide all health care practitioners the awareness that the physician is in alignment with the individual’s wishes regarding life-sustaining treatments. Medical orders for life-sustaining treatment (MOLST) can be completed by nurse practitioners or physician assistants. Different states refer to the MOLST by different names but the intent is the same (Institute of Medicine [IOM], 2015). To be effective advocates, nurses require knowledge of the distinction between a living will and a POLST or MOLST. Specific directives about the use of feeding tubes, nutrition and hydration, antibiotics, dialysis, organ and tissue donation, and pain management are other topics that should be included in advance directives (Keegan & Drick, 2011).

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Therefore, it is imperative that individuals discuss their wishes with their primary health care provider and significant others, and include them in advance directives to ensure that their desires are honored (Abele & Morley, 2016; Nelson, 2013). Despite the growing availability of advance directives since 1976, the completion and use of them has been slow. Reasons are multifactorial, including an individual’s lack of communicating or sharing a written document with family members and his or her health care practitioner and/or the ease of accessibility of these documents within health care facilities. However, more recently, improvement in completion of advance directives has been noted. In a retrospective cohort study involving 6,122 health and retirement study participants aged 60 years and older, the portion of decedents who had advance directives increased from 47% in 2000 to 72% in 2010 (Silveira, Wiitala, & Piette, 2014). Completion of a living will and including an individual’s do not resuscitate (DNR), do not intubate (DNI), and do not hospitalize orders had not been considered valid in most states in cases when the emergency medical services (EMS) personnel became involved. Before 2016, whether or not an individual had advance directives did not impact EMS responders’ legal obligation to initiate cardiopulmonary resuscitation (CPR) or lifesustaining measures when 911 was called. This was largely because physicians’ orders (POLST) were mostly written and acknowledged within health care facilities. Effective systems and processes for out-of-hospital DNR and DNI orders were often nebulous. However, in August 2016, the National Association of State EMS Officials released updated nationwide recommendation guidelines for EMS personnel on decision making for responding to scenarios in which a DNR decision is faced (National Association of Emergency Medical Service Officials [NASEMSO], 2016). This may occur in a nursing home or anywhere outside of a hospital. A valid DNR, either on an advance directive

form, card, bracelet, or on a POLST/MOLST document, would be considered exclusion criteria to the initiation of CPR. Both the individual and the health care provider’s name must be clearly visible for this information to be considered valid. Health care professionals continue to express discomfort in having discussions about advance directives (Coffey et al., 2016; National Academy of Medicine [NAM], 2016; Rhodes, Tindall, Xuan, Paulk, & Halm, 2015). Nursing research on advance directives has been limited and has mostly focused on nurses’ knowledge of advance directives and their confidence in discussing them (Coffey et al., 2016, Johnson et al., 2012; Ryan & Jezewski, 2012). In a systematic synthesis of three studies, Ryan and Jezewski (2012) reported that nurses identified a lack of upto-date knowledge on state or federal regulations and a lack of time and confidence to engage in meaningful discussion about end of life and were barriers to initiating discussions about advance directives. In a consensus study coordinated by the NAM, a national committee of experts reported the current state of end-of-life care in America (IOM, 2014) and progress toward resolution (NAM, 2016). Emphasis on a patient-centered interdisciplinary approach to encourage meaningful conversations among family members, caregivers, and health care providers about advance directives was an important recommendation. Educational gaps were identified with professional and undergraduate education, particularly in the area of interdisciplinary collaboration (IOM, 2014). An updated set of competencies for nurses was released in January 2016, to address the need for improvement in academic education for undergraduate nursing (Ferrell, Malloy, Mazanec, & Virani, 2016). Future nursing research should aim to focus on the following: (a) current status of educational preparation to identify congruency or barriers to implementation of the American Association of Colleges of Nursing (AACN)- and NAM-recommended

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competencies, (b) extent of creative interdisciplinary approaches to meaningful conversations about advance directives in undergraduate curricula or within professional development, (c) individuals’ understanding of advance directives and care options, and (d) incorporation of advocacy and communication skills to equip future health care providers to be able to address the gaps in health care systems and patient engagement.

Noreen Nelson Abele, P., & Morley, J. E. (2016). Advance directives:  The key to a good death? Journal of the American Medical Directors Association, 17(4), 279–283. Allen, J. F., Jr. (Ed.). (2013). Death and dying. In Health law and medical ethics for healthcare professionals (pp. 169–183). Upper Saddle River, NJ: Pearson. Coffey, A., McCarthy, G., Weathers, E., Friedman, M. I., Gallo, K., Ehrenfeld, M., . . . Itzhaki, M. (2016). Nurses’ knowledge of advance directives and perceived confidence in end-of-life care: A crosssectional study in five countries. International Journal of Nursing Practice, 22(3), 247–257. Ferrell, B., Malloy, P., Mazanec, P., & Virani, R. (2016). CARES: AACN’s new competencies and recommendations for educating undergraduate nursing students to improve palliative care. Journal of Professional Nursing, 32(5), 327–333. doi:10.1016/ j.profnurs.2016.07.002 Guido, G. W. (2010). Nursing care at the end of life. Upper Saddle River, NJ: Pearson. Hickman, R. L., Daly, B. J., Clochesy, J. M., O’Brien, J., & Leuchtag, M. (2016, May). Leveraging the lived experience of surrogate decision makers of the seriously ill to develop a decision support intervention. Applied Nursing Research, 30, 67–69. doi:10.1016/j.apnr.2015.10.012 Hickman, R. L., & Pinto, M. D. (2014). Advance directives lessen the decisional burden of surrogate decision-making for the chronically critically ill. Journal of Clinical Nursing, 23(5–6), 756–765.

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Institute of Medicine. (2014, September). Report brief: Dying in America: Improving quality and honoring individual preferences near the end of life. Washington, DC: National Academies Press. doi:10.17226/18748 Jecker, N. S., Jonsen, A. R., & Pearlman, R. A. (2012). Bioethics: An introduction to the history, methods and practice (3rd ed.). Sudbury, MA:  Jones & Bartlett. Johnson, R. W., Zhao, Y., Newby, K., Granger, C. B., & Granger, B. B. (2012). Reasons for noncompletion of advance directives in a cardiac intensive care unit. American Journal of Critical Care, 21(5), 311–319. doi:10.4037/ajcc2012394 Keegan, L. & Drick, C. A. (2011). End of life: Nursing solutions for death with dignity. New York, NY: Springer Publishing. National Academy of Medicine. (2016, May 23). Meeting recap: Assessing progress in end-of-life and serious illness care. Retrieved from https:// nam.edu/meeting-recap-assessing-progress-in -end-of-life-and-serious-illness-care National Association of Emergency Medical Service Officials. (2016). National model: EMS guidelines. Retrieved from http://www .nasemso.org Nelson, N. (2013). A death with dignity: A nurses’ story of the end of life of her mother. Nursing Forum, 48(2), 134–138. doi:10.1111/nuf.12021 Rao, J. K., Anderson, L. A., Lin, F. C., & Laux, J. P. (2014). Completion of advance directives among U.S.  consumers. American Journal of Preventive Medicine, 46(1), 65–70. Rhodes, R. L., Tindall, K., Xuan, L., Paulk, M. E., & Halm, E. A. (2015). Communication about advance directives and end-of-life care options among internal medicine residents. American Journal of Hospice & Palliative Care, 32(3), 262–268. Ryan, D., & Jezewski, M. A. (2012). Knowledge, attitudes, experiences, and confidence of nurses in completing advance directives: A systematic synthesis of three studies. Journal of Nursing Research, 20(2), 131–141. Silveira, M. J., Wiitala, W., & Piette, J. (2014). Advance directive completion by elderly Americans: A decade of change. Journal of the American Geriatrics Society, 62(4), 707–710. doi:10.1111/ jgs.12736

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AGEISM

AGEISM Ageism is defined as discrimination against individuals because they are old. It can be characterized by the dislike of an individual; avoidance of contact; discrimination of housing, employment, health services or any service simply due to age (Achenbaum, 2015). The term was first coined in 1969 by Robert N. Butler, MD, who at the time was a member of the National Capital Housing Authority. He witnessed age discrimination in Washington, DC, when the decision to turn an apartment complex to public housing for the elderly was made with considerable resistance from the community. He stated, “Age-ism might parallel racism as the great issue for the next 20–30 years” (Butler, 1969, p. 243). Ageism contributes to poor health care in older adults as well as exclusion of health care (Jönson, 2013). Evidence-based practice and safe best practices for older adults that do exist are less than adequate in ageing societies, unless regulatory mandates, such as those enforced by the Centers for Medicare & Medicaid Services, intervene (Carver & Parsons, 2012). Our nursing undergraduate programs may be guiding students away from elder care by promoting specialties such as critical care and medical/surgical units (Shen & Xiao, 2010). Ageism exists within the practice of nursing. Discrimination based on age underlies the nature of work expected of a nurse. For example, a young nurse is expected to practice in a physically demanding position in an acute care setting on a unit while rotating shifts. An elder nurse with seniority is seen in a position that is less physically demanding, working straight shifts with no rotations, such as in a long-term care facility (Harris, Bennett, Davey, & Ross, 2010). The proportion of the population in the United States older than 65 years is projected to increase from 12.4% in 2000 to 19.6% in 2030 (Centers for Disease Control and Prevention

[CDC], 2014). With this increasing number of older adults, many opportunities exist for nursing research in the topic of ageism. We can explore the workplace of the older nurse, the care provided to the older adult, outcomes of the older patient with respect to a variety of disease processes, and resources for the older adult, to mention a few. Butler, who defined ageism in 1969, feared that age and race were parallel when he witnessed it first in a housing opposition for an apartment complex for the elderly. Butler predicted that ageism would not fade. He predicted that it would replace racism. Butler was not the first to identify this discrimination for older adults. Butler’s achievement was to educate others about ageism. He served as the founding director of the National Institute on Ageing and the first chair of geriatrics at New York’s Mount Sinai School of Medicine. His goal was to train others about ageism so that all older adults were treated with dignity and respect (Achenbaum, 2013). Research has supported the following themes about ageism: older adults benefit from agerelated discounts and entitlements; the baby boom generation has seen both sides of ageism; when they were young, they mocked people who were older than 30 years, but now they are faced with job discrimination. Finally, elderly men and women who were once committed to retiring in their middle 60s are postponing retirement to their 70s. In many societies, negative attitudes toward the older adult exist. For example, an older adult may be marginalized by a family member when making a decision. A family member will state, “Honey, I know what the best choice on the menu is for you.” It is thought that the younger generation should care for the older adults in our community; however, in contemporary society, many households require both members of the home to maintain a full-time job while juggling children and their activities. This leaves the care of a loved older adult to the health care professionals. Stereotyping within society exists surrounding the older adult. An older

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adult may be thought of as too old to drive, too old to live alone, and too old to want to desire intimacy. These are all common stereotypes that society has regarding the older adult (Levy, Zonderman, Slade, & Ferrucci, 2012). Ageing is misunderstood by the community as a whole. With improved medical technology, life expectancy is increasing and a greater number of people are living longer. Fertility rates are dropping and individuals are having fewer children per household. This will decrease the ratio of young adults to older adults; therefore, it would benefit society to become more sensitive, as there will be more older adults (Kagan & Melendez-Torres, 2015). Ageism exists in the workplace and will rise as our workforce ages. Adults 55 years and older will increase by 38% from 2010 to 2020 (U.S. Bureau of Labor Statistics, 2012). Older adults are often victims of financial fraud because many older adults do not have the financial knowledge to manage their investments, therefore, they seek out professionals. This advice can be “spotty” and may be confusing to the older adult. Many times, the information from the professional has hidden fees that are not fully disclosed to the older adult, leaving the person confused, frustrated, and feeling lost after consultation with a professional (Setzfand & Watson, 2015). Access to retirement in the workplace has remained constant from 1979 to 2012, despite the rise of our ageing population. Employers continue to offer 46% of workers access to retirement benefits. The form of retirement has changed significantly. The number of employers offering employees defined-benefit plans, a plan in which employers contributed, has significantly declined and a shift has occurred to defined-contribution plans. This plan is one in which employees contribute a percentage of their salary toward retirement benefits. This decrease in benefits leaves older adults with less money available for retirement (Wiatrowski, 2013). Ageism occurs in contemporary nursing practice. This is evident when a nurse states,

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“He is too old to be HIV positive” or “She is too old to have gonorrhea.” Ageism is a determinant that has the potential to drive health, equal access to care, and quality outcomes for the older adult. Attitudes about older adults start in the nursing curricula when nursing students are exposed to the long-term care setting (Shen & Xiao, 2012). It is often presented as a setting that is understaffed, where patients receive less than adequate care, a setting where nurses practice at the end of their careers (Shen & Xiao, 2012). These misconceptions can be changed with the integration of quality-care initiatives, involving students in interdisciplinary care meetings and educating future nurses on the concept of ageism and how nurses can positively impact the care of the older adult. Currently, 15% of Americas older than 65 years require health care services (U.S. Bureau of Labor Statistics, 2012). This number is expected to rise significantly over the next 10 years, as the baby boomer generation continues to age. Older adults will have complex medical histories with more than one medical diagnosis. This will expand the opportunities for research. In summary, ageism is discriminating against the older population because it is older (Achenbaum, 2015). This negatively impacts the resources an older adult receives within health care, in the workplace, and in the community. With the population of adults 65 years and older projected to increase to 19.6% by the year 2030 (CDC, 2014), we are faced with an important nursing research topic: ageism. Many opportunities exist in the research arena surrounding ageism. We can look at how ageism affects the older adult related to a disease entity, how it affects health care, consider ageism within the nursing workforce and in the nursing curricula, and, based on the findings, make positive changes to impact and improve the quality of life of our older population.

Andrea M. Yevchak Donna M. Fick Rose Iannino-Renz

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Achenbaum, A.  (2015). A  history of ageism since 1969. Generations, 39(3), 10–16. Butler, R. N. (1969). Age-ism: Another form of bigotry. The Gerontologist, 9(4), 243–246. Carver, D., & Parsons, M. (2012). Value-based purchasing and practice strategies. Perioperative Nursing Clinics, 7(1), 297–303. Harris, R., Bennett, J., Davey, B., & Ross, F. (2010). Flexible working and the contribution of nurses in mid-life to the workforce:  A  qualitative study. International Journal of Nursing Studies, 47(4), 418–426. Jönson, H. (2013). We will be different! Ageism and the temporal construction of old age. The Gerontologist, 53(2), 198–204. Kagan, S. H., & Melendez-Torres, G. J. (2015). Ageism in nursing. Journal of Nursing Management, 23(5), 644–650. Levy, B. R., Zonderman, A. B., Slade, M. D., & Ferrucci, L. (2012). Memory shaped by age stereotypes over time. Journal of Gerontology, Series B: Psychological Sciences and Social Sciences, 67(4), 432–436. Setzfand, J., & Watson, M. (2015). Passive ageism and its effect on adults’ finances. Generations, 39(3), 39–45. Shen, J., & Xiao, L. D. (2012). Factors affecting nursing students’ intention to work with older people in China. Nurse Education Today, 32(3), 219–223. U.S. Bureau of Labor Statistics. (2012). Labor force projections to 2020: A more slowly growing workforce. Monthly Labor Review. Retrieved from https://www.bls.gov/opub/llr/2012/ 01/art3full.pdf Wiatrowski, W. J. (2013). The last private industry pension plans . Washington, DC: U.S. Bureau of Labor Statistics. Retrieved from h t t p s : / / w w w. b l s . g o / o p u b / t e d / 2 0 1 3 / ted_ 20130103htm

ALZHEIMER’S DISEASE According to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA],

2013), Alzheimer’s disease (AD) is a type of dementia and a mental disorder. Clinical criteria for the diagnosis of dementia include multiple cognitive deficits and, specifically, memory impairment. In addition, at least one of the following conditions is included: aphasia, apraxia, agnosia, or disturbance in executive functioning. AD, the most common cause of dementia, affects approximately 5.3 million adults and accounts for 50% to 60% of dementia cases. Many instances of dementia are the result of degenerative diseases whose progression cannot be arrested. However, several causes of dementia are either potentially reversible or stoppable and may be responsive, either totally or in part, to treatment. Types of dementia that are reversible include medication-induced dementia; metabolic disorders, such as endocrine, nutritional, or systemic disorders; vascular dementias, such as hydrocephalus, tumors, and hematoma; and depression. Brain pathology related to AD often begins in middle age and individuals begin to exhibit subtle cognitive decline (Knopman & Caselli, 2012). The ability to detect early cognitive decline is complicated by the fact that middle-age adults also exhibit losses in cognitive and brain function in the context of normal aging. Along with behavioral and subjective indicators, neuroimaging may be of particular use to categorize group profiles because age- and pathologically related changes often can be seen in the brain structure and function before the behavioral measures of functioning appear (Bondi et al., 2014). The prodromal phase of AD and other dementias is known as mild cognitive impairment (MCI). A diagnosis might be made too late because significant neuronal loss due to pathology starting in the medial temporal lobes already may have occurred (McDougall, Becker, & Arheart, 2006; Sperling et al., 2011). The Alzheimer’s Disease Neuroimaging Initiative (ADNI) outlined criteria for MCI to include: (a) subjective memory complaints reported by oneself, study partner, or

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clinician; (b) objective memory loss defined as scoring less than an education-adjusted cut-off score on delayed recall of Story A of the Wechsler Memory Scale—Revised (WMSR) Logical Memory Test (score = 8 for those with 16 years of education, score = 4 for those with 8–15 years of education, score = 2 for those with 0–7 years of education); (c) global Clinical Dementia Rating Scale (CDR) score of 0.5; and (d) general cognitive and functional performance sufficiently preserved such that a diagnosis of dementia could not be made by the site physician at the time of screening (Bondi et al., 2014). The presence of both MCI and decreased instrumental functional ability places all older adults at high risk of institutionalization (Gnjidic et al., 2012). Older adults with MCI—approximately 10% to 15% of people who are 65 years and older—are extremely vulnerable to the debilitating effects of stereotype threat because they (a) often have self-awareness of their impairment; (b) react to the impairment with justifiable feelings of frustration and sadness; (c) experience heightened anxiety when placed in situations (daily living as well as the neuropsychological testing context) in which the impairment is on display to others; and (d) by avoiding such situations, they isolate themselves more and in turn aggravate maladaptive rumination about their plight. Research directed toward mitigating stereotype threat among older adults with MCI holds the potential to reduce the “excess disability” induced by this psychosocial factor (Hess, Auman, Colcombe, & Rahhal, 2003). Nursing researchers are interested in aspects of health, such as symptom management. In the Nursing Diagnosis Handbook: An Evidenced-Based Guide to Planning Care, McDougall (2016) described the phenomenon of symptom management not only from the perspective of Nursing Outcomes Classifications but also the Nursing Intervention Classifications (McDougall, 2016). Because AD is a medical diagnosis, there are no theoretical underpinnings with

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the disease. However, researchers studying aspects of treatments may have unique theoretical mechanisms through which to study the behavioral manifestations of the illness.

PRECLINICAL DEMENTIA The National Institute on Aging and the Alzheimer Association (NIA-AA) proposed a framework for defining preclinical AD based on three stages (Jack et al., 2010). In cognitively normal individuals, there is a set of pathophysiological processes in AD that are observable with imaging and cerebrospinal fluid (CSF) biomarkers. The transition from biomarkers to a dementia model fits with data on the progression from cognitively normal to MCI. In the first stage of preclinical AD, an abnormal level of betaamyloid determined by amyloid imaging or by CSF assay is visible. The second stage of preclinical AD includes abnormal betaamyloid levels plus evidence of neuronal neurodegeneration seen from structural imaging, metabolic imaging, or CSF tau levels. In the third stage of preclinical AD, “subtle cognitive changes” accompany the stage 2 changes. The NIA-AA work group suggested that memory dysfunction was likely to be a key element in the transition. The cognitive changes are asymptomatic and only have meaning in the context of the abnormal biomarkers.

BETA-AMYLOID At the cellular level using anti-amyloid strategies the “amyloid cascade hypothesis” has not been sufficient to explain the neuronal damage in AD. An ongoing debate is whether neuroinflammation plays a significant role, either protective or harmful in neurodegenerative diseases. Neuroinflammation in AD, especially in the earliest stages, is part of a vicious cycle of glial priming, release of proinflammatory factors, and neuronal damage (Calsolaro & Edison, 2016).

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STIGMA

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The National Institutes of Health released PA-13–248, Research to Characterize and Reduce Stigma to Improve Health (2013). With the African American elder population projected to increase by more than 30% in the next 10 years (Administration on Aging, 2013), we need to develop and test interventions to improve the prognoses for this unique group, whose members are likely to have low memory self-efficacy on the one hand, and face stereotype threat on the other. All older adults and African Americans are highly susceptible to stereotype threat—a cultural stereotype associated with low memory and other cognitive abilities, which leads to an artificial decrement in these abilities. This increase in forgetfulness negatively impacts all elders’ well-being and quality of life. However, this particular group of Black elders is in a “double stereotype threat” predicament, potentially leading to even greater mental and physical decrements (Hess, Emery, & Queen, 2009; Pinel, 1999; Steele & Aronson, 1995).

LIFE-COURSE INQUIRIES Researchers have proposed that AD is more appropriately studied as a life-course phenomenon. Because of an increase in life expectancy, viewing AD as a disease of old age has evolved. Focusing on the latent period in adulthood permits researchers to consider vascular, lifestyle, psychological, and genetic risk factors as potential areas of interest. These factors allow for the development of risk scores for predicting the likelihood of developing a dementia. Age, low education, and vascular risk factors were identified as key factors in all scoring systems. These calculated risk scores can assist with predicting individuals who might benefit from interventions (Imtiaz, Tolppanen, Kivipelto, & Soininen, 2014).

PHYSICAL ACTIVITY It is relevant to consider psychosocial interventions for the prevention and treatment

of cognitive decline in aging and MCI populations. Huang, Fang, Li, and Chen (2016) reviewed neuroimaging studies on physical training in normal aging and MCI to identify the mechanisms underlying physical training. Studies of functional MRI, electroencephalography, magnetoencephalography, and positron emission tomography on brain networks were all included. The investigators found that the default mode network, frontoparietal network and frontoexecutive network are valuable targets for efficiency evaluation of interventions. Previous studies found cognitive brain networks were disrupted in aging and MCI populations, and physical exercise (PE) might change the trajectory of decline.

MEMORY SATISFACTION Assessment of memory complaints is an ongoing issue in the field. Our team developed a brief, psychometrically sound measure of memory perception and satisfaction. We used factor analysis and regression to investigate the use of the Memory Perception and Satisfaction Scale, a 20-item version of the Metamemory in Adulthood Questionnaire. Based on two samples of older adults (N  =  382 and N  =  221), the Memory Perception and Satisfaction Scale showed strong internal reliability and a two-factor structure. Our findings support the use of the Memory Perception and Satisfaction Scale, both in measuring perceptions of memory and predicting memory performance among older adults (McDougall et al., 2016b). The Alzheimer’s Association International Conference was held in Toronto, Canada, in July 2016. A few highlights from the conference are briefly presented. New Alzheimer’s therapy clinical trial results on the use of LMTM (TauRx Therapeutics) failed to demonstrate a treatment benefit in the full study population. In a small subgroup of the study population that received LMTM as a monotherapy, there was a statistically significant benefit on cognitive and

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functional outcomes, and slowing of brain atrophy. Next, researchers found that speedof-processing training may reduce the risk of developing cognitive decline or dementia over time. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study examined the impact of particular types of cognitive training on healthy adults older than 65. Two thousand, seven hundred and eighty-five participants at six trial sites were divided into four groups. Speed-of-processing training was the only item that showed a statistically significant impact on cognitive decline; at 10 years, the researchers observed a 33% reduction in risk of developing dementia over the period of the study. The scientists say this is the first time a cognitive training intervention has been shown to protect against dementia in a large, randomized controlled trial. Another major finding was that formal education and complex work may reduce the negative effects of bad diet and cerebrovascular disease on cognition. People whose work required complex thinking or activities are better able to withstand the onset of AD and that working with people, rather than data or physical things, was the main reason for the protective effect. Researchers introduced and described a new condition or patient status, known as mild behavioral impairment (MBI), which may be a forerunner of neurodegeneration and progression to dementia. This area has the potential to represent a paradigm shift in formal neurodegeneration testing—away from a sole focus on the memory to also encompass behavior. Finally, men receive dementia-related misdiagnosis more often than women. Women represent two thirds (3.3 million) of AD cases. Researchers from the Mayo Clinic in Jacksonville, Florida, examined records of 1,600 individuals from the State of Florida brain bank. Women with AD had lower education and older age at diagnosis and death, whereas men were younger at age of onset, had a shorter disease duration, and more commonly had an atypical clinical diagnosis

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(e.g., corticobasal degeneration or aphasia rather than Alzheimer’s).

Graham J. McDougall Jr. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: American Psychiatric Publishing. Bondi, M. W., Edmonds, E. C., Jak, A. J., Clark, L. R., Delano-Wood, L., McDonald, C. R., . . . Salmon, D. P. (2014). Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. Journal of Alzheimer’s Disease, 42(1), 275–289. Calsolaro, V., & Edison, P. (2016). Neuroinflammation in Alzheimer’s disease:  Current evidence and future  directions. Alzheimer’s & Dementia, 12(6), 719–732. Gnjidic, D., Stanaway, F. F., Cumming, R., Waite, L., Blyth, F., Naganathan, V., . . . Le Couteur, D. G. (2012). Mild cognitive impairment predicts institutionalization among older men: A populationbased cohort study. PloS One, 7(9), e46061. Hess, T. M., Auman, C., Colcombe, S. J., & Rahhal, T. A. (2003). The impact of stereotype threat on age differences in memory performance. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 58(1), P3–P11. Hess, T. M., Emery, L., & Queen, T. L. (2009). Task demands moderate stereotype threat effects on memory performance. Journal of Gerontology, Series B: Psychological Sciences and Social Sciences, 64(4), 482–486. Huang, P., Fang, R., Li, B. Y., & Chen, S. D. (2016). Exercise-related changes of networks in aging and mild cognitive impairment brain. Frontiers in Aging Neuroscience, 8, 47. Imtiaz, B., Tolppanen, A. M., Kivipelto, M., & Soininen, H. (2014). Future directions in Alzheimer’s disease from risk factors to prevention. Biochemical Pharmacology, 88(4), 661–670. Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., . . . Trojanowski, J. Q. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurology, 9(1), 119–128. Knopman, D. S., & Caselli, R. J. (2012). Appraisal of cognition in preclinical Alzheimer’s disease: A conceptual review. Neurodegenerative Disease Management, 2(2), 183–195.

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McDougall, G. J. (2016). Impaired memory. In B. J. Ackley, G. B. Ladwig, & M. B. F Makic (Eds.), Nursing diagnosis handbook: An evidenced-based guide to planning care (11th ed., pp. 579–582). St. Louis, MO: Elsevier. McDougall, G. J., Becker, H., & Arheart, K. L. (2006). Older adults in the SeniorWISE study at risk for mild cognitive impairment. Archives of Psychiatric Nursing, 20(3), 126–134. McDougall, G. J., George, S., McDonough, I., Lyon, L., Arherat, K., & LaRocca, M. (2016). Development and validation of the Memory Complaints inventory questionnaire. In J. Diehl-Schmid & K. Young (Chairs), Psychosocial and environmental assessment and care—different dementias, different cultures, different stages. Symposium conducted at the Annual Alzheimer’s Association International Conference, Toronto, Ontario, Canada. Pinel, E. C. (1999). Stigma consciousness: The psychological legacy of social stereotypes. Journal of Personality and Social Psychology, 76(1), 114–128. Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., . . . Phelps, C. H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 280–292. Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797–811.

ANIMAL-ASSISTED THERAPY Incorporating animals as an adjunct to treatment has been practiced in various disciplines by professionals, including registered nurses, physicians, physical and occupational therapists, social workers, psychologists, and licensed counselors (Kruger & Serpell, 2006) for myriad conditions, such as pervasive developmental disorders, cardiovascular disease, psychiatric disorders, cancer, and Alzheimer’s disease (Marcus, 2013).

With its broad biopsychosocial framework for health and symptom management, nursing is an optimal venue for animalassisted interventions (AAIs). As clinicians, nurses are amenable to using nontraditional practices in an effort to heal and provide comfort for their patients. In addition, nursing research focuses on understanding the symptoms of acute and chronic illness, finding ways to prevent or delay chronicity of physical or emotional illness, and finding overall approaches to achieve and maintain good physical and emotional health. In other words, nurses understand the interconnectedness among emotional, mental, and physical health and through alternative modalities can reduce or ameliorate stressors, allowing the body to do what it was designed to do—heal. Nursing’s unique role in both the psychological and physiological dimensions of illness and stress places it in an ideal position to examine and use the role of companion animals in clinical interventions. Practitioners of AAIs are often involved in pet visitation and animal-facilitated therapy programs in nursing homes, hospice, assisted living centers, and other short- and long-term care facilities. Research has demonstrated efficacy with this complementary modality, finding physiological, psychological, and emotional benefits in a variety of facilities, including hospitals (Diefenbeck, Bouffard, Matukaitis, Hastings, & Coble, 2010; Horowitz, 2010). Because the human–animal bond (HAB) is formed in a similar manner as a humanto-human bond, the attachment to an animal can be similar or even stronger in intensity. This bonding process is fostered through socialization, positive experiences, and physical contact with the animal (Robinson, 1995). Robinson indicates that the more similar the communication and sensory systems of the animals are to humans, the greater the likelihood of having a close relationship, which is why dogs and cats are often more desirable than a reptile or fish (Robinson, 1995). This bond is what makes AAIs possible.

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Historically, AAIs are believed to have been practiced as early as the 9th century in Gheel, Belgium, with handicapped persons (Altschiller, 2011; Serpell, 2000). Other research has documented the use of AAIs in the 1790s in York, England, where rabbits and chickens were incorporated as complementary modalities to treat the mentally ill to teach self-control without the use of restraints or harsh medicines (Altschiller, 2011; Arkow, 1987; Salotto, 2001). During the 1830s, mental institutions in Britain brought animals on the grounds to create a more pleasant environment (Serpell, 2000). Even Florence Nightingale had small animals that she shared with her patients while caring for wounded soldiers during the Crimean War; she found that animals reduced anxiety in children and adults in residential psychiatric facilities (Ernst, 2014). In her Notes on Nursing, she posited that a small pet is often an excellent companion for the sick, especially for the chronic cases (Nightingale, 1860; Serpell, 2006). In the 1960s, child psychiatrist Dr. Boris Levinson coined the term pet therapy after learning about the therapeutic benefits of having a dog in a counseling session. His cotherapist, “Jingles,” provided a way to reach severely withdrawn youth in treatment (Altschiller, 2011). During a session with an uncommunicative child, Dr. Levinson left the room, leaving his dog alone with the child for only a few moments. When he returned, the child was talking to the dog. This connection and positive response to “Jingles” was repeated by many other similar children (Altschiller, 2011). Despite the long history of incorporating animals therapeutically, the custom of AAIs is still being defined today. Literature searches reveal dozens of definitions of animal-assisted therapy and at least 12 different terms for the same practice, including pet therapy, pet psychotherapy, pet-facilitated therapy, pet-mediated therapy, and so forth. The most commonly used and preferred terminology and definition comes from Pet

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Partners, formerly known as the Delta Society, which is one of the largest organizations in the country responsible for registering therapy animals (Kruger & Serpell, 2006). The Pet Partners definition is cited consistently throughout the AAI literature. In 2013, a task was established for Animal-Assisted Therapy and Animal-Assisted Activity Guidelines for the Wellness of Animals involved through the International Association for Human Animal Interactions Organization (IAHAIO) and white paper published in (Jegatheesan et al., 2014). The definitions set forth by both Pet Partners and IAHAIO are similar, highlighting animal-assisted therapy as a goal-directed intervention by a health or human services professional who integrates animals into the treatment or care plan to achieve specified goals and objectives through measured progress (Jegatheesan et al., 2014). Also used are animal-assisted activities (AAA), which are less structured and typically conducted by volunteers. Pet visitation programs in hospitals would be an example of AAA. The difference lies in the absence of predetermined treatment goals and inconsistent practice. For most nurses, bringing their own dogs in for interventions may not be feasible due to the varied needs of the patients and needs of the dogs. However, it is not uncommon for nurses to work with a human–animal team for a therapeutic intervention. Dogs are most frequently brought into AAIs because of their general social nature, trainability, and size; however, horses are used extensively in a variety of remedial fields dealing with physical and psychological issues. In order to become a registered therapy dog, a dog older than 1 year must pass an evaluation through an organization such as Pet Partners or Therapy Dogs International. Most facilities and organizations require that therapy animals entering the buildings have this designation as a therapy dog. Horses are categorized and can be evaluated and registered by Pet Partners, but overall

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jurisdiction resides with the Professional Association of Therapeutic Horsemanship International (PATH International), which was formerly the North American Riding for the Handicapped Association (NARHA). Equine-facilitated psychotherapy (EFP) is facilitated by a credentialed health professional working with a credentialed equine professional. Hippotherapy, which is often incorrectly used synonymously with EFP, uses neurodevelopmental treatment and sensory integration based on the movement of the horse to improve balance, coordination, fine motor skills, posture, improve articulation, and increase cognitive skills (Kruger & Serpell, 2006). Anecdotal and empirical evidence demonstrates the effectiveness of AAIs for humans, but the well-being of the animals must also be taken into consideration. Guidelines from Pet Partners, IAHAIO, PATH, and other human–animal interaction organizations, such as the International Society for Anthrozoology, are becoming increasingly focused on the welfare of the animal. It is not enough for the dog or horse to just tolerate being in the sessions or acting as a cotherapist; the animal should enjoy it. Professionals need to understand that the animal in their charge is not just a tool, but a living, sentient being (Jegatheesan et al., 2014). In 1988, at the National Institutes of Health (NIH) Technology Assessment Workshop on the Health Benefits of Pets, major evidence was reported indicating that pet owners had an increase in 1-year survival rates after being discharged from a coronary care unit (Beck & Hatcher, 2003; Morrison, 2007; Siegel, 2002); demonstrating that pet ownership is a significant social predictor of 1-year survival for postcoronary patients studied. Ten years later, in an NIH clinical trial ancillary study to the Coronary Arrhythmia Suppression Trial (CAST), researchers reported that pet owners had slightly lower systolic blood pressures, plasma cholesterol, and triglyceride values than individuals without pets

(Beck & Hatcher, 2003). Combined, the study purports that because of pet ownership’s influence on psychosocial risk factors, having a loved pet reduces the incidence of cardiovascular disease (Beck & Hatcher, 2003). The inclusion of AAIs in hospitals has been shown to decrease medication use for pain and anxiety in cardiac patients as well as reductions in heart rate, blood pressure, respiratory rates, cortisol levels, epinephrine and norepinephrine levels, and other relaxation responses in the sympathetic and parasympathetic nervous systems (Cole, Gawlinski, Steers, & Kotlerman, 2007; DeCourcey, Russell, & Keister, 2010; Engelman, 2013; Patterson & Jensen, 2003). With an activated parasympathetic nervous system, the body can reach a state of equilibrium, diminishing the struggle to heal. In 1975, a resident at the Oakwood Forensic Center for the Criminally Insane in Lima, Ohio, rescued a wounded bird, and several severely depressed and typically noncommunicative patients cared for it (Lai, 1998; Strimple, 2003). Subsequently, the hospital conducted a yearlong study to attempt to mimic the results in other wards. The wards with animals present saw the levels of medication reduced to half and violent acts and suicide attempts decreased; the control population showed no change (Lai, 1998; Strimple, 2003). Similar results have been noted in other facilities. Animals also provide necessary social support and increase the frequency of this type of support for individuals who consider their pet to be a friend, a family member, and a confidant (Beck & Hatcher, 2003). For individuals with a human social support deficit, pets can moderate an intimacy with other humans. For the elderly who live alone, animals play a positive role in the improvement of life satisfaction, offer a sense of purpose, and provide feelings of personal safety compared with elders who don’t have pets (Beck & Hatcher, 2003). Incorporating dogs therapeutically, even for one 30-minute session per week has been

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demonstrated to be clinically significant in reducing feelings of loneliness per patient self-reports. Other measured benefits include decreased blood pressure and heart rate as well as an increased peripheral skin temperature (McCabe, Baun, Speich, & Agrawal, 2002). Patients with Alzheimer’s disease who have an attachment to a companion animal have fewer mood disorders and fewer episodes of anxiety and aggression compared with those without a loved pet (McCabe et al., 2002). From a physical health perspective, individuals with companion animals have a lower frequency of primary care visits (Siegel, 1990). Stressful life situations contribute to higher physician visitation rates because of the stressors’ interconnectedness with psychological distresses. The more stressors experienced, the greater attention paid and significance attributed to physiological symptoms, thus more trips to the family physician. Individuals encountering meaningful interactions with animals saw improved moods and faster recovery times (Coakley & Mahoney, 2009). Feelings of loneliness and isolation are common in residential facilities—whether in prisons, youth detention centers, hospitals, nursing homes, or assisted living. The physical separation from loved ones (through spousal loss, loss of home) often triggers the onset of loneliness and need for social relationships (Banks & Banks, 2002; Geisler, 2004). Residents in nursing homes who received regular pet visits had lower scores for loneliness than those with a low level or no contact (Banks & Banks, 2002). Animal-assisted therapies distract patients from pain perception and often provide comforting thoughts of home (Coakley & Mahoney, 2009). Rather than feeling lonely, the dogs made patients feel connected, cared for, and provided them with a sense of purpose. Attachment to another being is associated with greater physical health. Pets provide companionship, feelings of security, and of being loved (Siegel, 1990). Further research

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has found a decrease in anxiety, systolic pulmonary artery pressure, and epinephrine and norepinephrine levels (Coakley & Mahoney, 2009) in individuals with pets. Alzheimer’s disease provides specific challenges for individuals who require alternative interventions. These challenges include agitation, aggression, delusions, hallucinations, sleep problems, wandering, and vocalizations. Agitation affects more than 90% of the residents, which inhibits optimal health care (Richeson, 2003). This concern continues to escalate as the Alzheimer’s Association predicts that by 2050, there will be 14 million people affected by Alzheimer’s disease. For individuals with Alzheimer’s disease, sensory-based techniques have been used successfully to promote independence, decrease medications and need for physical restraint, and improve the quality of life (McCabe et al., 2002). Settings that are secure and comforting, featuring a myriad of sensory stimuli are most effective for these residents. The success of using companion animals stems from those factors. McCabe et  al. (2002) posited that when a dog was present on the unit from morning to evening, results showed the resident to be less violent, have fewer conflicts, need less medication, and have more acceptable behavior as well as decreased agitation and improved socialization during sundown hours; very similar to the aforementioned study at the institution where the residents cared for the injured bird. Whether it is because of the bond with a nonjudgmental being, finding a sense of purpose or a connection to nature, almost any animal can have a therapeutic impact. Using animals other than dogs might be more acceptable in certain settings, such as fish tanks used to improve morale and eating habits. Research by Edwards and Beck (2002) has found that the presence of fish in a nursing home dining room provided a positive influence for Alzheimer’s patients as residents sat at the table longer and consumed more calories, which meant a weight gain of 1.65 pounds and less need for nutritional

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supplements; patients felt the fish provided a nice distraction during prolonged hospital stays and felt less of the anxiety, depression, and hostility typically seen in patients awaiting a heart transplant. Pets in nursing homes encourage an increase in the level of social interaction among people. Increase in social and verbal interaction provides a valuable adjunct to other therapies (Geisler, 2004). Residents can experience themselves as a nurturer and a caregiver rather than the recipient of care (Geisler, 2004). Benefits of AAIs have demonstrated both physical and fiscal outcomes. Employing the use of animals has been shown to be a cost-effective intervention in a variety of health care settings through shorter hospital stays, reduction in need for medication, and an increase in food consumption resulting in a decrease in the need for supplements. A  study conducted in New  York, Missouri, and Texas showed that in nursing homes where animals and plants are an integral part of the environment, medication costs dropped from an average of $3.80 per patient per day to just $1.18 per patient per day (Geisler, 2004). At the other end of the life span, AAIs have been successful in working with chronically ill children. Companion animals have been found to provide companionship and tactile comfort, decrease stress, and facilitate social interaction as well as decrease cardiovascular reactivity to stress. Companion animals serve as playmates, confidants, and friends who provide unconditional love, a direct source of social support (Spence, 2002). The bond children have with companion animals has been positively related to improved self-esteem, social competence, and socioemotional functioning. Pets serve as social facilitators based on findings that animals make a person more socially attractive and provide a topic for conversation, which could be important for chronically ill children who may feel different and whose social life may be interrupted (Spence, 2002).

The acronym HAB is used across disciplines, yet there is no universally accepted definition of the human–animal bond (Fine, 2015, p. 5). There are, however, several commonalities among definitions, including that the relationship is reciprocal, persistent, and voluntary with a level of trust on the part of the animal (Fine, 2015). If the animal does not recognize his owner or guardian, there is no bond (Fine, 2015). Reviewing the criteria for defining the bond that occurs among humans reveals a similar style of bonding between humans and animals. The American Veterinary Association suggests that the HAB is a mutually beneficial relationship that is influenced by behaviors that support the well-being of both humans and animals (American Veterinary Medical Association, 2016). It is this bond that allows AAIs to be useful. AAIs are not necessarily theory specific; therefore, a variety of theories can be used. When reviewing the literature related to theories and AAIs, the most common theory that underpins the work is the biophilia hypothesis. E. O. Wilson’s biophilia hypothesis (1984, 1993) theorizes that there is an innate desire for positive affiliations with other living organisms (Amiot & Bastian, 2014; Bruneau & Johnson, 2016). Adjusted theoretical versions of the biophilia hypothesis have added that biophilia is more than a single instinct, but rather complex learned thoughts and behaviors that trigger emotional reactions, which have been shaped by culture (Amiot & Bastian, 2014; Wilson, 1993). Other theories that uphold AAIs include, but are not limited to, attachment theory; attentionis egens, or attention seeking; Rogerian theory; learning theory; social mediation theory; object relations theory; cognitive theories. Although the use of AAI dates back hundreds of years, the amount of empirical evidence supporting its effectiveness is just now gaining momentum. Concerns about studies lacking adequate rigor on the effectiveness of AAIs have dominated the literature in past decades; concerns include a lack of random

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assignment, lack of control groups, small sample sizes, not including strong controls, and a lack of long-term posttreatment followup assessments (Herzog, 2015). Isolating variables to show the animal as the catalyst for change is often difficult. Beck and Hatcher (2003) write that there are inconsistencies within the literature and, as a result, the magnitude of the health benefits may be overestimated or underestimated, begging the question as to whether the populations that benefit would fare just as well enjoying other living environments like gardening or walking in green spaces, and so on. Even rigorous experimental designs used in natural settings are subject to intervening variables that are outside of the researchers’ control (Wilson & Barker, 2003). Other considerations include sample selection within specific populations (e.g., Alzheimer’s patients), which makes randomization meaningless (C. Wilson & Barker, 2003) and is not always accurate in generalizing groups from one facility to another. With that being said, Beck and Hatcher (2003) concluded that the available data do suggest that animals play a significant role in benefiting the lives of humans and despite the deluge of anecdotal evidence and relatively fragile empirical data, the field of animal-assisted therapy continues to be vibrant and alive in a variety of clinical and nonclinical settings. In an effort to make the practice more mainstream and accepted throughout the various disciplines, current practitioners conducting evidence-based research are needed to provide welldesigned research studies to further demonstrate scientifically the efficacy that so many have experienced while using AAIs. Herzog (2015) praises research journals like the HAB journal, Anthrozoos, for discontinuing the practice of publishing studies that do not include control groups. The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Waltham Center for Pet Nutrition (a division of Mars)

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has given more than $9 million to support more rigorous research related to human– animal interactions (Herzog, 2015). As the field continues to grow, the quality of research is improving and better validates the effectiveness of AAIs.

Amy R. Johnson Amiot, C., & Bastian, B. (2014). Toward a psychology of human-animal relations. Psychological Bulletin. doi:10.1037/a0038147yp Banks, M. R., & Banks, W. A. (2002). The effects of animal-assisted therapy on loneliness in an elderly population in long-term care facilities. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 57(7), M428–M432. Beck, A., & Hatcher, A. (2003). Future directions in human–animal bond research. American Behavioral Scientist, 47(1), 79–93. Bruneau, L., & Johnson, A. (2016). Fido and Freud meet: Integrating animal assisted interventions with counseling theory. Paper based on a program presented at the 2011 American Counseling Association Conference, New Orleans, LA. VISTAS Online. Retrieved from http://www .michaelwilliamscounseling.com/?cat=90 Coakley, A. B., & Mahoney, E. K. (2009). Creating a therapeutic and healing environment with a pet therapy program. Complementary Therapies in Clinical Practice, 15(3), 141–146. Cole, K. M., Gawlinski, A., Steers, N., & Kotlerman, J. (2007). Animal-assisted therapy in patients hospitalized with heart failure. American Journal of Critical Care, 16(6), 575–585; quiz 586; discussion 587. DeCourcey, M., Russell, A. C., & Keister, K. J. (2010). Animal-assisted therapy:  Evaluation and implementation of a complementary therapy to improve the psychological and physiological health of critically ill patients. Dimensions of Critical Care Nursing, 29(5), 211–214. Diefenbeck, C., Bouffard, L., Matukaitis, J., Hastings, H., & Coble, S. (2010). Healing paws: Animal assisted therapy in acute care. Nursing Critical Care, 5(4), 34–39. Edwards, N. E., & Beck, A. M. (2002). Animalassisted therapy and nutrition in Alzheimer’s disease. Western Journal of Nursing Research, 24(6), 697–712. Engelman, S. R. (2013). Palliative care and use of animal-assisted therapy. Omega, 67(1–2), 63–67.

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Ernst, L. (2014). Animal-assisted therapy: An exploration of its history, healing benefits, and how skilled nursing facilities can set up programs. Annals of Long-Term Care: Clinical Care and Aging, 22(10), 27–32. Geisler, A. M. (2004). Companion animals in palliative care: Stories from the bedside. American Journal of Hospice & Palliative Care, 21(4), 285–288. Herzog, H. (2015). The research challenge: Threats to the validity of animal-assisted therapy studies and suggestions for improvement. In A. H. Fine (Ed.), Handbook on animal assisted therapy: Foundations and guidelines for animal assisted interventions (4th ed., pp. 408–413). San Diego, CA: Academic Press/Elsevier. Horowitz, S.  (2010). Animal-assisted therapy for inpatients. Alternatives and Complementary Therapies, 16(6), 339–343. Jegatheesan, B., Beetz, A., Ormerod, E., Johnson, R., Fine, A., Yamazaki, K., . . . Choi, G. (2014). The IAHAIO definitions for animal assisted intervention and animal assisted activity and guidelines for wellness of animals involved task force (White paper). Retrieved from http://www.iahaio.org/new/index.php?disp lay=declarations Kruger, K., & Serpell, J. (2006). Animal-assisted interventions in mental health: Definitions and theoretical foundations. In A. H. Fine (Ed.), Handbook on animal assisted therapy: Theoretical foundations and guidelines for practice (2nd ed., pp. 21–38). San Diego, CA: Elsevier. Marcus, D. A. (2013). The science behind animalassisted therapy. Current Pain and Headache Reports, 17(4), 322. McCabe, B. W., Baun, M. M., Speich, D., & Agrawal, S. (2002). Resident dog in the Alzheimer’s special care unit. Western Journal of Nursing Research, 24(6), 684–696. Morrison, M. L. (2007). Health benefits of animalassisted interventions. Complementary Health Practice Review, 12(1), 51–62. Nightingale, F. (1860). Notes on nursing. New York, NY: Appleton. Patterson, D. R., & Jensen, M. P. (2003). Hypnosis and clinical pain. Psychological Bulletin, 129(4), 495–521. Richeson, N. E. (2003). Effects of animal-assisted therapy on agitated behaviors and social interactions of older adults with dementia.

American Journal of Alzheimer’s Disease and Other Dementias, 18(6), 353–358. Robinson, I. (1995). Associations between man and animals. In I. Robinson (Ed.), The Waltham book of human–animal interaction: Benefits and responsibilities of pet ownership. Tarrytown, NY: Elsevier Science. Serpell, J. (2000). Historical exploration of the value of human-animal relationships. In A. H. Fine (Ed.), Handbook on animal assisted therapy: Theoretical foundations and guidelines for practice. San Diego, CA: Elsevier. Serpell, J. (2006). Animal assisted interventions in historical perspective. In A. H. Fine (Ed.), Handbook on animal assisted therapy: Theoretical foundations and guidelines for practice (2nd ed., pp. 3–17). San Diego, CA: Elsevier. Siegel, J. M. (1990). Stressful life events and use of physician services among the elderly:  The moderating role of pet ownership. Journal of Personality and Social Psychology, 58(6), 1081–1086. Wilson, C., & Barker, S. (2003). Challenges in designing human-animal interaction research. American Behavioral Scientist, 47(1), 16–28. Wilson, E.  O. (1984). Biophilia. Cambridge, MA: Harvard University Press. Wilson, E.  O. (1993). Biophilia and the conservation ethics. In S. R. Kellert & E. O. Wilson (Eds.), The biophilia hypothesis (pp. 31–41). Washington, DC: Island Press.

APPLIED RESEARCH In an attempt to differentiate among various types of research, the scientific community uses myriad terms, which, however, tend to fall into a discrete classification. On the one end, terms such as basic, fundamental, and theoretical research are used to refer to research focused on discovering fundamental principles and processes governing physical and life phenomena. On the other end, we find such terms as applied, clinical, practical, and product research. These refer to the application of the findings of basic/fundamental/theoretical research to generate research aimed

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at answering focused and problem-specific questions. Although it is the subject of ongoing debate, it is assumed that there are fundamental principles and processes that are at the core of the discipline of nursing and its central tenets of health, patient, nurse, and environment. In addition, it is assumed that nursing draws on fundamental principles and processes discovered in other disciplines to generate new knowledge about nursing and patient care. Under these assumptions, applied research in nursing can be defined. The etymology of applied goes back to the Latin adplicare, meaning to put something (a law, a test, etc.) into practical operation. Applied research in nursing, then, refers to research aimed at concrete and practical issues and questions of concern to the delivery of nursing care. The most evident type of applied

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research is intervention research—from exploratory investigations to randomized controlled trials. This type of applied research is aimed at providing answers to questions about the effectiveness, efficacy, and safety of nursing interventions. Yet nonintervention (or descriptive) research may be categorized as applied research as well if it meets the general criterion of being focused on concrete and practical issues and questions about nursing care. Other types of applied research in nursing include studies on models of care, research on organizational or other systems-level determinants of care, analyses of the nursing work force, and studies on the economic aspects of nursing care.

Ivo Abraham Sabina De Geest Karen MacDonald

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B BASIC RESEARCH Basic research includes all forms of scholarly inquiry for the purpose of demonstrating the existence or elucidation of phenomena. Basic research is conducted without the intent to address specific problems or realworld application of knowledge. As a discipline and a science, nursing is informed by knowledge from basic and applied research, and nursing disciplinary knowledge is integrated into the broader context of the whole of human knowledge. The origins of nursing research trace back to Florence Nightingale. Over time, the majority of the scholarly work is best categorized as applied rather than basic research in that nursing research has been conducted for the primary purpose of solving problems related to human health. Nursing seeks knowledge from the perspective of the human experience of health. Human perceptions and experiences of health are studied with the intent to generate knowledge to solve problems through nursing care and practice. There is a cadre of nurses who were doctorally prepared in the basic sciences, both social and biological, as part of the U.S. Public Health Service Nurse Scientist Training Program from 1962 until the late 1970s. Nurses with doctoral degrees in basic sciences were prepared to contribute as basic researchers, and then they adapted their knowledge and skills to conduct nursing research. Despite the growing number and popularity of doctoral programs in nursing, small numbers of nurses continue to pursue degrees in the basic sciences in the United States. This educational path is used more

often in countries where doctoral programs in nursing are not available. Another link between the basic sciences and nursing has evolved as a result of doctoral students in nursing pursuing a graduate minor in a basic science or a postdoctoral fellowship in a basic science. These basic research programs for nurses with doctoral degrees in nursing are facilitated by nurses with doctoral degrees in basic research disciplines. Nurse researchers often engage in basic research to generate knowledge that may lead to new perspectives for applied research in nursing.

Sue K. Donaldson

BEHAVIORAL RESEARCH An examination of behavioral research is best begun by considering what it is and differentiating it from related areas of research. Behavioral research within nursing generally refers to the study of health-related behaviors of persons. Studies may include the following areas: (a) health-promoting behaviors such as exercise, diet, immunization, and smoking cessation; (b) screening behaviors such as mammography, breast self-examination, and prostate examinations; and (c) therapeutic behaviors such as adherence to treatment regimen, blood glucose monitoring, participation in cardiac rehabilitation programs, and treatment-related appointment keeping. The research spans medical and psychiatric populations. It is directed toward an understanding of the nature of behavior and health relationships and to the modification of behaviors that affect health. It has been

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estimated that over half of premature deaths could be prevented if health behaviors were altered. Behavioral research has its roots in learning theories that arose in the early part of the 20th century. Classical or respondent conditioning was followed by instrumental or operant conditioning and evolved into the cognitive behavioral theories that dominate the field today. In classical conditioning, an unconditioned stimulus is paired with a conditioned stimulus, resulting in the development of a conditioned response. Much of the research emphasizes conditioned physiological responses. An example is found in the study of anticipatory nausea and vomiting during chemotherapy. In this case, chemotherapy (unconditioned stimulus) may induce nausea and vomiting. After several exposures to chemotherapy in a particular setting (conditioned stimulus), the setting itself may induce nausea and vomiting (conditioned response) before and independent of the actual administration of the chemotherapy (unconditioned stimulus). Another example is the reciprocal inhibition or desensitization in which anxiety is viewed similarly as a conditioned response to stimuli. An incompatible response (relaxation) is paired with progressively stronger levels of the conditioned stimulus in order to inhibit anxiety responses. With instrumental or operant conditioning, behavior is seen as arising from environmental stimuli or random exploratory actions, which are then sustained by the occurrence of positive reinforcement following the behavior. Laws have been established that address the identification of reinforcers, the schedules of administration of reinforcers for initiation and maintenance of behavior, and strategies for the extinction of behavior. In this model, motivation is seen as a state of deprivation or satiation with regard to reinforcers. Numerous strategies have evolved from this work, including but not limited to contracting and tailoring, which have been used in the studies of patient adherence;

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token economies, which have been used in studies on unit management with the mentally ill or developmentally delayed; and contingency management, which has been used in the promotion of treatment behaviors, such as exercise. As the operant model has expanded over time, self-management, or self-regulation, has evolved as a special case of contingency management. With self-management the individual is responsible for establishing intermediate goals, monitoring progress toward those goals, and administering selfreinforcement for success. Self-management has been studied particularly for chronic, long-term regimens, such as those for diabetes, asthma, and cardiovascular disease. In both of these models there is an emphasis on behavior rather than motivation or personality or relationships, beyond that of the reinforcing behaviors of significant others. The history of the behavior is of less interest than the factors that currently sustain the behavior. An empirical model is used with an assessment of the frequency or intensity of the behavior over time, the stimulus conditions that precede the behavior, and the consequent or reinforcing events that follow the behavior. Intervention is then directed to the specific areas targeted by the initial assessment. Detailed assessment continues through the course of intervention and often through a period following intervention to assess maintenance or generalization. Each of the cognitive behavioral models identifies a cognitive feature as a major motivational determinant of behavior. Selfefficacy theory postulates the role of perceived capability to engage in a behavior under various conditions. The theory of reasoned action postulates that intention to engage in a behavior is significant and is influenced by beliefs regarding behavioral outcomes and attitudes toward the behavior. The health belief model postulates that one’s perceptions about the illness in terms of its threat (severity and susceptibility), as well as the perception of the benefits and barriers

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to engaging in the behavior, influence intentions and subsequently behavior. The common sense model of illness proposes that the individual’s own model of the illness influences his or her illness or treatment-related behaviors. Behavioral research can be distinguished from psychosocial research, which tends to emphasize adjustment and coping as well as predictor and moderator variables arising from the psychological state or the social environment of the person. Behavioral research, including cognitive behavioral studies, emphasizes behavior. In the classical and instrumental models, observable behavior is stressed. In the cognitive behavioral model, both observable and covert behaviors are stressed. Within nursing much of the behavioral research has addressed participation in treatment, exercise, sexual behaviors, health promotion, breast self-examination and mammography use, childbirth and maternal behaviors, behavioral symptoms of dementia, self-management in chronic conditions, management of alcohol or drug dependency, and the role of biofeedback in such behaviors as pelvic floor muscle exercise in incontinence and heart rate variability. Unlike psychosocial studies, factors, such as personality, coping strategies, and socioeconomic status, are not primary interests; however, they may be of interest in determining reinforcers and stimulus conditions. There is an additional body of behavioral research that tends to be interdisciplinary in nature and is of relevance to nursing. There are studies in the community to modify health behaviors within populations and studies within multicenter clinical trials that attempt to influence the health behavior or protocol-related behaviors of research participants. Also there is a broad set of studies used to identify the relationship between behavior and disease etiology, such as studies of the role of exercise on the maintenance of function in the older adult, mechanisms of addiction in smoking behavior, and the effect of neurotransmitters on eating behaviors.

This field has come to be known as biobehavioral research. Given the prevalence of lifestyle behaviors that adversely affect health and the management of illness, research to understand and modify these behaviors would benefit the individual as well as the population. There is a need for nursing research to expand into the interdisciplinary arenas, particularly in the examination of health behavior change in the community, studies within multicenter clinical trials, and the etiological relationship between behavior and health and illness. Furthermore, many of the studies in nursing have been descriptive in nature or have focused on the development of assessment instruments. Few of the studies have examined how to intervene with behaviors that contribute to the development or progression of illness. This research, however, would be useful to better direct interventions with patients.

ACKNOWLEDGMENT This paper was supported in part by a National Institute of Nursing Research grant (5 P30 NR03924) and a National Heart, Lung, and Blood Institute grant (1 UO1HL48992).

Jacqueline Dunbar-Jacob

BIOFEEDBACK Biofeedback is a training program in which individuals are provided with visual and/ or audio information about their physiological state. The physiological data are measured using noninvasive electro-sensors, and the data are processed and displayed through a computerized device. It is through the feedback training that individuals learn techniques to consciously regulate involuntary bodily functions such as balancing the autonomic nervous system. Psychological responses often

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co-occur with the change of physiological and emotional states. With repeated practice, individuals often become mindful about the selfregulation technique and may achieve the desired physiological and psychological state without the assistance of external devices. In the past, biofeedback for symptom management has been thought to be simply training the muscles and body functioning through operant conditioning, but now it is more common to consider the brain and the central nervous system as the central focus of the treatment. It is, after all, the electrical–biochemical systems through which all bodily activities are finally determined. In order to focus on the brain–neural pathway, biofeedback acknowledges the mind–body interface and the centrality of the brain in the disease process. The intervention that entrains brain-wave regulation is called neurofeedback (Hammond, 2011), a form of biofeedback. There are many more studies that have incorporated both the traditional biofeedback component and the brainwave training (neurofeedback). In biofeedback/neurofeedback, the most commonly indexed physiological states include heart rate, heart rate variability (HRV), respiration, blood pressure, body temperature, peripheral sweating level (also known as galvanic skin response [GSR], electrodermal response [EDR], or skin conductance [SC]), muscle activity electromyography (EMG), and brain-wave EEG. The goal of biofeedback/neurofeedback is to enable the process of self-regulation for health promotion, symptom management, and peak performance (Biofeedback, 2016). Since 1980, thousands of studies have been conducted to examine the clinical implication of biofeedback/neurofeedback. The most studied conditions include but are not limited to: poststroke rehabilitation (Woodford & Price, 2007), urinary incontinence (Fazeli et al., 2015; Fitz et al., 2012), temporomandibular disorders, hypertension (Nakao, Yano, Nomura, & Kuboki, 2003), migraine (Nestoriuc & Martin, 2007), chronic back pain (Sielski, Rief, & Glombiewski, 2016), and attention deficient hyperactive disorder

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(ADHD; Cortese et al., 2016). In addition, there is one line of research in biofeedback/ neurofeedback that involves the use of light and/or sound stimulation to entrain brainwaves for symptom management and health promotion. The targeted conditions ranged from cognitive functioning, stress reduction, and pain management to sleep promotion (Budzynski, 1996; Budzynski & Budzynski, 2000; Huang & Charyton, 2008; Tang, Riegel, McCurry, & Vitiello, 2016). There are three major organizations for biofeedback professionals:  the Association for Applied Psychophysiology and Biofeedback, the Biofeedback Certification Institution of America, and the International Society for Neurofeedback and Research. There are more than 100 nurse professionals in the Biofeedback Certification Institution of America, the certifying body for biofeedback or neurofeedback. Nursing biofeedback research has shown effective changes in patient symptoms through the application of complementary techniques. A review of biofeedback or self-management training research by nurses before 1997 indicated favorable patient outcomes when performing management of stress symptoms, progressive relaxation, reduction of tension with electromyography training, hand warming, training during childbirth, respiratory training, and HRV training (Nakagawa-Kogan, 1994). These publications predominantly indicated the individual efforts to inform the field of their respective specialized treatments. Biofeedback research has been integrated into nursing education programs even though there is little published research.

Hsin-Yi (Jean) Tang Budzynski, T.  (1996). Brain brightening:  Can neurofeedback improve cognitive process? Biofeedback, 24(2), 14–17. Biofeedback. (2016). About biofeedback. Retrieved from http://www.aapb.org/i4a/pages/index .cfm?pageid=3463

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Budzynski, T., & Budzynski, H.  K. (2000). Reversing age-related cognitive decline: Use of neurofeedback and audio-visual stimulation. Biofeedback, 28(3), 19–21. Cortese, S., Ferrin, M., Brandeis, D., Holtmann, M., Aggensteiner, P., Daley, D., . . . Sonuga-Barke, E. J. (2016). Neurofeedback for attention-deficit/hyperactivity disorder: Meta-analysis of clinical and neuropsychological outcomes from randomized controlled trials. Journal of the American Academy of Child and Adolescent Psychiatry, 55(6), 444–455. doi:10.1016/ j.jaac.2016.03.007 Fazeli, M. S., Lin, Y., Nikoo, N., Jaggumantri, S., Collet, J. P., & Afshar, K. (2015). Biofeedback for nonneuropathic daytime voiding disorders in children:  A  systematic review and meta-analysis of randomized controlled trials. Journal of Urology, 193(1), 274–279. Fitz, F. F., Resende, A. P., Stüpp, L., Sartori, M. G., Girão, M. J., & Castro, R. A. (2012). Biofeedback for the treatment of female pelvic floor muscle dysfunction:  A  systematic review and metaanalysis. International Urogynecology Journal, 23(11), 1495–1516. Hammond, D.  C. (2011). What is neurofeedback: An update. Journal of Neurotherapy, 15(4), 305–336. Huang, T. L., & Charyton, C. (2008). A comprehensive review of the psychological effects of brainwave entrainment. Alternative Therapies in Health and Medicine, 14(5), 38–50. Nakao, M., Yano, E., Nomura, S., & Kuboki, T. (2003). Blood pressure-lowering effects of biofeedback treatment in hypertension:  A  metaanalysis of randomized controlled trials. Hypertension Research, 26(1), 37–46. Nestoriuc, Y., & Martin, A. (2007). Efficacy of biofeedback for migraine:  A  meta-analysis. Pain, 128(1–2), 111–127. Sielski, R., Rief, W., & Glombiewski, J. A. (2016). Efficacy of biofeedback in chronic back pain: A meta-analysis. International Journal of Behavioral Medicine, 10, 162–173. doi:10.1007/ s12529-016-9572-9 Tang, H. Y., Riegel, B., McCurry, S. M., & Vitiello, M. V. (2016). Open-loop audio-visual stimulation (AVS):  A  useful tool for management of insomnia? Applied Psychophysiology and Biofeedback, 41(1), 39–46. Woodford, H., & Price, C. (2007). EMG biofeedback for the recovery of motor function after

stroke. Cochrane Database of Systematic Reviews, 2007(2), CD004585. doi:10.1002/14651858 .CD004585.pub2

BOYKIN AND SCHOENHOFER: NURSING AS CARING THEORY Caring is a distinct feature of nursing practice. Caring theories inform and guide nursing practice. Multiple theories of caring exist, including the theory of culture care (Leininger, 1985), the theory on caring (Roach, 2002), and the theory of human caring (Watson, 1979, 1985, 2008). Each of these theories is grounded in different disciplines with many concepts borrowed and applied to nursing with each building on and complementing the other. The theory of Nursing as Caring developed by Anne Boykin and Savina Schoenhofer builds on the work of Leininger, Roach, and Watson. Boykin and Schoenhoefer (1993) posit that all persons are caring. Caring for persons is a value that underlies each of the major ideas in Nursing as Caring theory, and is essential for understanding this theory and its implications. Caring as a theory, much like the nursing profession, has evolved since its historical beginning. As the nursing profession evolved, it struggled to identify what caring is and the way it defines nursing (Trafecanty, 2006). Confusion in defining caring was seen in the nursing literature as late as the 1950s, only to be explicated later as a theory and as a building block of nursing (Swanson, 1999). The discovery of scientific medicine, technological advances, and the education of nurses to treat symptoms was the impetus for the development of this theory (Boykin & Schoenhofer, 1993). Boykin and Schoenhofer’s (1993) theory is unique and nontraditional in that it does not follow any mathematical formula using concepts, definitions, statements, and propositions. This theory is grounded in

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nursing and liberates it from a medical model. It is born in nursing practice and is intended as a framework for practice in the real world of nursing. The theory was not designed to reach the end goal of health and wellness like many nursing theories, but rather to create a unique way of living caring in the world (Boykin & Schoenhoefer, 1993). The nurse is always living as a caring person; always a nurse. When a person in the role of a nurse offers nursing service to another, such a service is called caring (Boykin & Schoenhoefer, 1993). Underlying their theory, Boykin and Schoenhoefer (1993, p. 30) asserted these major assumptions: • Persons are caring by virtue of their humanness. • Persons are caring moment to moment. • Persons are whole and complete in the moment. • Personhood is the process of living grounded in caring. • Personhood is enhanced through participating in nurturing relationships with caring others. • Nursing is both a discipline and a profession. Based on these suppositions, all human beings are considered caring although not every human act is caring (Boykin & Schoenhofer, 1993). Although the act may seem uncaring, the person remains caring. The expression of caring varies in the moment, develops over time, and is a lifelong process (Boykin & Schoenhofer, 1998). Being whole and complete in the moment means that there are no inadequacies or deficits in a person that needs correction as proposed in the nursing process. Boykin and Schoehofer’s (1998) theory is not concerned with symptom management or diagnosis of a problem. There is no need for intervention or healing. In caring, the person is taken at face value and does not have to prove himself or herself as a caring being. Personhood allows the person to live out his or her life caring in the

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moment. This is enhanced by participating in nurturing relationships with caring people. The theory of Nursing as Caring further defends nursing as both a discipline and a profession. As a discipline nursing responds to the social call of nursing, whereas as a profession it recognizes this call and uses scientific knowledge to create the necessary caring response of nurses. One of the rubrics of the theory of Nursing as Caring is that all nursing knowledge emerges from within the nursing situation (Schoenhoefer, 2002). The nursing situation is the lived experience between the nurse and the person nursed, in which the nurse comes to know the person as caring and living caring. Boykin and Schoenhofer (1993) assert that the nurse enters the world of the person in order to come to know the person as caring and with intent; that is a commitment and a choice. It explains the relationship between the nurse and the patient, which is a personal connection between the two. The nurse responds to the patient by acknowledging and creating caring responses that nurture the person. The lived experience allows the story of nursing to unfold, be told, and shared. Each nursing situation is unique just as each patient is unique. From the assumptions used in the theory of Nursing as Caring, the model for being in relationships resembles a dance of caring persons (Boykin & Schoenhofer, 1993). The image of a dancing circle also called the dance of nursing describes being with the nursed (Boykin & Schoenhoefer, 1993). Each person is caring and each person's role is essential in contributing to the process of living grounded caring. Each dancer makes a special contribution to the dance. The dancers may or may not hold hands and there is always room for more to join the circle. There are no power distinctions or position hierarchies in this circle (Boykin, Bulfin, Baldwin, & Southern, 2004). The nursed call on different dancers (health care professionals) at various points in time, demonstrating that no one person’s role is any more or less important

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than another’s. The power of the dance is most fully recognized when people work as a team. The uniqueness of this nursing theory transcends nursing practice, nursing administration, and nursing education in very practical ways. Nurse faculty, nurse researchers, graduate nursing students, hospital and health care administrators use Nursing as Caring theory to provide a foundation for teaching, research, and practice (Bulfin, 2005). For example, Bulfin (2005) described the application of this theory to a model of practice in a community hospital. The results confirmed that as a result of this model patient satisfaction increased dramatically and the staff felt appreciated when they were acknowledged as caring. In line with this research, Duffy (2005) studied the competency of caring in baccalaureate nursing students. The reported conclusions indicate that there was a moderate degree of self-reported caring. Locsin (1998) used Nursing as Caring theory to develop the middle range theory technological competence of caring. This theory focuses on using technology in critical care as nurses come to know their patient fully and completely (Locsin, 1998). There is an increasing focus on task completion, technical innovations, best business practices, and patient outcomes in nursing practice. Consequently, nursing leaders’ attention and staff behaviors are not always focused on caring practices and the moral and economic value of caring (Felgen, 2003). In addition, the onset of a looming nursing shortage, an increasing dissatisfaction with the health care system, a changing health care system enacted by the federal government, and reports of poor patient outcomes also shift the focus from caring (Watson, 2009). Boykin, Schoenhofer, Smith, St. Jean, and Aleman (2003) report patient outcomes encompass patient’s experiences as having received respectful, compassionate, and competent care. Boykin and Schoenhofer (1998) submit that the nursing profession must know clearly what the value of caring is in the

health care setting. They propose that caring in nursing must be paid for even though it cannot be bought (Boykin & Schoenhofer, 1998). Further research will test this theory leading to practice changes, enhance quality outcomes for patients, and spur the development of additional middle range theories.

Theresa Bucco Boykin, A., Bulfin, S., Baldwin, J., & Southern, R. (2004). Transforming care in the emergency department. Topics in Emergency Medicine, 26(4), 331–336. Boykin, A., & Schoenhofer, S. O. (1993). Nursing as caring: A model for transforming practice. Boston, MA: Jones & Bartlett/National League for Nursing. Bulfin, S. (2005). Nursing as caring theory: Living caring in practice. Nursing Science Quarterly, 18(4), 313–319. Duffy, J. (2005). Assessing nursing students’ caring competencies. In M. H. Oermann & K. T. Heinrich (Eds.), Annual review of nursing education (Vol. 3, pp. 59–76). New York, NY: Springer Publishing. Locsin, R. C. (1998). Technologic competence as caring in critical care nursing. Holistic Nursing Practice, 12(4), 50–56.

BREASTFEEDING Breastfeeding provides nutritional, immunological, cognitive, and psychological benefits for young children and is important to the health of women, families, and society. A burgeoning body of research has identified the unique properties and the unreplaceable living tissue transferred to infants and children through breastfeeding and its effect on health outcomes. As global health care systems begin to face the reality of increasing costs related to chronic health conditions and recognize the positive health benefits of breastfeeding, more countries are promoting and supporting breastfeeding families. The

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economic benefits may be just as staggering. Economic analyses approximate $302 billion in losses from not breastfeeding, or 0.49% of the world gross national income (WGNI; Rollins et al., 2016). As frontline practitioners in acute, clinic, and public health locations, nurses are very involved in the research and evidence-based practices (EBPs) that promote and support breastfeeding. National and international policies and recommendations from nongovernmental organizations, national governments, and medical organizations have been developed on the basis of compelling research and include the U.S. Department of Health and Human Services (2016) Healthy People 2020, setting national health objectives to identify significant threats to health and to seek health equity; the U.S. surgeon general’s “Blueprint for Action on Breastfeeding” (Satcher, 2001), and the World Health Organization’s Global Strategy for Infant and Young Child Feeding (World Health Organization/United Nations Children’s Fund, 2003). Advent of the Baby Friendly Hospital Initiative (BFHI; Abrahams & Labbok, 2009) and the Neo-BFHI (Nyqvist et al., 2012, 2013) has suffered from a lack of uptake in key nations (Atchan, Davis, & Foureur, 2013) and has not had the overall expected effect. Nurses and nurse researchers can play a key role in this area. Systematic review of instruments measuring the nurses’ translation of EBP (Leung, Trevena, & Waters, 2014) found that the instrument assessing the highest validity relied entirely on self-report and a performance-based instrument measuring knowledge, skills, and attitudes is needed. An evidence-based clinical practice guideline, available in Breastfeeding Support: Preconception Care Through the First Year, is a valuable resource for all nurses (Association of Women’s Health, 2015). A report from the Agency for Healthcare Quality and Research screened 9,000 studies in developed countries with a meta-analysis of the health impact of breastfeeding on infants and women (Ip et al., 2007). According to this report, infants who are breastfed had

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a reduced risk of acute otitis media, atopic dermatitis, gastrointestinal infections, lower respiratory tract disease, asthma, obesity, type 2 diabetes, childhood leukemia, and sudden infant death syndrome (SIDS). Mothers who breastfed had a reduced risk of type 2 diabetes, breast cancer, and ovarian cancer (Ip et al., 2007). More recent research has found reduced dental caries in breastfed infants (Avila, Pordeus, Paiva, & Martins, 2015) and decreased risks of ovarian cancer related to the duration of breastfeeding (Feng, Chen, & Shen, 2014) as well as protection from breast cancer when mother is a nonsmoker (González-Jiménez, García, Aguilar, Padilla, & Álvarez, 2014). As mentioned previously, the focus on premature birth and breastfeeding in the neonatal intensive care unit (NICU) has led to the development of the Neo-BFHI used in Sweden, Brazil, and in some areas of the United States and Canada. The focus on mother–baby care and the nurse’s role as a facilitator in supporting parents through skin-to-skin kangaroo mother care (KMC) and breastfeeding has led to the nursing research in this area, including the role of NICU peer counselors (Rossman, Greene, & Meier, 2015), mothers’ proximity, and KMC resulting in an increased milk volume in mothers with very low-birth-weight (VLBW) infants (Acuña-Muga et al., 2014); and the way mothers maintain breastfeeding of preterm infants (Rodrigues et al., 2013). The research in Canada is exploring the effect of skin-to-skin KMC and breastfeeding for pain management in neonates (Harrison et al., 2015). Historically, a large discrepancy exists in breastfeeding rates according to the social determinants of health, including income, education, race, and ethnicity—nursing research continues to focus on meeting the needs of vulnerable populations, recognizing that the continuity of care and support systems, including health care professional support, play a large role in women’s success in breastfeeding for their intended duration. The researchers examined structured

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versus nonstructured breastfeeding programs to support initiation and duration of breastfeeding in acute and primary care sites (Beake, Pellowe, Dykes, Schmied, & Bick, 2012), whereas others examined the intergenerational effect on breastfeeding initiation and duration (Di Manno, Macdonald, & Knight, 2015); a meta-analysis of the timing and exclusivity of breastfeeding reported that early initiation (first hour of life) and exclusive breastfeeding for the first month were associated with reduced risk of neonatal mortality and infection-related deaths, including lower risk of sepsis, diarrhea, and respiratory infections (Khan, Vesel, Bahl, & Martines, 2015). The other major areas studied by nurse scholars include breastfeeding interventions (Ahmed & Sands, 2010; Pate, 2009; Spiby et al., 2009; A. L. Watkins & Dodgson, 2010), support for breastfeeding mothers (Declercq, Labbok, Sakala, & O’Hara, 2009), effect of pacifier use (Declercq et al., 2009; Kronborg & Vaeth, 2009), effect of the BFHI on breastfeeding (Bartick, Stuebe, Shealy, Walker, & Grummer-Strawn, 2009), postpartum depression’s effect on infant feeding (Accortt, Cheadle, & Dunkel Schetter, 2015; Donaldson-Myles, 2011; S. Watkins, Meltzer-Brody, Zolnoun, & Stuebe, 2011), and weight management interventions in postpartum and breastfeeding mothers (Neville, McKinley, Holmes, Spence, & Woodside, 2014). Nurses need updated education on the basis of research to provide support to breastfeeding mothers at critical times, starting in prelicensure programs focusing on advocacy and patient education (Bozzette & Posner, 2013; Vandewark, 2014) and to identify women at risk for complications early on. For example, a meta-analysis found the effects of prenatal depression on low birth weight (LBW) are more consistent than effects on length of gestation or preterm birth (Accortt et al., 2015), so that interventions can be initiated and referrals made in a timely fashion to preserve the breastfeeding relationship.

Nurses need to be aware of new developments in breastfeeding in areas such as breast reduction/augmentation surgery (Schiff, Algert, Ampt, Sywak, & Roberts, 2014; Thibaudeau, Sinno, & Williams, 2010), HIV status (Jackson, Goga, Doherty, & Chopra, 2009), and psychotropic drug use during breastfeeding (Fortinguerra, Clavenna, & Bonati, 2009). Careful assessment of the benefits and risks of not breastfeeding should be in the forefront of nursing research. In addition, new growth charts provide more accurate data on breastfeeding infants’ expected growth patterns, and clinicians have new resources in planning their care (Vesel et al., 2010), although connections to the decreased risk of obesity are difficult to prove given confounding variables (Lefebvre & John, 2014). There is continued conflicting evidence of the health care professional’s role as an advocate, informer (risk–benefit), and supporter whether a woman continues to breastfeed or not (Larsen & Kronborg, 2013), and the important role of other health professionals, for example, pharmacists (Edwards, 2014) and their knowledge, attitudes, and practices. Nurse scientists continue to use different methodologies to study breastfeeding and to identify some of the reasons for discrepancies in initiation, duration, and support, including ethnographies, phenomenological studies, historical–cultural approaches, and ecological perspectives. Theoretical frameworks used to explore the health behavior of breastfeeding include the theory of planned behavior, the health belief model, the social cognitive theory using the concept of self-efficacy, and the social-ecological frameworks. Nurses have conducted many meta-analyses of both quantitative and qualitative research in the area of breastfeeding. Researchers have demonstrated the importance of peer and social support, the effect of hospital interventions, the need for comprehensive breastfeeding education and support, the communication-related barriers, the socioeconomic issues, the effect of values and

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practice, and most important the culturally relevant issues that influence infant-feeding choices. The more recent research is taking a hard look at social determinants of health and interventions that target meeting the needs of vulnerable populations. The influence of the health care delivery system, community, and society/culture cannot be ignored and aspects of the social determinants of health that have led to disparities in success with breastfeeding continue to be recognized. In addition, nurses are leading and participating collaboratively in interdisciplinary teams that lead to rich research and knowledge dissemination. Challenges related to the study of breastfeeding include three major areas: the lack of consistency in the definition of breastfeeding (e.g., exclusivity) that makes comparison of studies tedious if not impossible, the difficulty in measuring cross-cultural effects (lack of reliability and validity studies of major breastfeeding instruments with various cultures), and the development of prospective designs and randomized controlled trials. We have made strides with meta-analyses, more theory-focused research, and a better effort at defining breastfeeding and separating out the effects of exclusivity. Some systematic reviews of areas that are not yet mentioned include lesbian, gay, bisexual, transgender, queer or questioning, and intersex (LGBTQI) populations (Farrow, 2015); vitamin D supplementation for breastfed infants (Thiele, Senti, & Anderson, 2013); adolescents (Sipsma, Jones, & Cole-Lewis, 2015); mastitis (Amir, 2014); herbal/galactogogue efficacy (Mortel & Mehta, 2013); workplace breastfeeding (Anderson et al., 2015; Atabay et al., 2015); and breast reduction and impact of cosmetic breast implants (Schiff et al., 2014; Thibaudeau et al., 2010). Although breastfeeding is now recognized as a right of mothers, a health care behavior contributing to the reduction of infant and maternal morbidity and mortality rates, less expensive than artificial milk supplementation and more environmentally

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friendly, the national/global breastfeeding goals are far from being met. A cost analysis demonstrated that if 90% of U.S. families with children were successful at exclusively breastfeeding for 6 months, the cost saving would be $13 billion per year (Bartick & Reinhold, 2010).

Suzanne Hetzel Campbell

Abrahams, S. W., & Labbok, M. H. (2009). Exploring the impact of the Baby-Friendly Hospital Initiative on trends in exclusive breastfeeding. International Breastfeeding Journal, 4, 11. Accortt, E. E., Cheadle, A. C., & Dunkel Schetter, C. (2015). Prenatal depression and adverse birth outcomes:  An updated systematic review. Maternal and Child Health Journal, 19(6), 1306–1337. Acuña-Muga, J., Ureta-Velasco, N., de la CruzBértolo, J., Ballesteros-López, R., SánchezMartínez, R., Miranda-Casabona, E., & Pallás-Alonso, C.  (2014). Volume of milk obtained in relation to location and circumstances of expression in mothers of very low birth weight infants. Journal of Human Lactation, 30(1), 41–46. doi:10.1177/0890334413509140 Ahmed, A. H., & Sands, L. P. (2010). Effect of pre- and postdischarge interventions on breastfeeding outcomes and weight gain among premature infants. Journal of Obstetric Gynecologic, & Neonatal Nursing, 39(1), 53–63. Amir, L. H.; Academy of Breastfeeding Medicine Protocol Committee. (2014). ABM clinical protocol #4:  Mastitis, revised March 2014. Breastfeeding Medicine, 9(5), 239–243. Anderson, J., Kuehl, R. A., Drury, S. A., Tschetter, L., Schwaegerl, M., Hildreth, M., . . . Lamp, J. (2015). Policies aren’t enough: The importance of interpersonal communication about workplace breastfeeding support. Journal of Human Lactation, 31(2), 260–266. Association of Women’s Health, Obstetrical, and Neonatal Nursing. (2015). Breastfeeding support:  Preconception care through the first year. Evidence-based clinical practice guideline (3rd ed.). Washington, DC: Author. Atabay, E., Moreno, G., Nandi, A., Kranz, G., Vincent, I., Assi, T.-M., . . . Heymann, S. J. (2015). Facilitating working mothers’ ability to breastfeed: Global trends in guaranteeing

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breastfeeding breaks at work, 1995–2014. Journal of Human Lactation, 31(1), 81–88. Atchan, M., Davis, D., & Foureur, M. (2013). The impact of the Baby Friendly Health Initiative in the Australian health care system: A critical narrative review of the evidence. Breastfeeding Review, 21(2), 15–22. Avila, W. M., Pordeus, I. A., Paiva, S. M., & Martins, C. C. (2015). Breast and bottle feeding as risk factors for dental caries:  A  systematic review and meta-analysis. PLoS One, 10(11), e0142922. Bartick, M., & Reinhold, A. (2010). The burden of suboptimal breastfeeding in the United States:  A  pediatric cost analysis. Pediatrics, 125(5), e1048–e1056. Bartick, M., Stuebe, A., Shealy, K. R., Walker, M., & Grummer-Strawn, L. M. (2009). Closing the quality gap: Promoting evidence-based breastfeeding care in the hospital. Pediatrics, 124(4), e793–e802. Beake, S., Pellowe, C., Dykes, F., Schmied, V., & Bick, D. (2012). A systematic review of structured compared with non-structured breastfeeding programmes to support the initiation and duration of exclusive and any breastfeeding in acute and primary health care settings. Maternal & Child Nutrition, 8(2), 141–161. Bozzette, M., & Posner, T. (2013). Increasing student nurses’ knowledge of breastfeeding in baccalaureate education. Nurse Education in Practice, 13(3), 228–233. Declercq, E., Labbok, M. H., Sakala, C., & O’Hara, M. (2009). Hospital practices and women’s likelihood of fulfilling their intention to exclusively breastfeed. American Journal of Public Health, 99(5), 929–935. Di Manno, L., Macdonald, J. A., & Knight, T. (2015). The intergenerational continuity of breastfeeding intention, initiation, and duration:  A  systematic review. Birth, 42(1), 5–15. Donaldson-Myles, F.  (2011). Postnatal depression and infant feeding:  A  review of the evidence. British Journal of Midwifery, 19(10), 614–624. doi:10.12968/bjom.2011.19.10.619 Edwards, R. A. (2014). Pharmacists as an underutilized resource for improving community-level support of breastfeeding. Journal of Human Lactation, 30(1), 14–19. Farrow, A. (2015). Lactation support and the LGBTQI community. Journal of Human Lactation, 31(1), 26–28.

Feng, L. P., Chen, H. L., & Shen, M. Y. (2014). Breastfeeding and the risk of ovarian cancer:  A  meta-analysis. Journal of Midwifery & Women’s Health, 59(4), 428–437. Fortinguerra, F., Clavenna, A., & Bonati, M. (2009). Psychotropic drug use during breastfeeding: A review of the evidence. Pediatrics, 124(4), e547–e556. González-Jiménez, E., García, P. A., Aguilar, M. J., Padilla, C. A., & Álvarez, J. (2014). Breastfeeding and the prevention of breast cancer:  A  retrospective review of clinical histories. Journal of Clinical Nursing, 23(17–18), 2397–2403. Harrison, D., Reszel, J., Wilding, J., Abdulla, K., Bueno, M., Campbell-Yeo, M., . . . Stevens, B. (2015). Neuroprotective core measure 5: Minimizing stress and pain—Neonatal pain management practices during heel lance and venipuncture in Ontario, Canada. Newborn and Infant Nursing Reviews, 15, 116–123. doi: 10.1053/j.nainr.2015.06.010 Ip, S. C. M., Raman, G., Chew, P., Magula, N., DeVine, D., Trikalinos, T., & Lau, J. (2007). Breastfeeding and maternal and infant health outcomes in developed countries. Evidence report/technology assessment No. 153 (AHRQ Publication No. 07-E007). Rockville, MD: Tufts-New England Medical Center Evidence-Based Practice Center. Jackson, D. J., Goga, A. E., Doherty, T., & Chopra, M. (2009). An update on HIV and infant feeding issues in developed and developing countries. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 38(2), 219–229. Khan, J., Vesel, L., Bahl, R., & Martines, J. C. (2015). Timing of breastfeeding initiation and exclusivity of breastfeeding during the first month of life:  Effects on neonatal mortality and morbidity—A systematic review and metaanalysis. Maternal & Child Health Journal, 19(3), 468–479. Kronborg, H., & Vaeth, M. (2009). How are effective breastfeeding technique and pacifier use related to breastfeeding problems and breastfeeding duration? Birth, 36(1), 34–42. Larsen, J. S., & Kronborg, H. (2013). When breastfeeding is unsuccessful—Mothers’ experiences after giving up breastfeeding. Scandinavian Journal of Caring Sciences, 27(4), 848–856. Lefebvre, C. M., & John, R. M. (2014). The effect of breastfeeding on childhood overweight

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and obesity: A systematic review of the literature. Journal of the American Association of Nurse Practitioners, 26(7), 386–401. Leung, K., Trevena, L., & Waters, D. (2014). Systematic review of instruments for measuring nurses’ knowledge, skills and attitudes for evidence-based practice. Journal of Advanced Nursing, 70(10), 2181–2195. Mortel, M., & Mehta, S. D. (2013). Systematic review of the efficacy of herbal galactogogues. Journal of Human Lactation, 29(2), 154–162. Neville, C. E., McKinley, M. C., Holmes, V. A., Spence, D., & Woodside, J. V. (2014). The effectiveness of weight management interventions in breastfeeding women—A systematic review and critical evaluation. Birth, 41(3), 223–236. Nyqvist, K. H., Häggkvist, A. P., Hansen, M. N., Kylberg, E., Frandsen, A. L., Maastrup, R., . . . Haiek, L. N. (2012). Expansion of the ten steps to successful breastfeeding into neonatal intensive care: Expert group recommendations for three guiding principles. Journal of Human Lactation, 28(3), 289–296. Nyqvist, K. H., Häggkvist, A. P., Hansen, M. N., Kylberg, E., Frandsen, A. L., Maastrup, R., . . . Haiek, L. N.; Baby-Friendly Hospital Initiative Expert Group. (2013). Expansion of the babyfriendly hospital initiative ten steps to successful breastfeeding into neonatal intensive care: Expert group recommendations. Journal of Human Lactation, 29(3), 300–309. Pate, B. (2009). A systematic review of the effectiveness of breastfeeding intervention delivery methods. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 38(6), 642–653. Rodrigues, A. P., Martins, E. L., Trojahn, T. C., de Mello Padoin, S. M., de Paula, C. C., & Tronco, C.  S. (2013). Maintaining the breastfeeding of preterm newborns:  An integrative literature review. Revista Eletronica de Enfermagem, 15(1), 253–264. doi:10.5216/ree.v15i1.17067 Rollins, N. C., Bhandari, N., Hajeebhoy, N., Horton, S., Lutter, C. K., Martines, J. C., . . .  Victora, C. G.; Lancet Breastfeeding Series Group. (2016). Why invest, and what it will take to improve breastfeeding practices? Lancet, 387(10017), 491–504. Rossman, B., Greene, M. M., & Meier, P. P. (2015). The role of peer support in the development of maternal identity for “NICU Moms.” Journal of Obstetric, Gynecologic, & Neonatal Nursing, 44(1), 3–16.

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Satcher, D. S. (2001). DHHS blueprint for action on breastfeeding. Public Health Reports, 116(1), 72–73. Schiff, M., Algert, C. S., Ampt, A., Sywak, M. S., & Roberts, C. L. (2014). The impact of cosmetic breast implants on breastfeeding:  A  systematic review and meta-analysis. International Breastfeeding Journal, 9, 17. Sipsma, H. L., Jones, K. L., & Cole-Lewis, H. (2015). Breastfeeding among adolescent mothers:  A  systematic review of interventions from high-income countries. Journal of Human Lactation, 31(2), 221–229; quiz 321. Spiby, H., McCormick, F., Wallace, L., Renfrew, M. J., D’Souza, L., & Dyson, L. (2009). A systematic review of education and evidence-based practice interventions with health professionals and breast feeding counsellors on duration of breast feeding. Midwifery, 25(1), 50–61. Thibaudeau, S., Sinno, H., & Williams, B. (2010). The effects of breast reduction on successful breastfeeding: A systematic review. Journal of Plastic, Reconstructive & Aesthetic Surgery, 63(10), 1688–1693. doi:10.1016/j.bjps .2009.07.027 Thiele, D. K., Senti, J. L., & Anderson, C. M. (2013). Maternal vitamin D supplementation to meet the needs of the breastfed infant:  A  systematic review. Journal of Human Lactation, 29(2), 163–170. U.S. Department of Health and Human Services. (2011). The surgeon general’s call to action to support breastfeeding. Retrieved from http:// www.surgeongeneral.gov/ library/ calls/ breastfeeding/ calltoactiontosupportbreast feeding.pdf U.S. Department of Health and Human Services. (2016). Healthy People 2020. Retrieved from http:// www.hhs.gov/ ash/ oah/ resources -and-publications/healthy-people-2020.html Vandewark, A. C. (2014). Breastfeeding attitudes and knowledge in bachelor of science in nursing candidates. Journal of Perinatal Education, 23(3), 135–141. Vesel, L., Bahl, R., Martines, J., Penny, M., Bhandari, N., Kirkwood, B. R.; WHO Immunizationlinked Vitamin A  Supplementation Study Group. (2010). Use of new World Health Organization child growth standards to assess how infant malnutrition relates to breastfeeding and mortality. Bulletin of the World Health Organization, 88(1), 39–48.

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Watkins, A. L., & Dodgson, J. E. (2010). Breastfeeding educational interventions for health professionals: A synthesis of intervention studies. Journal for Specialists in Pediatric Nursing, 15(3), 223–232. Watkins, S., Meltzer-Brody, S., Zolnoun, D., & Stuebe, A. (2011). Early breastfeeding

experiences and postpartum depression. Obstetrics & Gynecology, 118(2, Pt. 1), 214–221. World Health Organization/United Nations Children’s Fund. (2003). Global strategy for infant and young child feeding. In Infant and young child nutrition. Retrieved from http://www.who.int/ nutrition/topics/global_strategy/en

C CANCER IN CHILDREN Pediatric oncology represents only a small fraction of the discipline of oncology and makes up less than 1% of all cancers diagnosed each year. Approximately 10,380 children in the United States younger than 15 years will be diagnosed with cancer in 2016 (American Cancer Society, 2016). Major treatment advances in recent decades have resulted in more than 80% of children with cancer now surviving 5 years or more. This is a tremendous increase since the mid-1970s, when the 5-year survival rate was around 50%. Still, survival rates vary depending on the type of cancer and other factors. Although relatively rare, childhood cancer continues to cause considerable morbidity among those affected and remains the second leading cause of death after accidents in children aged 1 to 14 years. For children of all ages, leukemia is the most frequent type of cancer, followed by brain tumors and lymphomas. Tumors of the kidney are more common in African Americans, whereas tumors of the brain and bone are more common in Caucasians. The cause of most childhood cancers remains unknown. Despite this lack of knowledge about the origin of most cancers, there is increasing information on risk factors that increase the likelihood of children developing cancer. About 5% of all cancers in children are caused by an inherited mutation (a genetic mutation that can be passed from parents to their children). For example, children with retinoblastoma, Wilms tumor, and neuroblastoma demonstrate patterns of inheritance

that suggest a genetic basis for the disorder. Genetic abnormalities have been found in acute leukemia (Yokota & Kanakura, 2016) and lymphoma as well as other pediatric solid tumors. Wilms tumor is associated with an increased incidence of congenital anomalies. Children with syndromes caused by abnormal numbers of chromosomes (e.g., Down syndrome) have a significantly increased incidence of cancer (Mateos, Barbaric, Byatt, Sutton, & Marshall, 2015). Children with immune deficiencies are at a greater risk of developing cancer. Some viruses have been linked to childhood cancer, such as hepatitis B virus associated with hepatocellular cancer in children and Epstein–Barr virus associated with the development of lymphoma. The major focus of pediatric oncology nursing research includes symptom assessment and management, quality-of-life, and long-term survivorship issues. Although increased attention on nursing research has occurred over the past 10 years, many areas of pediatric oncology nursing have yet to be explored. There is a significant need for further clinical research among pediatric oncology patients of various socioeconomic backgrounds, cultural diversity, and specific developmental ages. Incorporating the pediatric patient as an active participant is an important consideration for research studies and patient-reported outcomes (PROs) are becoming an expectation of many studies. In an effort to increase PROs, the National Institutes of Health funded the Patient Reported Outcomes Measurement Information Systems (PROMIS) pediatric initiative to validate self-reported measures in children and adolescents with chronic illnesses. The use of PROMIS measures can identify common data

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elements within pediatric oncology and also allow for comparison with other pediatric chronic illnesses. Although self-report is the standard for measuring outcomes in patients, young children who are preverbal rely on parent-proxy reporting. Despite this option, children with cancer who are younger than 5 years are often excluded from studies and little is known about their experiences during cancer treatment. Symptom assessment has been a focus of pediatric oncology nursing research for many years. Fatigue, pain, sleep disturbances, depression, nausea, and vomiting frequently occur in children and adolescents with cancer and are the most common variables in pediatric oncology research (Rodgers, Hooke, & Hockenberry, 2013). A number of descriptive and cross-sectional studies have reported multiple symptoms in pediatric oncology patients, but only a few studies have identified symptom patterns over time. A longitudinal study of 20 adolescents with cancer found that fatigue peaked immediately after the administration of chemotherapy and then gradually declined until the next chemotherapy cycle but never completely resolved during multiple courses of chemotherapy (Erickson et al., 2010). Symptom cluster is another area of limited knowledge and research within pediatric oncology. A study of 67 children and adolescents showed fatigue, sleep disturbance, and nausea and vomiting clustered together and, when present, caused more depressive symptoms and behavior changes among adolescents after chemotherapy (Hockenberry et al., 2010). There is great potential to advance symptom science by evaluating symptom interactions as well as changes in symptom severity over time. Efforts to manage symptoms of cancer and its treatments have not kept pace with new advances in the causes and cures for cancer. Areas of symptom-management research in pediatric oncology are primarily limited to descriptive studies. Nonpharmacological interventions, such as acupuncture, hypnosis, distraction, and imagery, have been shown to be effective in relieving nausea, vomiting,

pain, and anxiety in children undergoing cancer treatment (Rheingans, 2007; Yeh et al., 2012). Systematic reviews have summarized best practices and clinical guidelines to treat symptoms, such as nausea, vomiting, and insomnia in children undergoing cancer treatment (Dupuis et al., 2013; Walter, Nixon, Davey, Downie, & Horne, 2015). Surprisingly, the use of technology for symptom management among pediatric oncology patients is limited. A mobile phone-based application, ASyMS, determines whether a call from a health care provider or a self-care message is warranted based on the reported symptom severity. A pilot study of 25 adolescents revealed that participants liked the system and found it simple to use (Gibson et al., 2010). More research is needed to expand the use of technology for symptom management, especially among children and adolescents, who are very accustomed to using it. As survival for childhood cancer continues to improve, nursing investigations are focusing on survivorship issues and quality of life after the diagnosis and treatment of cancer. A  review of childhood cancer survivor studies showed that childhood cancer survivors who underwent radiation therapy reported more psychological distress, those who underwent chemotherapy treatment with anthracyclines or alkylating agents experienced more physical impairments, and those who had limb-sparing procedures reported more anxiety and more functional impairment than those who had an amputation (Zeltzer et  al., 2009). Childhood cancer survivor studies have also documented the adverse effects of the central nervous system treatment on cognitive, academic, and psychosocial functioning. Interventions designed to minimize the adverse effects of central nervous system therapy are being conducted. It is evident from the recent childhood cancer literature that there is still much to be gained from continued research. The importance of striving for symptom relief in children cannot be overemphasized. Recognition and

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acknowledgment of the beliefs and expectations of children and their parents regarding cancer-related symptoms should continue to be a major research focus. Longitudinal studies evaluating the trajectory of symptom occurrence and symptom management over time are not found. Continued exploration of the most effective management and coping strategies should be pursued for children experiencing all types of cancer or treatmentrelated symptoms. Finally, the use of research findings in the clinical setting is lacking. More innovative, creative methods for dissemination of our knowledge of symptom occurrence and symptom management must be explored. Evaluating feasibility and fidelity along with the effectiveness of an intervention during a study will allow for a more successful transition to real-life settings. Designing and maintaining joint research relationships with other disciplines are essential to facilitate the development of scientific credibility of nurse-initiated protocols and pediatric oncology nurse investigator studies.

Marilyn Hockenberry Cheryl Rodgers

American Cancer Society. (2016). Key statistics for childhood cancer. Retrieved from https://www.cancer.org Dupuis, L. L., Boodhan, S., Holdsworth, M., Robinson, P. D., Hain, R., Portwine, C., . . . Sung, L.; Pediatric Oncology Group of Ontario. (2013). Guideline for the prevention of acute nausea and vomiting due to antineoplastic medication in pediatric cancer patients. Pediatric Blood Cancer, 60(7), 1073–1082. Erickson, J. M., Beck, S. L., Christian, B., Dudley, W. N., Hollen, P., Albritton, K., . . . Godder, K. (2010). Patterns of fatigue in adolescents receiving chemotherapy. Oncology Nursing Forum, 37(4), 444–455. Gibson, F., Aldiss, S., Taylor, R. M., Maguire, R., McCann, L., Sage, M., & Kearney, N. (2010). Utilization of the Medical Research Council evaluation framework in the development of technology for symptom management: The ASyMS-YG Study. Cancer Nursing, 33(5), 343–352.

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Hockenberry, M. J., Hooke, M. C., Gregurich, M., McCarthy, K., Sambuco, G., & Krull, K. (2010). Symptom clusters in children and adolescents receiving cisplatin, doxorubicin, or ifosfamide. Oncology Nursing Forum, 37(1), E16–E27. Mateos, M. K., Barbaric, D., Byatt, S. A., Sutton, R., & Marshall, G. M. (2015). Down syndrome and leukemia:  Insights into leukemogenesis and translational targets. Translational Pediatrics, 4(2), 76–92. Rheingans, J. I. (2007). A systematic review of nonpharmacologic adjunctive therapies for symptom management in children with cancer. Journal of Pediatric Oncology Nursing, 24(2), 81–94. Rodgers, C. C., Hooke, M. C., & Hockenberry, M. J. (2013). Symptom clusters in children. Current Opinion in Supportive and Palliative Care, 7(1), 67–72. Walter, L. M., Nixon, G. M., Davey, M. J., Downie, P. A., & Horne, R. S. (2015). Sleep and fatigue in pediatric oncology: A review of the literature. Sleep Medicine Reviews, 24, 71–82. Yeh, C. H., Chien, L. C., Chiang, Y. C., Lin, S. W., Huang, C. K., & Ren, D. (2012). Reduction in nausea and vomiting in children undergoing cancer chemotherapy by either appropriate or sham auricular acupuncture points with standard care. Journal of Alternative and Complementary Medicine, 18(4), 334–340. Yokota, T., & Kanakura, Y. (2016). Genetic abnormalities associated with acute lymphoblastic leukemia. Cancer Science, 107(6), 721–725. Zeltzer, L. K., Recklitis, C., Buchbinder, D., Zebrack, B., Casillas, J., Tsao, J. C., & Krull, K. (2009). Psychological status in childhood cancer survivors: A report from the Childhood Cancer Survivor Study. Journal of Clinical Oncology, 27(14), 2396–2404.

CARDIOVASCULAR RISK FACTORS Cardiovascular disease (CVD) is a major cause of morbidity and mortality in men and women worldwide, including in both high- and low-income countries.

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Atherosclerotic-CVD processes begin early in life and are influenced over time by the interaction of genetic and potentially modifiable behaviors and multilevel environmental factors. Hypercholesterolemia—elevated serum total cholesterol (TC)—is recognized as a major risk factor for coronary heart disease (CHD). Low-density lipoprotein cholesterol (LDL-C), the major atherogenic lipoprotein, typically constitutes 60% to 70% of serum TC and has been a primary target of cholesterollowering therapy. In 1988, on the basis of available epidemiological and clinical data, the National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) issued the first guidelines for identifying and managing hypercholesterolemia in adults. Since that time, results of numerous randomized controlled trials (RCTs) confirmed that lowering LDL-C was important in the primary and secondary prevention of CHD. The most recent (2014) evidence-based guidelines issued by the American College of Cardiology (ACC) and the American Heart Association (AHA) on the treatment of blood cholesterol to reduce atherosclerotic CVD risk in adults differ from previous guidelines in several ways (Stone et al., 2014). Specific targets for LDL-C lowering were abandoned because the Expert ACC/ AHA Panel was unable to find RCT evidence to support continued use of specific LDLC or non-high-density lipoprotein (HDL-C) treatment targets. The panel did, however, find extensive RCT evidence supporting the use of appropriate intensity of 3-hydroxy3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase inhibitors (statins) to reduce atherosclerotic cardiovascular disease (ASCVD) risk in those most likely to benefit. Specifically, the 2014 guidelines highlight four major statin benefit groups for whom ASCVD risk reduction clearly outweighs the risk of adverse events: (a) individuals with documented clinical ASCVD who require aggressive risk-factor modification and intense lipid lowering for secondary prevention, (b) primary prevention in individuals with primary elevations of

LDL-C greater than or equal to 190 mg/dL, (c) primary prevention in individuals 40 to 75 years of age with diabetes (types 1 and 2) and with LDL-C 70 to 189 mg/dL, and (d) primary prevention in individuals without diabetes and with an estimated 10-year ASCVD risk of more than 7.5%. The 2014 guidelines also focus on the appropriate intensity of statin therapy. High-intensity statin therapy lowers LDL-C by more than 50% and is recommended for those with clinical ASCVD (secondary prevention), individuals with LDL-C levels that are greater than or equal to 190 mg/dL, and patients 40 to 75 years of age with diabetes and LDL-C 70 to 189 mg/dL and a 10-year ASCVD risk that is greater than or equal to 7.5%. Moderate-intensity statin therapy lowers LDL-C from 30% to 50% and is recommended for lower risk individuals with diabetes and for those with a 10-year ASCVD risk that is greater than or equal to 7.5% and intolerance to higher intensity therapy. Moderate-intensity statin therapy can also be used in other high-risk patients who are intolerant of high-intensity statins or who are older than 75 years of age. Of note and based on RCTs, the relative reduction in ASCVD events is similar across the range of LDL-C levels in the primary prevention groups. The Pooled Cohort Risk Calculator recommended to estimate the 10-year risk for ASCVD has been a topic of some controversy within the cardiovascular community with some data suggesting overemphasis on age and overestimation of risk particularly in the primary prevention population (Stone et al., 2014). The accumulated evidence, however, supports the use of statin therapy for higher risk individuals without clinical ASCVD demonstrating reductions in all-cause mortality, stroke, CHD, and fatal and nonfatal CVD. The 2014 guidelines emphasize the importance of clinical decision making in the application of guidelines to individual patients with consideration of patient preferences for treatment in addition to the estimated 10-year risk for ASCVD.

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Particularly noteworthy is the emphasis placed on the importance of patient–provider communication and the discussion of risks and benefits of statin therapy, risk for future ASCVD, and individually tailored strategies to reduce risk. Similar to previous guidelines, lifestyle modification is highlighted as a central component of CVD prevention and management. Detailed in the 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk (Eckel et al., 2014), emphasis is placed on adherence to a heart-healthy diet, regular exercise, avoidance of tobacco products, and maintenance of a healthy body weight. Viewed as a critical component of cardiovascular health promotion and ASCVD reduction across the life course, the 2014 guidelines recommend lifestyle modification both before and in concert with the use of cholesterol-lowering drug therapies. Consistent with recommendations of the 33rd Bethesda Conference on preventive cardiology (Ockene, Hayman, Pasternak, Schron, & Dunbar-Jacob, 2002), the 2014 guidelines identify and target adherence-enhancing interventions that consider the characteristics of the individual patient, the provider, and the systems of health care delivery. Case management by nurses within the context of multidisciplinary team approaches is considered an integral component of increasing treatment adherence. The Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents, published in 2011, suggest substantive changes in the approaches to the management of lipids and other CVD risk factors (Expert Panel, 2011). Before these recent guidelines, recommendations for lipid screening indicated a targeted approach focusing on children and adolescents with a family history of dyslipidemia or premature CVD. Previous guidelines also recommended a fasting lipid profile as the optimal approach to the detection of dyslipidemia in children. Accumulated evidence, however, suggests that the targeted approach missed many children and adolescents with substantial elevation of LDL-C. Concerns regarding children with

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genetic dyslipidemia, particularly those with heterozygous familial hypercholesterolemia (FH) who are at clearly an increased risk of ASCVD over their lifetime fueled the recommendation for the universal screening of children between the ages of 9 and 11 years. This age range was targeted because evidence suggests that this is the time period that ASCVD processes begin to accelerate and it precedes the physiological changes of puberty that result in declines in LDL-C. In addition, evidence emerged supporting the use of non-HDL-C as a screening measure. Of note, non-HDL-C can be obtained in a nonfasting state, facilitating the use in health care settings, including primary care. An important pharmacological modification in the treatment that was also recommended by the American Academy of Pediatrics (AAP; Daniels & Greer, 2008) and the AHA (McCrindle et al., 2007) focuses on the timing of initiation and the class of lipidlowering agents. Specifically, the 2011 recommendations emphasize lifestyle interventions as the cornerstone of treatment; however, if an adequate trial does not result in target goals (LDL-C is persistently greater than 190 mg/ dL with no other risk factors, LDL-C is persistently greater than 160 mg/dL with a family history of premature heart disease or two or more other risk factors, and LDL-C greater than or equal to 130 mg/dL in the setting of diabetes), pharmacological treatment beginning at 10 years and older should be considered. On the basis of accumulated safety and efficacy data, the 2011 guidelines recommend that statins be considered as the first line of drug treatment. The 2011 guidelines also focus on the management of low cardioprotective HDL-C and high triglycerides, commonly observed in obesity. The treatment recommendations emphasize lifestyle interventions, including diet (CHILD-2-TG) and physical activity. A critically important component of the 2011 guidelines is the emphasis on the treatment of dyslipidemia in the context of all CVD risk factors, including hypertension, tobacco use, diabetes, obesity, and physical inactivity (Expert Panel, 2011).

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The assessment and management of hypercholesterolemia and other lipid abnormalities is an important component of both individual/ high-risk and population-based approaches to CVD risk reduction. Current evidence-based guidelines for adults and children and adolescents consider both lipid and nonlipid risk factors, target LDL-C in algorithms for assessment and treatment considerations, and emphasize lifestyle interventions as the cornerstone of treatment. Therapeutic regimens, including pharmacotherapy and lifestyle modifications, are based on the individual’s risk status; treatment outcomes are optimized with case management by nurses within the context of a multidisciplinary team approach. Directions for future research build on and extend current programs of nursing and multidisciplinary research focused on innovative models for primary and secondary prevention of CVD across the life span and with emphasis on both quality and cost as outcomes (Allen & Dennison, 2010; Allen, Dennison Himmelfarb, Szanton, & Frick, 2014; Allen et al., 2011; Berra, Miller, & Jennings, 2011). Additional areas for future research include multilevel approaches to reducing disparities in cardiovascular health with emphasis on social and behavioral determinants (Hayman & Worel, 2016) and optimizing the role of nurses and nursing in global CVD prevention (Hayman, Berra, Fletcher, & Houston Miller, 2015).

Laura L. Hayman Heather H. Ryan Allen, J. K., & Dennison, C. R. (2010). Randomized trials of nursing interventions for secondary prevention in patients with coronary artery disease and heart failure:  Systematic review. Journal of Cardiovascular Nursing, 25(3), 207–220. Allen, J. K., Dennison-Himmelfarb, C. R., Szanton, S. L., Bone, L., Hill, M. N., Levine, D. M., . . . Anderson, K. (2011). Community Outreach and Cardiovascular Health (COACH) Trial: A randomized, controlled trial of nurse practitioner/ community health worker cardiovascular disease risk reduction in urban community health centers. Circulation:  Cardiovascular Quality and Outcomes, 4(6), 595–602.

Allen, J. K., Dennison Himmelfarb, C. R., Szanton, S. L., & Frick, K. D. (2014). Cost-effectiveness of nurse practitioner/community health worker care to reduce cardiovascular health disparities. Journal of Cardiovascular Nursing, 29(4), 308–314. Berra, K., Miller, N. H., & Jennings, C. (2011). Nurse-based models for cardiovascular disease prevention:  From research to practice. Journal of Cardiovascular Nursing, 26(Suppl.  4), S546–S555. Daniels, S. R., Greer, F. R.; Committee on Nutrition. (2008). Lipid screening and cardiovascular health in childhood. Pediatrics, 122(1), 198–208. Eckel, R. H., Jakicic, J. M., Ard, J. D., de Jesus, J. M., Houston Miller, N., Hubbard, V. S., . . . Tomaselli, G. F.; American College of Cardiology/American Heart Association Task Force on Practice Guidelines. (2014). 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: A report of the American College of Cardiology/ American Heart Association Task Force on Practice Guidelines. Circulation, 129(25, Suppl. 2), S76–S99. Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents. (2011). Summary report. Pediatrics, 128(Suppl. 5), S213–S256. Fletcher, B., Berra, K., Ades, P., Braun, L. T., Burke, L. E., Durstine, J. L., . . . Winston, M.; Council on Cardiovascular Nursing; Council on Arteriosclerosis, Thrombosis, and Vascular Biology; Council on Basic Cardiovascular Sciences; Council on Cardiovascular Disease in the Young; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Council on Nutrition, Physical Activity, and Metabolism; Council on Stroke; Preventive Cardiovascular Nurses Association. (2005). Managing abnormal blood lipids: A collaborative approach. Circulation, 112(20), 3184–3209. Hayman, L. L., Berra, K., Fletcher, B. J., & Houston Miller, N. (2015). The role of nurses in promoting cardiovascular health worldwide:  The global cardiovascular nursing leadership forum. Journal of the American College of Cardiology, 66(7), 864–866. Hayman, L. L., & Worel, J. N. (2016). Reducing disparities in cardiovascular health:  Social determinants matter. Journal of Cardiovascular Nursing, 31(4), 288–290. McCrindle, B. W., Urbina, E. M., Dennison, B. A., Jacobson, M. S., Steinberger, J., Rocchini, A. P., . . . Daniels , S. R.; American Heart Association

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Atherosclerosis, Hypertension, and Obesity in Youth Committee; American Heart Association Council of Cardiovascular Disease in the Young; American Heart Association Council on Cardiovascular Nursing. (2007). Drug therapy of high-risk lipid abnormalities in children and adolescents: A scientific statement from the American Heart Association Atherosclerosis, Hypertension, and Obesity in Youth Committee, Council of Cardiovascular Disease in the Young, with the Council on Cardiovascular Nursing. Circulation, 115(14), 1948–1967. National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (ATP III). (2002). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation, 106, 3143–3421. Ockene, I. S., Hayman, L. L., Pasternak, R. C., Schron, E., & Dunbar-Jacob, J. (2002). Task force #4—Adherence issues and behavior changes: Achieving a long-term solution. 33rd Bethesda Conference. Journal of the American College of Cardiology, 40(4), 630–640. Stone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., . . . Wilson, P. W.; American College of Cardiology/ American Heart Association Task Force on Practice Guidelines. (2014). 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation, 129(25, Suppl. 2), S1–S45.

CAREGIVER A caregiver is defined as an individual who assists ill person(s), often helps with a patient’s physical care, typically lives with the patient, and does not receive monetary compensation for the help. Also, a caregiver is a person who not only performs common caregiver responsibilities (i.e., providing physical, social, spiritual, financial management,

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and complex home care) but also advocates for the ill person within health care systems and society, as a whole (National Family Caregivers Association, 2009). The caregiver’s role is often expected in relation to one’s elders, yet rarely is there preparation for caregiving for one’s child or one’s spouse. Direct patient care encompasses much more than physical care; it also necessitates learning an extensive amount of information about illness, symptoms, medications, technological treatments, and how to relate to health care professionals (Smith, 1995; Wilkins, Bruce, & Sirey, 2009). Caregivers must also be prepared for emergencies and be capable of responding appropriately. Usually, the caregiver must also manage his or her personal responsibilities, whether as a breadwinner, a housekeeper, or both. The caregiver’s relationship with the patient, the caregiver’s age and developmental stage of life, the patient’s illness severity, and the suddenness and amount of the change in the patient’s need for caregiving have been predictive of caregiver burnout in various illness populations, such as chronic obstructive pulmonary disease (Caress, Luker, Chalmers, & Salmon, 2009), kidney disease (Tong, Sainsbury, & Craig, 2008), heart failure (Bakas, Pressler, Johnson, Nauser, & Shaneyfelt, 2006; Molloy, Johnston, & Witham, 2005; Pressler et al., 2009, 2013), and stroke survivors (Rigby, Gubitz, & Phillips, 2009). The indirect familial caregiver tasks include designating others to assist with patient care, exchanging information, maintaining decision making among appropriate persons, and coping with psychosocial stressors (Whitlatch, 2008). Because the caregiver by definition is laden with tasks and expectations, the major area of research has been caregiver burden and negative outcomes on caregivers’ physical, mental, and financial health (Piamjariyakul et al., 2015; Piamjariyakul, Smith, Russell, Werkowitch, & Elyachar, 2013; Schulz & Sherwood, 2008; Smith et al., 2010). The majority of burden studies has been descriptive and correlational and has resulted in the identification of multiple factors recognized

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as being significant problems: complexity of the care needed by the patient that is often measured as illness demands. Numerous variables (e.g., demographic information, developmental stage, social support) that have been studied in relation to caregiver experience are influential yet not universally predictive of caregiver burden (Biegel, Sales, & Schulz, 1991). Caregiving is a daily part of a family member’s life and does lead to persistent worry, stress, and poor physical health (Agren, Evangelista, & Strömberg, 2010; Luttik et al., 2007; Luttik, Jaarsma, Veeger, & van Veldhuisen, 2005; National Alliance for Caregiving, 2004; Pressler et al., 2013). Smith’s (1994) research indicated caregivers’ motives for helping consistently explain the variance in their depression, coping, and quality of life (Smith, Kleinbeck, Boyle, Kochinda, & Parker, 2001). In another clinical trial, Smith et al. (2010) reported significant relationships among family income adequacy and patients’ and caregivers’ quality of life as well as patients’ clinical outcomes and caregivers’ mental health. Out-of-pocket nonreimbursed costs have a substantial impact on families managing home heart failure care (Korves et al., 2012). Patients with chronic health problems and their families often pay through expensive health insurance to cover their multiple health services, which puts a disproportionate burden on them for nonreimbursed expenses (Cunningham, 2009). These costs include any one or a combination of expenditures for annual insurance premiums, deductibles, and copayments for health services. Items not covered by insurance were reported as higher than 10% of the family annual income for out-of-pocket costs for their health services (Paez, Zhao, & Hwang, 2009; Piamjariyakul et al., 2010, 2014). Qualitative data supported these findings that economic stress was the strongest factor affecting the quality of life of patients and the caregiver (Smith et al., 2010). This finding was consistent and confirmed Smith’s (1994) family home caregiving model, which was replicated across two decades (Smith, 1999; Smith et al.,

2002; Winkler, Ross, Piamjariyakul, Gajewski, & Smith, 2006). In each model, caregiver characteristics of esteem, depression, and physical and mental health in the context of caregiving (e.g., family income adequacy) have predicted patient outcomes (Smith, 2007; Smith, Leenerts, & Gajewski, 2003). Problem-solving ability is lauded as essential and the caregiver’s ability to solve problems can avert patient problems (National Family Caregivers Association, 2002; Schulz, 2000), yet only a handful of studies on problem solving in caregiving were found. Unique research on the positive aspects of caregiving is being conducted by Smith (2007) under the concept of caregiving effectiveness. Effective caregiving is defined as the family provision of technical, physical, and emotional care that results in optimal patient health and quality of life and minimal technological side effects while maintaining the caregiver’s health and quality of life (Smith, 1994). Nursing interventions have been found to be efficacious for caregiver problems of depression, sleep deprivation, social isolation, and lack of access to evidence-based information, caregiving, and complex technology problem solving (Smith, Dauz, Clements, Werkowitch, & Whitman, 2009; Smith et al., 2003, 2006). These interventions include counseling, peer support, high-quality Internet information, and contacts with experts. There is a dearth of research on caregiving with lifelong technology dependence that begins unexpectedly in middle life (when teenagers and elder family members also need assistance) and continues on a trajectory of intermittent disease exacerbations and slow, progressive decline (Spaulding et al., 2014; Winkler et al., 2006). Traditional education, such as verbal instruction at discharge, does not ensure that caregivers will be able to understand and integrate home care management activities into daily routines (Albert, 2008; Clark et al., 2009; Piamjariyakul, Smith, Werkowitch, & Elyachar, 2012a). Telephone coaching, telehealth, and web-based support in the homes are other interventions providing caregivers support (Piamjariyakul, Schiefelbein, & Smith, 2006;

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Piamjariyakul & Smith, 2008; Piamjariyakul, Smith, Werkowitch, & Elyachar, 2012b; Smith, 2007). In two recent studies, family caregivers requested information on the most challenging aspects of providing home care for chronically ill patients: dealing with patients’ dietary restrictions, monitoring signs and symptoms, and obtaining information from health care providers (Pressler et al., 2009; Wilkins et al., 2009). The most widely recommended clinical yet unverified approach is to provide guidelines to manage specific caregiving problems (Schulz, Lustig, Handler, & Martire, 2002). Step-by-step guidelines (including computer algorithms) can guide systematic thinking and develop skills for solving stressful caregiving problems and communicating with their health care providers (Given, Sherwood, & Given, 2008; Piamjariyakul et al., 2010; Smith, Koehler, Moore, Blanchard, & Ellerbeck, 2005). The state-of-the-science report on computer-based algorithms that aid patients to make step-by-step decisions about treatment options concluded that improved knowledge, attitudes, and lower health services used resulted from patients’ use of algorithms (Agency for Health Care Policy and Research, 1998; Agency for Healthcare Research and Quality, 2010). The Cochrane review and the randomized trial results concur, adding that patients with step-by-step decision aids had realistic treatment expectations, satisfaction with care, and lowered anxiety (O’Connor et al., 2002). The more successful problem-solving algorithms included logical, easily remembered steps, multiperspective (psychological and physical) information, long-term access, and booster repetition, all tailored to a specific group with common problems (Piamjariyakul et al., 2013; Smith et al., 2005, 2015). Research should continue on the culturally related aspects of caregiving strategies used in various ethnic groups (Dilworth-Anderson et al., 2005; Dilworth-Anderson, Williams, & Gibson, 2002; Evans, Crogan, Belyea, & Coon, 2009; Piamjariyakul et al., 2015; Williamson & Harrison, 2010). Another contemporary focus in caregiving research should be the caregiving family, as research has clearly indicated

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that multiple members of families are involved in providing direct and indirect care, both to the patient and in support of the primary caregiver (Smith, 1996). In addition to the caregiving family, the caregiving neighborhood or parish should be a focus of study (Durant et al., 2013). With an appropriate outreach intervention program, the “out-of-home caregivers” can help provide a low-cost health care support to the patients, such as monitoring symptoms, improving treatment adherence, prescribed diet, and lifestyle changes (Kalra et al., 2004; Piette et al., 2008). Historically, research on the topic of caregivers has come from the literature on aging in which burden and supportive interventions have been studied (Tong et al., 2008). Interventions tested include teaching mastery of caregiving tasks, social interventions, such as support groups or telephone contacts, and direct clinical services, such as counseling and respite care. Outcomes of many of these intervention studies indicated that in the short term, the interventions may reduce caregiver stress in a limited way, but the burden returns when the interventions cease. Given the escalating involvement of informal caregivers and high costs of chronic illness care, interventions with the potential for improving caregiver daily home care management and improving patients’ outcomes (i.e., reducing rehospitalizations) must be tested.

Ubolrat Piamjariyakul Carol E. Smith Agency for Health Care Policy and Research. (1998). Consumer health informatics and patient decision making (AHCPR Pub. No. 98N001). Retrieved from https://archive.ahrq .gov/professionals/quality-patient-safety/ quality-resources/tools/rtisumm.html Agency for Healthcare Research and Quality. (2010). Web healthcare 411: News series from AHRQ. Retrieved from http://healthcare411.ahrq.gov Agren, S., Evangelista, L., & Strömberg, A. (2010). Do partners of patients with chronic heart failure experience caregiver burden? European Journal of Cardiovascular Nursing, 9(4), 254–262.

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Albert, N. M. (2008). Promoting self-care in heart failure:  State of clinical practice based on the perspectives of healthcare systems and providers. Journal of Cardiovascular Nursing, 23(3), 277–284. Bakas, T., Pressler, S. J., Johnson, E. A., Nauser, J. A., & Shaneyfelt, T. (2006). Family caregiving in heart failure. Nursing Research, 55(3), 180–188. Biegel, D., Sales, E., & Schulz, R. (Eds.). (1991). Family caregiving in chronic illness. In Family caregiver application series (pp. 1–45). Newbury Park, CA: Sage. Caress, A.-L., Luker, K. A., Chalmers, K. I., & Salmon, M. P. (2009). A review of the information and support need of family carers of patients with chronic obstructive pulmonary disease. Journal of Clinical Nursing, 18, 479–491. Clark, A. M., Freydberg, C. N., McAlister, F. A., Tsuyuki, R. T., Armstrong, P. W., & Strain, L. A. (2009). Patient and informal caregivers’ knowledge of heart failure: Necessary but insufficient for effective self-care. European Journal of Heart Failure, 11(6), 617–621. Cunningham, C. J. (2009, July). Chronic burdens: The persistently high out-of-pocket health care expenses faced by many Americans with chronic conditions. Commonwealth Fund, 63, 1–14. Dilworth-Anderson, P., Brummett, B. H., Goodwin, P., Williams, S. W., Williams, R. B., & Siegler, I. C. (2005). Effect of race on cultural justifications for caregiving. Journals of Gerontology: Series B, Psychological Sciences and Social Sciences, 60(5), S257–S262. Dilworth-Anderson, P., Williams, I. C., & Gibson, B. E. (2002). Issues of race, ethnicity, and culture in caregiving research: A 20-year review (1980-2000). The Gerontologist, 42(2), 237–272. Durant, R. W., Brown, Q. L., Cherrington, A. L., Andreae, L. J., Hardy, C. M., & Scarinci, I. C. (2013). Social support among African Americans with heart failure: Is there a role for community health advisors? Heart & Lung, 42(1), 19–25. Evans, B. C., Crogan, N., Belyea, M., & Coon, D. (2009). Utility of the life course perspective in research with Mexican American caregivers of older adults. Journal of Transcultural Nursing, 20(1), 5–14. Given, B., Sherwood, P. R., & Given, C. W. (2008). What knowledge and skills do caregivers need? American Journal of Nursing, 108(Suppl. 9), 28–34; quiz 34.

Kalra, L., Evans, A., Perez, I., Melbourn, A., Patel, A., Knapp, M., & Donaldson, N. (2004). Training carers of stroke patients: Randomised controlled trial. British Medical Journal, 328(7448), 1099. Korves, C., Eldar-Lissai, A., McHale, J., Lafeuille, M. H., Hwa Ong, S., & Sheng Duh, M. (2012). Resource utilization and costs following hospitalization of patients with chronic heart failure in the U.S. Journal of Medical Economics, 15(5), 925–937. Luttik, M. L., Jaarsma, T., Veeger, N., Tijssen, J., Sanderman, R., & van Veldhuisen, D. J. (2007). Caregiver burden in partners of heart failure patients; limited influence of disease severity. European Journal of Heart Failure, 9(6–7), 695–701. Luttik, M. L., Jaarsma, T., Veeger, N. J., & van Veldhuisen, D. J. (2005). For better and for worse: Quality of life impaired in HF patients as well as in their partners. European Journal of Cardiovascular Nursing, 4(1), 11–14. Molloy, G. J., Johnston, D. W., & Witham, M. D. (2005). Family caregiving and congestive heart failure. Review and analysis. European Journal of Heart Failure, 7(4), 592–603. National Alliance for Caregiving. (2004). Caregiving in the U.S. Retrieved from http://www .caregiving.org/data/04finalreport.pdf National Family Caregivers Association. (2002). NFCA caregiver survey. Retrieved from https://www.allsup.com/media/files/NFCA -Caregiver-Survey10.11.pdf National Family Caregivers Association. (2009). Who are America’s family caregivers? Retrieved from http://www.caregiving.org/ data/Caregiving_in_the_US_2009_full_report .pdf O’Connor, A.  M., Stacey, D., Rovner, D., HomesRovner, M., Tetroe, J., Llewellyn-Thomas, H., . . . Jones, J. (2002). Decision aids for people facing health treatment or screening decisions (Cochrane Review) in the Cochrane Library. Oxford, UK: Update Software. Paez, K. A., Zhao, L., & Hwang, W. (2009). Rising out-of-pocket spending for chronic conditions: A ten-year trend. Health Affairs, 28(1), 15–25. Piamjariyakul, U., Schiefelbein, J., & Smith, C. (2006). CPAP home support of elderly via website algorithms. 11th World Congress on Internet Medicine, Toronto October 14–19. Medical Science Interventions Reports. Retrieved

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from https://www.wesrch.com/medical/ paper-details/pdf-ME1MS1754PLDU-11th -world-congress-on-internet-in-medicine -abstracts Piamjariyakul, U., & Smith, C. E. (2008). Telemedicine utilization reports and evaluation. In L. Martinez & C. Gomez (Eds.), Telemedicine in the 21st century (pp. 41–53). Hauppauge, NY: Nova Science Publishers. Piamjariyakul, U., Smith, C. E., Russell, C., Werkowitch, M., & Elyachar, A. (2013). The feasibility of a telephone coaching program on heart failure home management for family caregivers. Heart & Lung: The Journal of Critical Care, 42(1), 32–39. Piamjariyakul, U., Smith, C.  E., Werkowitch, M., & Elyachar, A.  (2012a). Part I:  Heart failure home management: Patients, multidisciplinary healthcare professionals and family caregivers perspectives. Applied Nursing Research, 25(4), 239–245. Piamjariyakul, U., Smith, C. E., Werkowitch, M., & Elyachar, A. (2012b). Part II: Heart failure home management: Integrating patients’, professionals’, and caregivers recommendations. Applied Nursing Research, 25(4), 246–250. Piamjariyakul, U., Werkowitch, M., Wick, J., Russell, C., Vacek, J. L., & Smith, C. E. (2015). Caregiver coaching program effect: Reducing heart failure patient rehospitalizations and improving caregiver outcomes among African Americans. Heart & Lung: The Journal of Critical Care, 44(6), 466–473. Piamjariyakul, U., Yadrich, D. M., Ross, V. M., Smith, C. E., Clements, F., & Williams, A. R. (2010). Complex home care: Part 2—Family annual income, insurance premium, and outof-pocket expenses. Nursing Economic$, 28(5), 323–329. Piamjariyakul, U., Yadrich, D. M., Russell, C., Myer, J., Prinyarux, C., Vacek, J. L., . . . Smith, C. E. (2014). Patients’ annual income adequacy, insurance premiums and out-of-pocket expenses related to heart failure care. Heart & Lung: The Journal of Critical Care, 43(5), 469–475. Piette, J. D., Gregor, M. A., Share, D., Heisler, M., Bernstein, S. J., Koelling, T., & Chan, P. (2008). Improving heart failure self-management support by actively engaging out-of-home caregivers: Results of a feasibility study. Congestive Heart Failure, 14(1), 12–18.

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Pressler, S. J., Gradus-Pizlo, I., Chubinski, S. D., Smith, G., Wheeler, S., Sloan, R., & Jung, M. (2013). Family caregivers of patients with heart failure: A longitudinal study. Journal of Cardiovascular Nursing, 28(5), 417–428. Pressler, S. J., Gradus-Pizlo, I., Chubinski, S. D., Smith, G., Wheeler, S., Wu, J., & Sloan, R. (2009). Family caregiver outcomes in heart failure. American Journal of Critical Care, 18(2), 149–159. Rigby, H., Gubitz, G., & Phillips, S. (2009). A systematic review of caregiver burden following stroke. International Journal of Stroke, 4(4), 285–292. Schulz, R.  (2000). Handbook of dementia caregiving:  Evidence-based interventions for family caregivers. New York, NY: Springer Publishing. Schulz, R., Lustig, A., Handler, S., & Martire, L. M. (2002). Technology based caregiver intervention research: Current status and future directions. Gerontechnology, 2(1), 15–47. Schulz, R., & Sherwood, P. R. (2008). Physical and mental health effects of family caregiving. American Journal of Nursing, 108(Suppl. 9), 23–27; quiz 27. Smith, C. E. (1994). A model of caregiving effectiveness for technologically dependent adults residing at home. Advances in Nursing Science, 17(2), 27–40. Smith, C.  E. (1995). Technology and home care. In S.  Fitzpatrick & A.  Jacox (Eds.), Annual review of nursing research (Vol. 13, pp. 137–167). New York, NY: Springer Publishing. Smith, C. E. (1996). Quality of life and caregiving in technological home care. In J. J. Fitzpatrick & J. Norbeck (Eds.), Annual review of nursing research (Vol. 14, pp. 95–118). New York, NY: Springer Publishing. Smith, C. E. (1999). Caregiving effectiveness in families managing complex technology at home: Replication of a model. Nursing Research, 48(3), 120–128. Smith, C. E. (2007). Testing virtual nurse caring of picture phones and Internet. Clinical Nutrition, 2(2), 43–44. Smith, C. E., Curtas, S., Kleinbeck, S. V., Werkowitch, M., Mosier, M., Seidner, D. L., & Steiger, E. (2003). Clinical trial of interactive and videotaped educational interventions reduce infection, reactive depression, and rehospitalizations for sepsis in patients on home parenteral nutrition. Journal of Parenteral and Enteral Nutrition, 27(2), 137–145.

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Smith, C. E., Dauz, E. R., Clements, F., Puno, F. N., Cook, D., Doolittle, G., & Leeds, W. (2006). Telehealth services to improve nonadherence: A placebo-controlled study. Telemedicine Journal and e-Health, 12(3), 289–296. Smith, C. E., Dauz, E., Clements, F., Werkowitch, M., & Whitman, R. (2009). Patient education combined in a music and habit-forming intervention for adherence to continuous positive airway (CPAP) prescribed for sleep apnea. Patient Education and Counseling, 74(2), 184–190. Smith, C. E., Kleinbeck, S. V., Boyle, D., Kochinda, C., & Parker, S. (2001). Family caregivers’ motives for helping scale derived from motivation-to-help theory. Journal of Nursing Measurement, 9(3), 239–257. Smith, C. E., Koehler, J., Moore, J. M., Blanchard, E., & Ellerbeck, E. (2005). Testing videotape education for heart failure. Clinical Nursing Research, 14(2), 191–205. Smith, C. E., Leenerts, M. H., & Gajewski, B. J. (2003). A systematically tested intervention for managing reactive depression. Nursing Research, 52(6), 401–409. Smith, C. E., Pace, K., Kochinda, C., Kleinbeck, S. V., Koehler, J., & Popkess-Vawter, S. (2002). Caregiving effectiveness model evolution to a midrange theory of home care: A process for critique and replication. Advances in Nursing Science, 25(1), 50–64. Smith, C. E., Piamjariyakul, U., Dalton, K. M., Russell, C., Wick, J., & Ellerbeck, E. F. (2015). Nurse-led multidisciplinary heart failure group clinic appointments: Methods, materials, and outcomes used in the clinical trial. Journal of Cardiovascular Nursing, 30(4, Suppl. 1), S25–S34. Smith, C. E., Piamjariyakul, U., Yadrich, D. M., Ross, V. M., Gajewski, B., & Williams, A. R. (2010). Complex home care: Part III—Economic impact on family caregiver quality of life and patients’ clinical outcomes. Nursing Economic$, 28(6), 393–399, 414. Spaulding, R., Smith, C. E., Nelson, E. L., Yadrich, D., Werkowitch, M., & Piamjariyakul, U. (2014). iCare: mHealth clinic appointments using iPad Minis between multiple professionals and intravenous dependent patients in their homes; ATA case study. Washington, DC: American Telemedicine Association. Retrieved from http://hub.americantelemed.org/ resources/telemedicine-case-studies

Tong, A., Sainsbury, P., & Craig, J. C. (2008). Support interventions for caregivers of people with chronic kidney disease: A systematic review. Nephrology, Dialysis, Transplantation, 23(12), 3960–3965. Whitlatch, C. (2008). Informal caregivers: Communication and decision making. American Journal of Nursing, 108(Suppl. 9), 73–77; quiz 77. Wilkins, V. M., Bruce, M. L., & Sirey, J. A. (2009). Caregiving tasks and training interest of family caregivers of medically ill homebound older adults. Journal of Aging and Health, 21(3), 528–542. Williamson, M., & Harrison, L. (2010). Providing culturally appropriate care: A literature review. International Journal of Nursing Studies, 47(6), 761–769. Winkler, M. F., Ross, V. M., Piamjariyakul, U., Gajewski, B., & Smith, C. E. (2006). Technology dependence in home care: Impact on patients and their family caregivers. Nutrition in Clinical Practice, 21(6), 544–556.

CARING Caring is a central concept in the discipline of nursing (Cowling, Smith, & Watson, 2008; Newman, Sime, & Corcoran-Perry, 1991; Newman, Smith, Pharris, & Jones, 2008; M. C. Smith, 2014). The discipline of nursing focuses on the study of human–environment health and healing through caring. The knowledge of any professional discipline guides its practice; therefore, the promotion of health, healing, and well-being through caring is the goal of nursing practice. Over the past 40 years, philosophic, theoretic, and empiric dimensions of caring in nursing have grown significantly, contributing to the emergence of a substantive body of knowledge referred to as caring science. Although criticism has been levied against the concept of “caring” in nursing

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for its lack of conceptual clarity (Morse, Solberg, Neander, Bottorff, & Johnson, 1990; Paley, 2001; M. J. Smith, 1990), there is growing international consensus within the discipline that knowledge about caring is key to understanding human health, healing, and quality of life (Newman et al., 2008; Stevenson & Tripp-Reimer, 1990; Watson & Smith, 2002). On the basis of an analysis of the literature, Morse et al. (1990) elaborated five perspectives of caring in nursing: a human trait, a moral imperative, an affect, an interpersonal interaction, and a therapeutic intervention. In another analysis of caring theory, Boykin and Schoenhofer (1990) argued for a multidimensional approach integrating ontological (meaning of caring), anthropological (meaning of being a caring person), and ontical (function and ethic of caring) perspectives. Philosophical/theoretical and empirical work in caring is expanding. Philosophies, grand theories, and middle range theories compose the philosophic or theoretic dimensions of caring science. Boykin and Schoenhofer (2001), Duffy (2015), Eriksson (2006), Leininger and McFarland (2006), Locsin (2015), Mayeroff (1971), Ray (2013), Ray and Turkel (2014), Roach (2007), M. C. Smith (2015), Swanson (1991), and Watson (2008a) posit philosophies or theories focused on explicating the nature and dynamics of care and caring. Watson (1979, 1985, 1999, 2005) is the most prolific philosopher/theorist in the field of caring science. In her theory of human caring she describes caring as an ontology, a way of being, and a quality of consciousness that potentiates healing. She also describes caring as an ethic or moral ideal in which the humanity of the person is preserved. The theory includes 10 caritas processes, the transpersonal caring moment, caring consciousness/intentionality and energetic presence, and caring–healing modalities. Watson’s Caring Science Institute is an umbrella organization that leads the advancement of the philosophy, theory, ethic, and practice model around

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the world through a variety of mechanisms, such as the Watson Caring Science Global Associates, composed of nearly 20 member countries with full and pending status; postdoctoral educational programs; the Watson Caring Science Center, formed in collaboration with the University of Colorado College of Nursing, which includes the International Caritas Consortium of member hospitals embracing the theory as a practice model, the Caritas Coach Education program to prepare caring science champions within health care systems, and the Caring Science interdisciplinary PhD program. This organizational structure provides the resources and networking needed to sustain the seeding and advancing of Watson’s theory within health care organizations throughout the world and in the next generation of caring scientists. Madeleine Leininger, another prominent theorist (Leininger & McFarland, 2006) elucidated the transcultural dimensions of care or caring in her theory of cultural care universality and diversity. Boykin and Schoenhofer’s (1990) theory of nursing as caring contains the concepts of coming to know the other as caring, hearing and responding to calls for caring, and nurturing the growth of the other in caring. Based on a series of studies, Swanson (1991) developed a middle range theory with a definition of caring as “a nurturing way of relating to a valued other toward whom one feels a personal sense of commitment and responsibility” (p. 165). She identified five processes by which caring is enacted: knowing, being with, doing for, enabling, and maintaining belief. Katie Eriksson (2006), a leading caring scholar in Scandanavia, defines the mission of caring as the alleviation of human suffering and serving life and health. Smith (1999) argued that the meaning of caring as a concept is defined by the theory in which it is situated. She described a unitary view of caring as manifesting intentions, attuning to dynamic flow, appreciating pattern, experiencing the infinite, and inviting creative emergence.

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Caring science is a well-developed transdisciplinary field of study in the Nordic countries. Authors, such as Eriksson, Kari Martinsen, and others, have led robust research and theory development efforts in the Scandanavian countries, and the Scandanavian Journal of Caring Sciences is a vehicle for dissemination of this knowledge. Interdisciplinary academic departments of caring science and doctoral degrees exist in the field. Several trends have accelerated interest in the application of caring theories to guide practice. Hospitals with or seeking Magnet® status have adopted caring-based frameworks to guide nursing practice. The importance of caring to a culture of safety is being explored by some scholars (Swanson & Wojnar, 2004). Others (Duffy & Hoskins, 2003; Ray, 2013; Turkel, 2001; Valentine, 1997) have examined the relationship between economics and caring, asserting and supporting that caring and attention to the economics of health care are not mutually exclusive and that caring-based nursing practice can result in positive economic outcomes. Three reviews of the research literature on caring have been published. Swanson (1999) summarized and categorized the research related to caring in nursing science, and Sherwood (1997) reported a meta-synthesis of the qualitative research on caring. M.  Smith (2004) reviewed the research related to Watson’s theory of human caring. Many different designs and methods have been used to investigate caring, including descriptive qualitative designs, surveys, phenomenology, and quasiexperimental designs using standardized scales and physiological measurement. Swanson (1999) reviewed 130 data-based articles, chapters, and books on caring published between 1980 and 1996. The studies were categorized into five levels: capacity for caring (characteristics of caring persons), concerns and commitments (beliefs or values that underlie nursing caring), conditions (what affects, enhances, or inhibits the occurrence of caring), caring

actions (what caring means to nurses and clients and what it looks like), and caring consequences (outcomes of caring). In her summary of 30 qualitative studies that described outcomes of caring and noncaring relationships, Swanson found that outcomes of caring for the recipients of care were emotional and spiritual well-being (dignity, selfcontrol, and personhood), enhanced healing, and enhanced relationships. Consequences of noncaring were humiliation; fear; and feeling out of control, desperate, helpless, alienated, and vulnerable. Nurses who care report a sense of personal and professional satisfaction and fulfillment, whereas noncaring is related to outcomes of becoming hardened, oblivious, depressed, frightened, and worn down. Haldorsdottir’s (1991) research led to a classification of levels of caring relationships related to a continuum of health or vitality; abusive relationships were classified as biocidic, cold, and detached; biostatic, apathetic ones as biopassive; benevolence and kindness as bioactive; and transpersonal caring relationships as biogenic or life giving. Sherwood’s (1997) meta-synthesis of 16 qualitative studies revealed four patterns of nurse caring: interaction, knowledge, intentional response, and therapeutic outcomes. Caring was defined within content, context, process, and therapeutic or healing outcomes. Two types of caring knowledge and skills were identified as person centered and technical– physical. M. Smith (2004) reviewed 40 studies published between 1988 and 2003 that focused specifically on Watson’s theory of transpersonal caring. Four major categories of research were identified: nature of nurse caring, nurse caring behaviors as perceived by clients and nurses, human experiences and caring needs, and evaluating outcomes of caring in nursing practice and education. The largest number of studies focused on nurse caring behaviors as perceived by clients or nurses. An expanding area of research is related to evaluating outcomes of caring. Research supports that caring-based activities impact mood following miscarriage;

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patient satisfaction; pain and symptom distress in patients with cancer, well-being, and even blood pressure. Watson’s (2008b) compendium of instruments used to assess and measure caring is an important contribution toward the advancement of research. This text provides background on more than 20 instruments, citations of work in which they were used, and a copy of them. Some of these tools are as follows: (a) Larson’s Caring Assessment Report Evaluation Q (CARE-Q) to measure perceptions of nurse caring behavior, (b) Wolf’s Caring Behaviors Inventory to measure the process of caring, (c) Cronin and Harrison’s Caring Behavior Assessment Tool and Duffy’s Caring Assessment Tool to measure patient perceptions of nurse caring behaviors, (d) Nyberg’s Caring Attribute Scale to measure caring attributes, and (e) Coates’s Caring Efficacy Scale to measure the belief in the ability to express a caring orientation and to develop caring relationships. The future of research in caring is promising. An international community of scholars is actively building knowledge in caring science. The International Association for Human Caring meets annually to disseminate the work of its members, and the International Journal in Human Caring publishes research and scholarship that expands caring science. The Watson Caring Science Institute and the Anne Boykin Institute for the Advancement of Caring in Nursing have been established to support the scholarly development, dissemination, and application of knowledge related to caring. Scholars are examining the transtheoretical linkages between caring theories and other nursing conceptual systems (Watson & Smith, 2002). Important research questions center on the relationship between caring and healing outcomes, the qualities of a caring consciousness, the ontological competencies, types of nursing therapeutics that are caring based, and the types of environments and communities that facilitate caring. Nursing is the discipline that is studying the relationship

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between caring relationships and healing. Research needs to move beyond examining caring in nurse–patient relationships to caring relationships with family, friends, animals, nature, and their supreme being and how these relationships affect health outcomes. It will be important to study both caregiver and recipient outcomes of caring theory-based models of practice in different settings. Swanson (1999) offered several suggestions for future research related to caring: developing measures of caring capacity, examining the effects of nurturing and experience on caring capacity, identifying and measuring the competing variables that may confound the links between caring actions and their outcomes, moving from studying the individual as a unit of analysis to studying aggregates, and developing clinical trials to test the effectiveness of caring-based therapeutics in promotion of health and well-being. Different designs and methods must be used to capture the emerging questions in the field. Multiple ways of knowing from empirics to aesthetics are required to explore all dimensions of caring phenomena. A model of research that integrates these multiple perspectives and ways of knowing may be the preferred epistemological model for studying caring (Quinn, Smith, Ritenbaugh, Swanson, & Watson, 2003).

Marlaine C. Smith Sally Phillips Boykin, A., & Schoenhofer, S. (1990). Caring in nursing:  Analysis of extant theory. Nursing Science Quarterly, 3(4), 149–155. Boykin, A., & Schoenhofer, S. (2001). Nursing as caring:  A  model for transforming practice. Sudbury, MA: Harper Perennial. Cowling, W. R., Smith, M. C., & Watson, J. (2008). The power of wholeness, consciousness, and caring a dialogue on nursing science, art, and healing. Advances in Nursing Science, 31(1), E41–E51. Duffy, J.  R. (2015). Joanne Duffy’s quality-caring model. In M.  C. Smith & M.  A. Parker (Eds.),

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Nursing theories and nursing practice (pp.  393– 409). Philadelphia: F. A. Davis. Duffy, J. R., & Hoskins, L. M. (2003). The qualitycaring model:  Blending dual paradigms. Advances in Nursing Science, 26(1), 77–88. Eriksson, K.  (2006). The suffering human being. Chicago, IL: Nordic Studies Press. Haldorsdottir, S. (1991). Five basic modes of being with another. In D. A. Gaut & M. Leininger (Eds.), Caring: The compassionate healer (pp. 37–49). New York, NY: National League for Nursing. Leininger, M., & McFarland, M. (2006). Culture care diversity and universality: Worldwide nursing theory (2nd ed.). Sudbury, MA: Jones & Bartlett. Locsin, R. (2015). Rozzano Locsin’s technological competency as caring in nursing. In M. C. Smith & M. A. Parker (Eds.), Nursing theories and nursing practice (pp. 449–460). Philadelphia, PA: F. A. Davis. Mayeroff, M. (1971). On caring. New York, NY: Harper & Row. Morse, J. M., Solberg, S. M., Neander, W. L., Bottorff, J. L., & Johnson, J. L. (1990). Concepts of caring and caring as a concept. Advances in Nursing Science, 13(1), 1–14. Newman, M. A., Sime, A. M., & Corcoran-Perry, S. A. (1991). The focus of the discipline of nursing. Advances in Nursing Science, 14(1), 1–6. Newman, M. A., Smith, M. C., Pharris, M. D., & Jones, D. (2008). The focus of the discipline revisited. Advances in Nursing Science, 31(1), E16–E27. Paley, J. (2001). An archaeology of caring knowledge. Journal of Advanced Nursing, 36(2), 188–198. Quinn, J. F., Smith, M., Ritenbaugh, C., Swanson, K., & Watson, M. J. (2003). Research guidelines for assessing the impact of the healing relationship in clinical nursing. Alternative Therapies in Health and Medicine, 9(Suppl. 3), A65–A79. Ray, M. A. (2013). The theory of bureaucratic caring. In M. Smith, M. Turkel, & Z. Wolf (Eds.), Caring in nursing classics: An essential resource (pp. 309– 320). New York, NY: Springer Publishing. Ray, M.  A., & Turkel, M.  (2014). The theory of emancipatory nursing praxis:  The theory of relational caring complexity. Advances in Nursing Science, 37, 132–146. Roach, S.  (2007). Caring, the human mode of being:  A  blueprint for the health professions. Ottawa, ON: CHA Press.

Sherwood, G. D. (1997). Meta-synthesis of qualitative analyses of caring: Defining a therapeutic model of nursing. Advanced Practice Nursing Quarterly, 3(1), 32–42. Smith, M. (2004). Review of research related to Watson’s theory of caring. Nursing Science Quarterly, 17(1), 13–25. Smith, M.  C. (2014). Disciplinary perspectives linked to middle range theory. In M.  J. Smith & P.  Liehr (Eds.), Middle range theory for nursing (3rd ed., pp. 3–14). New York, NY: Springer Publishing. Smith, M. C. (2015). Marlaine Smith’s theory of unitary caring. In M. C. Smith & M. A. Parker (Eds.), Nursing theories and nursing practice (4th ed., pp. 509–519). Philadelphia, PA: F. A. Davis. Smith, M. J. (1990). Caring: Ubiquitous or unique. Nursing Science Quarterly, 3(2), 54. Stevenson, J. S., & Tripp-Reimer, T. (Eds.). (1990). Knowledge about care and caring. Proceedings of a Wingspread Conference. Kansas City, MO: American Academy of Nursing. Swanson, K. M. (1991). Empirical development of a middle range theory of caring. Nursing Research, 40(3), 161–166. Swanson, K.  M. (1999). What’s known about caring in nursing:  A  literary meta-analysis. In A. S. Hinshaw, J. Shaver, & S. Feetham (Eds.), Handbook of clinical nursing research (pp. 31–60). Thousand Oaks, CA: Sage. Swanson, K. M., & Wojnar, D. M. (2004). Optimal healing environments in nursing. Journal of Alternative and Complementary Medicine, 10(Suppl. 1), S-43– S-48. doi:10.1089/acm.2004.10.S-43 Turkel, M.  (2001). Struggling to find balance: The paradox between caring and economics. Nursing Administration Quarterly, 13(4), 307–313. Valentine, K. L. (1997). Exploration of the relationship between caring and cost. Holistic Nursing Practice, 11(4), 71–81. Watson, J. (1985). Nursing: Human science and human care. Norwalk, CT: Appleton Century. Watson, J.  (1999). Postmodern nursing and beyond. New York, NY: Churchill-Livingstone. Watson, J.  (2005). Caring science:  Sacred science. New York, NY: Churchill-Livingstone. Watson, J. (2008a). The philosophy and science of caring (revised ed.). Boulder:  University Press of Colorado.

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Watson, J. (2008b). Assessing and measuring caring in nursing and health sciences. New York, NY: Springer Publishing. Watson, J., & Smith, M. C. (2002). Caring science and the science of unitary human beings: A transtheoretical discourse for nursing knowledge development. Journal of Advanced Nursing, 37(5), 452–461.

CASE STUDY METHOD OF RESEARCH Case study as a method of research has been used in nursing, medicine, and the social sciences for decades because of the recognized importance in practice of a holistic and individualized approach. Case study can bridge the gap between theory and practice and is a useful tool for implementation science and translational research. It is the recognition of the connection between practice and research that makes case study research appealing to health care practitioners. Case study is described as a research method or design (Clarke, Reed, & Keyes, 2015; Denzin & Lincoln, 2011; Yin, 2014), a method of data collection (Cronin, 2014; Lincoln & Guba, 1985), and a technique for teaching (Breslin & Buchanan, 2008; Henning, Nielsen, & Hauschildt, 2006). Stake (1995) considers the case as the unit of study rather than a methodologic choice. Case study is a way to describe, to explore, to understand, and to evaluate a phenomenon within the context in which it occurs (Anthony & Jack, 2009; Yin, 2014) with the understanding that the context is of significance. The earliest use of case study was as a teaching technique reported in 1870 at the Harvard Law School (Garvin, 2003). Case study as a teaching technique used problem solving in the transition between theory and practice and has been used in nursing since

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the early 1900s (Parsons, 1911). Case studies were commonly reported in nursing 40 to 50 years ago (Burns & Grove, 2011) but fell out of favor as nursing struggled to be recognized as a science. There has been a renewed interest in the case study as an approach to constructivist inquiry (Anthony & Jack, 2009). Case study research design can be quantitative or qualitative and examine phenomena that can be conceptual or about individuals, populations, or organizations (Clarke et al., 2015). Case studies can be as simple as a single, brief case or very complex, examining a large number of variables, but the goal is to answer questions of how or why. Case study is also used for theory generation and hypothesis testing. Qualitative case study method is often used as an adjunct method in an otherwise quantitative study. It is used this way for “in-depth study of meaningful characteristics of real-life events” (Anthony & Jack, 2009, p. 1175). Case study is a method that is appropriate with research that is flexible in epistemology, ontology, methodology, and strategies of inquiry (Clarke et al., 2015). In nursing, case study design is used to study the complexities of nursing practice (Casey & Houghton, 2010). Case study is an intensive systematic study of an entity or entities about which little is known and conducted within the context of the reallife situation. The common characteristics of case studies include the use of theory to guide data collection and analysis; the use of multiple sources of data and triangulation, applicable when the boundaries between context and phenomenon are unclear; and there are more variables than data points (Clarke et al., 2015). Case studies can be exploratory, descriptive, interpretive, experimental, or explanatory (Yin, 2014). The level of analysis also varies from factual or interpretive to evaluative (Lincoln & Guba, 1985; Yin, 2014). Case study is used to expand understanding of phenomena about which little is known. The data can then be used to

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formulate hypotheses and plan larger studies. Other purposes of case study include theory testing, description, and explanation. For example, the intensive analysis involved in case study is appropriate to answer questions of explanation, such as why participants think or behave in certain ways. The case study approach can also be used when a problem has been identified and a solution needs to be found—all within the context of the current “real-life” situation. The research process for case study design is similar to the techniques used in other designs. First, the literature is reviewed, and the purpose, the research questions, and the definition of the case are developed. Questions of what, how, and why are appropriate for case study designs. The definition of the case, its constituents, and boundaries will determine the type of cases to be sampled. A  theoretical/conceptual framework (pre-understandings) will guide the study. This will help to identify assumptions that the researcher may have about the phenomenon at the beginning of the study. At the outset of the study, the unit of analysis must be clearly delineated. The unit of analysis is the case, which can be a single person, family, community, or institution (Burns & Grove, 2011). Clearly identifying the unit of analysis has implications for the data collection and the study protocol. The protocol should list how participants will be recruited and what constitutes data (documents, letters, interviews, field observations, etc.). The protocol should also identify what resources will be needed and a tentative time line for data collection. Because case study method is flexible, modifications can be made in the protocol as the study progresses and the problems emerge. The protocol should also identify the plan for data analysis and how the data will be reported. Case study design can be a single-case design or a multiple-case design. Single-case designs are used when a case represents a typical, extreme, critical, unique, or revelatory

case (Yin, 2014). When the purpose of the study is theory generation, a multiple-case design is appropriate. Multiple-case design draws inferences and interpretations from a group of cases. The multiple-case design is also useful to add depth to explanatory and descriptive studies. Data for case study can be qualitative or quantitative and often includes both in the same study, depending on the research question. Data from multiple sources, archival data, field notes, interview tapes (audio or video), direct observation, participant observation, logs, documents, and narratives generate a comprehensive and rich case study. Every source of data has strengths and weaknesses, but when used together, the benefits of each combine to diminish the weaknesses and strengthen the outcome. Data analysis in case study is guided by the research question(s) and the type of data. Qualitative data analysis techniques, content analysis, analytic induction, constant comparison, and phenomenological analysis are used in the case study depending on the type of data and research question(s). Planned case studies are generally analyzed using pattern matching because the multiple sources of data contribute to similar phenomena (Almutairi, Gardner, & McCarthy, 2014). Because there are no fixed formulas for analyzing qualitative data, the researcher’s own rigorous thinking is paramount, giving consideration to alternative interpretations (Yin, 2014). If data are quantitative in nature, analysis is similar to any quantitative study and is dependent on the research question(s). The goal for data analysis in case study research is to answer the research question(s), but also contributes to broader issues and the possible transferability of the results to other contexts. Case study reports are presented in a variety of ways, from formal written narratives to creative montages of photographs, videotape, and arts and crafts work. Most case study reports in nursing

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are formal written narratives appearing in peer-reviewed journals. There are no rules or standardized ways to write a report, but most case studies include an explanation of the problem or issue and a detailed description of the context and processes surrounding the phenomenon under investigation. A discussion of the results is also included in the reports, which can contain inferences about how these results fit with the existing literature and implications for practice. The standard measures of reliability and validity apply to case studies that are quantitative. The criteria developed by Lincoln and Guba (1985) are used to evaluate qualitative case studies. When a study meets the criteria for credibility, transferability, dependability, and confirmability, it is considered to be trustworthy (reliable and valid). Credibility of the interpretations is supported by techniques such as triangulation of data-collection methods, negative case analysis, and checking the interpretation with the participants themselves. Transferability (generalizability) is an indication of whether the findings or conclusions of the study fit in other contexts and fit with the existing literature. When another person is able to follow the researcher’s audit trail or the process and procedures of the inquiry, then the study is considered to be dependable. Confirmability is achieved when the results, conclusions, and recommendations are supported in the data and the audit trail is evident. Case study method is a comprehensive research strategy used to examine phenomena of interest to nursing within the real-life context. As a method, it has survived the positivist debate and is being used more often in nursing. On the basis of the fact that case studies are reported almost exclusively in peer-reviewed journals (benchmarks of quality), it can be stated that case study is an accepted research method/design in nursing. An ongoing challenge to the use of case study as a research method in nursing is the continued debate and lack of clarity in what

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case study actually is. Case study method fits with the current trend in inquiry that supports flexibility in epistemology, ontology, methodology, and research strategy (Denzin & Lincoln, 2011).

Debera Jane Thomas Almutairi, A. F., Gardner, G. E., & McCarthy,  A. (2014). Practical guidance for the use of a pattern-matching technique in case-study research: A case presentation. Nursing & Health Sciences, 16(2), 239–244. Anthony, S., & Jack, S. (2009). Qualitative case study methodology in nursing research:  An integrative review. Journal of Advanced Nursing, 65(6), 1171–1181. Breslin, M., & Buchanan, R. (2008). On the case study method of research and teaching in design. Design Issues, 24(1), 36–40. Burns, N., & Grove, S.  K. (2011). Understanding nursing research: Building an evidence-based practice (5th ed.). St. Louis, MO: Saunders/Elsevier. Casey, D., & Houghton, C. (2010). Clarifying case study research: Examples from practice. Nurse Researcher, 17(3), 41–51. Clarke, C., Reed, J., & Keyes, S.  E. (2015). Case study research. In K.  Gerrish & J.  Lathlean (Eds.), The research process in nursing (7th ed., pp. 279–290). West Sussex, UK: John Wiley. Cronin, C. (2014). Using case study research as a rigorous form of inquiry. Nurse Researcher, 21(5), 19–27. Denzin, N.  K., & Lincoln, Y.  S. (Eds.). (2011). The SAGE handbook of qualitative research (4th ed.). Thousand Oaks, CA: Sage. Garvin, D. A. (2003, September–October). Making the case. Harvard Magazine, pp. 58–59. Henning, J. E., Nielsen, L. E., & Hauschildt, J. A. (2006). Implementing case study methodology in critical care nursing:  A  discourse analysis. Nurse Educator, 31(4), 153–158. Lincoln, Y.  S., & Guba, E.  G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage. Parsons, S. (1911). The case study method of teaching nursing. American Journal of Nursing, 11(11), 1009–1011. Stake, R.  E. (1995). The art of case study research. Thousand Oaks, CA: Sage. Yin, R. K. (2014). Case study research design and methods (5th ed.). Thousand Oaks, CA: Sage.

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CAUSAL MODELING

CAUSAL MODELING Causal modeling refers to a class of theoretical and methodological techniques used to examine cause-and-effect relationships, generally with nonexperimental data. Path analysis, structural equation modeling, covariance structure modeling, and LISREL (linear structural relations) modeling have slightly different meanings but are often used interchangeably with the term causal modeling. Path analysis usually refers to a model that contains observed variables rather than latent (unobserved) variables and is analyzed with multiple regression procedures. The other three terms generally refer to models with latent variables with multiple empirical indicators that are analyzed with iterative programs such as LISREL or EQS. A common misconception is that these models can be used to establish causality with nonexperimental data; however, statistical techniques cannot overcome restrictions imposed by the study’s design. Nonexperimental data provide weak evidence of causality regardless of the analysis techniques applied. A causal model is composed of latent concepts and the hypothesized relationships among those concepts. The researcher constructs this model a priori based on theoretical or research evidence for the direction and sign of the proposed effects. Although the model can be based on the observed correlations in the sample, this practice is not recommended. Empirically derived models capitalize on sample variations and often contain paths that are not theoretically defensible; findings from empirically constructed models should not be interpreted without replication in another sample. Most causal models contain two or more stages; they have independent variables, one or more mediating variables, and the final outcome variables. Because the mediating variables act as both independent and dependent variables, the terms exogenous and

endogenous are used to describe the latent variables. Exogenous variables are those whose causes are not represented in the model; the causes of the endogenous variables are represented in the model. Causal models contain two different structures. The measurement model includes the latent variables, their empirical indicators (observed variables), and associated error variances. The measurement model is based on the factor analysis model. A respondent’s position on the latent variables is considered to cause the observed responses on the empirical indicators, so arrows point from the latent variable to the empirical indicator. The part of the indicator that cannot be explained by the latent variable is the error variance generally due to measurement. The structural model specifies the relationships among the latent concepts and is based on the regression model. Each of the endogenous variables has an associated explained variance, similar to R2 in multiple regression. The paths between latent variables represent hypotheses about the relationship between the variables. The multistage nature of causal models allows the researcher to divide the total effects of one latent variable on another into direct and indirect effects. Direct effects represent one latent variable’s influence on another that is not transmitted through a third latent variable. Indirect effects are the effects of one latent variable that are transmitted through one or more mediating latent variables. Each latent variable can have many indirect effects but only one direct effect on another latent variable. Causal models can be either recursive or nonrecursive. Recursive models have arrows that point in the same direction; there are no feedback loops or reciprocal causation paths. Nonrecursive models contain one or more feedback loops or reciprocal causation paths. Feedback loops can exist among latent concepts or error terms. An important issue for nonrecursive models is the identification status. The

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identification status refers to the amount of information (variances and covariances) available, compared with the number of parameters that are to be estimated. If the amount of information equals the number of parameters to be estimated, the model is “just identified.” If the amount of information exceeds the number of parameters to be estimated, the model is “overidentified.” In both cases, a unique solution for the parameters can be found. With the use of standard conventions, recursive models are almost always overidentified. When the amount of information is less than the number of parameters to be estimated, the model is “underidentified” or “unidentified,” and a unique solution is not possible. Nonrecursive models are underidentified unless instrumental latent variables (a latent variable for each path that has a direct effect on one of the two latent variables in the reciprocal causation relationship but only an indirect effect on the other latent variable) can be specified. Causal models can be analyzed with standard multiple regression procedures or structural equation analysis programs, such as LISREL or EQS (see entry “Structural Equation Modeling”). Multiple regression is appropriate when each concept is measured with only one empirical indicator. Path coefficients (standardized regression coefficients, or betas) are estimated by regressing each endogenous variable on the variables that are hypothesized to have a direct effect on it. Fit of the model is calculated by comparing total possible explained variance for the just identified model with the total explained variance of the proposed overidentified model. Data requirements for path analysis are the same as those for multiple regression: (a) interval or near-interval data for the dependent measure; (b) interval, nearinterval, or dummy-, effect-, or orthogonally coded categorical data for the independent measures; and (c) five to 10 cases per independent variable. Assumptions of multiple regression must be met.

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In summary, causal modeling techniques provide a way to more fully represent the complexities of the phenomenon, to test theoretical models specifying causal flow, and to separate the effects of one variable on another into direct and indirect effects. Although causal modeling cannot be used to establish causality, it provides information on the strength and direction of the hypothesized effects. Thus, causal modeling enables investigators to explore the process by which one variable might affect another and to identify possible points for intervention.

JoAnne M. Youngblut

CEREBRAL ISCHEMIA Cerebral ischemia is inadequate blood flow to the brain necessary to meet metabolic and nutritive needs of the brain tissue (Edvinsson, MacKenzie, & McCulloch, 1993). The decrease or absence of blood flow that results from an obstruction or occlusion may result in neurological damage. The severity of cerebral ischemia depends on the severity and duration of the reduction in cerebral blood flow (CBF) adversely affecting various functional and metabolic processes as CBF decreases (Heiss & Rosner, 1983). The brain stores no oxygen and little glucose and is thus dependent on a constant supply of oxygen and glucose from the blood. Cerebral ischemia may be focal or global, depending on whether a part of the brain or the entire brain is ischemic. Focal cerebral ischemia occurs when a major cerebral artery becomes occluded or constricted from arterial spasm, emboli, or thrombosis. Global ischemia occurs from an overall decrease in CBF, for example, after cardiac arrest. Global oxygen deprivation of the brain may also occur as a result of asphyxia, anemia, hypoxia, or near drowning. Nurses are responsible for

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identifying individuals at risk for focal or global cerebral ischemia. Nursing assessment of early symptoms of cerebral ischemia can allow for intervention and minimize the probability of permanent damage. Spielmeyer first described “ischemic cell change” in 1922, and Brierley presented the time course for neuronal change during a low-flow state and provided evidence of the threshold for cerebral anoxic ischemia (Brierley, Brown, & Meldrum, 1971; Chiang, Kowada, Ames, Wright, & Majno, 1968). He observed and described in further detail the process of ischemic cell change (Brierley, Meldrum, & Brown, 1973). With the initial decrease in blood flow, oxygen, and/or glucose to the brain, the contour of cells, nucleus, and nucleolus remain unchanged. There is a disruption of mitochondria and an increase in the astrocyte processes surrounding the neurons. As the ischemic process continues, there is neuronal shrinkage, changes within organelles in the cytoplasm, and the cell is further surrounded by astrocytic processes. As the nucleus continues to shrink and the cytoplasm becomes more amorphous, incrustations begin to form. Finally, as the incrustations disappear and the cytoplasm becomes increasingly homogeneous, astrocytes proliferate and lipid phagocytes form in preparation for removal of the now “ghost cell.” As the flow lowers and the mitochondria fail, energy sources change from an aerobic to an anaerobic pathway, with a corresponding increase in lactic acid production, metabolic derangement, and loss of ion and transmitter homeostasis. If this process continues unchecked, there will be inadequate energy to maintain the sodium potassium pump across the cell membrane (Jones et al., 1981). Researchers have increasingly detailed the process in an attempt to identify and improve the brain’s tolerance to recover from an ischemic challenge. In the 16th century, Servetus first presented the idea that blood flowed through the lungs; he was burned at the stake for his efforts. Harvey (1578–1657) supported

Servetus’s findings by describing the flow of blood through the body. Nearly 200 years later, oxygen was discovered by Priestley, and Steele and Lavoisier made the connection that oxygen contributed to the production of “heat” or energy. Fick (1870) defined blood flow as the quantity of a substance, such as oxygen, that is taken up by a specific organ over a unit of time. The first “measures” of CBF involved direct and indirect observations of intracranial vessels (Roy & Sherrington, 1890). It was not until 1945, when Kety and Schmidt applied the Fick principle to diffusible gas, nitrous oxide, that one was able to estimate CBF (Kety, 1950; Kety & Schmidt, 1948). Kety was the first person to measure global CBF in humans using vascular transit time. The technique was modified by Lassen and Ingvar (1972) when Xe-133, a highly diffusible gas, was injected into the internal carotid artery. Multiple extracranial detectors traced the transit time of the radiation from the Xe-133 as it flowed through the brain, providing focal CBF measures. Diffusible tracers are now combined with tomographic reconstruction, such as CT, PET, or MRI to calculate vascular transit time. For example, stable xenon-enhanced CT scanning measures CBF via a conventional scanner interfaced with computer hardware and software and directs the delivery of xenon gas transit throughout brain regions. Serial CT scans are conducted during the inhalation of a gas mixture containing 30% xenon, 30% to 60% oxygen, and room air. The serial images are stored and regional flows are calculated. CBF is also estimated from measurement of cerebral blood volume. One way to estimate cerebral blood volume is using a gradient echo planar system on magnetic resonance systems. The dynamic contrastenhanced susceptibility-weighted perfusionimaging technique involves giving a bolus of paramagnetic contrast material (i.e., gadolinium). The contrast media are traced, and the amount of signal attenuation is proportional to the cerebral blood volume. With a series of

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multislice measurements, one may generate a time–density curve, and the area under the curve provides an index of relative blood volume (Grandin, 2003). Similar techniques are adapted to CT scanners with the capability for rapid sequential scanning. The threshold for irreversible brain damage from cerebral ischemia is generally defined as less than 20 mL/100 g of tissue/min (Jones et al., 1981; Yonas, Sekhar, Johnson, & Gur, 1989). CBF below this level alters the functioning of the mitochondria to produce energy. Studies show that the threshold for irreversible brain damage is volume and time dependent. Global brain ischemia that is sustained for longer than 4 to 5 minutes will result in permanent brain damage (Brierley et al., 1973). Little impairment occurs with more than 23 mL/100 g of tissue/min, and symptoms of neurologic impairment develop with less than 20 mL/100 g/min (Branston, Symon, Crockard, & Pasztor, 1974). Less than 18 to 20 mL/100 g/min of tissue, evidence of diminished electrical activity by evoked potentials or EEG occurs (Sundt, Sharbrough, Anderson, & Michenfelder, 1974). Less than 15 mL/ 100 g/min of tissue is considered to be a threshold for synaptic transmission (Astrup, Siesjö, & Symon, 1981). In addition, factors, including temperature, drug administration, and individual variation, contribute to the complexity of defining this threshold. Recent work focuses on methods that “noninvasively” detect, track changes in, or treat cerebral ischemia. The determination and prediction of cerebral ischemia is subject to the strengths and limitations of the technique used to detect low-flow states. As neuroimaging methodologies continue to evolve, our ability to detect low-flow states improve. For example, technological advances using dynamic perfusion CT imaging (Wright et al., 2016) or the integration of PET and MRI allow us to designate low-flow states with improved precision (Totaro et al., 2010; Wright et al., 2016) and improve a clinician’s

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ability to differentiate between cerebral infarct and ischemia (Saver, 2008). To date, there are no serum biomarkers or assays available that can detect the presence of cerebral ischemia; however, advances are being made in the identification of serum biomarkers associated with complications of cerebral ischemia and infarct, such as blood– brain barrier disruption (Asano, Chantler, & Barr, 2016; Maestrini et al., 2016). Ongoing studies are examining the temporal relationship between gene expression detected in peripheral blood and cerebral ischemia associated with brain damage and neurologic dysfunction. Future directions in cerebral ischemia include more specific and sensitive clinical criteria for stages of cerebral ischemia and infarction, noninvasive techniques to measure regional blood flow, and the development of assays of ischemia and/or infarct. As techniques become increasingly more portable and useable, there will be a translation from the radiology department to application by nurses in the community or at the bedside to assess, to predict, to identify, and to monitor patients at risk for cerebral ischemia.

Mary E. Kerr

Asano, S., Chantler, P. D., & Barr, T. L. (2016). Gene expression profiling in stroke: Relevance of blood–brain interaction. Current Opinion in Pharmacology, 26, 80–86. Astrup, J., Siesjö, B. K., & Symon, L. (1981). Thresholds in cerebral ischemia—The ischemic penumbra. Stroke, 12(6), 723–725. Branston, N. M., Symon, L., Crockard, H. A., & Pasztor, E. (1974). Relationship between the cortical evoked potential and local cortical blood flow following acute middle cerebral artery occlusion in the baboon. Experimental Neurology, 45(2), 195–208. Brierley, J. B., Brown, A. W., & Meldrum, B. S. (1971). The nature and time course of the neuronal alterations resulting from oligaemia and hypoglycaemia in the brain of Macaca mulatta. Brain Research, 25(3), 483–499.

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Brierley, J. B., Meldrum, B. S., & Brown, A. W. (1973). The threshold and neuropathology of cerebral “anoxic-ischemic” cell change. Archives of Neurology, 29(6), 367–374. Chiang, J., Kowada, M., Ames, A., Wright, R. L., & Majno, G. (1968). Cerebral ischemia. III. Vascular changes. American Journal of Pathology, 52(2), 455–476. Edvinsson, L., MacKenzie, E.  T., & McCulloch, J.  (1993). Cerebral blood flow and metabolism. New York, NY: Raven Press. Heiss, W. D., & Rosner, G. (1983). Functional recovery of cortical neurons as related to degree and duration of ischemia. Annals of Neurology, 14(3), 294–301. Kety, S. S. (1950). Blood flow and metabolism of the human brain in health and disease. Transactions & Studies of the College of Physicians of Philadelphia, 18(3), 103–108. Kety, S. S., & Schmidt, C. F. (1948). The nitrous oxide method for the quantitative determination of cerebral blood flow in man: Theory, procedure and normal values. Journal of Clinical Investigation, 27(4), 476–483. Lassen, N. A., & Ingvar, D. H. (1972). Radioisotopic assessment of regional cerebral blood flow. Progress in Nuclear Medicine, 1, 376–409. Maestrini, I., Ducroquet, A., Moulin, S., Leys, D., Cordonnier, C., & Bordet, R. (2016). Blood biomarkers in the early stage of cerebral ischemia. Revue Neurologique, 172(3), 198–219. Roy, C. S., & Sherrington, C. S. (1890). On the regulation of the blood-supply of the brain. Journal of Physiology, 11(1–2), 85–158.17. Saver, J. L. (2008). Proposal for a universal definition of cerebral infarction. Stroke, 39(11), 3110–3115. Sundt, T. M., Sharbrough, F. W., Anderson, R. E., & Michenfelder, J. D. (1974). Cerebral blood flow measurements and electroencephalograms during carotid endarterectomy. Journal of Neurosurgery, 41(3), 310–320. Totaro, P., Toni, D., Durastanti, L., Bozzao, L., Gualdi, G. F., Raz, E., . . . Pantano, P. (2010). Diffusion-weighted MRI in patients with non-diagnostic CT in the post-acute phase of cerebral ischemia. European Neurology, 63(2), 94–100. Wright, E. A., d’Esterre, C. D., Morrison, L. B., Cockburn, N., Kovacs, M., & Lee, T. Y. (2016). Absolute cerebral blood flow infarction threshold for 3-hour ischemia time determined with CT perfusion and 18F-FFMZ-PET imaging in

a porcine model of cerebral ischemia. PLOS ONE, 11(6), e0158157. Yonas, H., Sekhar, L., Johnson, D. W., & Gur, D. (1989). Determination of irreversible ischemia by xenon-enhanced computed tomographic monitoring of cerebral blood flow in patients with symptomatic vasospasm. Neurosurgery, 24(3), 368–372.

CHILD AND ADOLESCENT DELINQUENTS Juvenile delinquency continues to be the product of multiple and complex causes. Contemporary nursing science and practice has come to recognize the influence of social determinants of health on poor behavioral outcomes. Indicators of child well-being (i.e., economic and sociodemographic factors) directly and indirectly relate to youth crime and victimization. Juvenile persons younger than 18 years comprise 24% of the U.S. population, an estimated 74,181,500 persons (U.S. Census Bureau, 2010a). By 2050, the juvenile population is expected to be 16% more than in 2010, but only 21% of the total population. The racial and ethnic makeup of the population was classified as 76% White, 17% Black, 2% American Indian, and 5% Asian; and 23% of juveniles were of Hispanic ethnicity. The Census Bureau estimates that the Hispanic proportion of the juvenile population will near 30% by 2030 and 36% by 2050 (U.S. Census Bureau, 2010b). Chronic and extreme poverty, particularly for children who experience it from an early age, place those children at greater risk of serious delinquency (Hawkins et al., 2000). Almost half of the children who live with only their mother or with neither parent live in poverty (U.S. Census Bureau, 2010b). The effects of family structure have been demonstrated as a better predictor of problem

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behaviors than race or ethnicity or condition of the community (McCurley & Snyder, 2004). Not surprising, poor supervision and parental involvement have been identified as specific risk factors. There has been no notable change in education dropout rates over a 10-year period studied (3.4%), nor was there a difference noted by gender (male, 3.5%; female, 3.4 %) or among the various racial/ethnic groups: White non-Hispanic (2.4%), Black non-Hispanic (4.8%), and Hispanic (5.8%). However, for youth living in more financially secure homes, the dropout rates were dramatically lower (1.4% vs. 7.4%). Educational failure leads to future unemployment and contributes to the risks associated with delinquency. The incidence of institutionalization among high school dropouts is 63 times higher (Aud et al., 2011) compared with those who complete high school. In addition, data reveal that children who remain in school are less likely to be exposed to nonfatal crime experiences. It has long been known that childhood abuse and neglect is a strong predictor of problem behaviors in children. Currently, one out of 25 children in the United States is abused or neglected (Sedlak et al., 2010), a rate that has not changed over the past few years. Although the overall rates of abuse and neglect have not changed, there has been a shift in the types of maltreatment experienced by children. The rate of neglect, specifically emotional neglect, increased, largely related to exposure to domestic violence, which more than tripled from 2:1,000 children in 1993 to 7:1,000 children in 2005 to 2006 (Finkelhor, Turner, Ormrod, Hamby, & Kracke, 2009). Furthermore, children younger than 4 years, who comprise 34% of all victims, accounted for 79% of maltreatment fatalities. Boys had higher maltreatment fatality rates (2.51 deaths per 100,000) than girls (1.73 per 100,000). And, although most victims of fatalities were White (44%), rates were more than double for Black (3.91) and multiracial (3.65) children compared with White children (1.68

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per 100,000; U.S. Department of Health and Human Services [DHHS], 2011). Exposure to violence is dramatic in the lives of children and covers multiple categories of violence: conventional crime (e.g., kidnapping, robbery, and theft), child maltreatment, peer and sibling victimization, sexual victimization, witnessing crime and indirect victimization, school violence and threats, and Internet violence and victimization (Finkelhor, Turner, Hamby, & Ormrod, 2011). Although the rate of serious violence against youth 12 to 17 years old fell 69% between 2002 and 2010, polyvictimization rates remained highest among boys (54%) and non-Hispanic Black youth (41%) aged 14 to 17 year age group. Data indicate that 23% of the victims of serious violent crime reported to law enforcement agencies were against youth under age 18 years; 64% of these were for sexual assaults (Sickmund & Puzzanchera, 2014). It is interesting to note that many juveniles who commit crimes never enter the juvenile justice system (Sickmund & Puzzanchera, 2014), resulting in systematic underreporting and possible distortion in the scope and attributes of juvenile crime reported. Underreported health-risk behaviors that contribute to the leading causes of death, injury, and social problems among youth include physical fighting (selfreported by 33% of Black and Hispanic high school students) and illicit substance use (48%) with widespread use of alcohol and tobacco (Centers for Disease Control and Prevention [CDC], 2012). The prevalence of youth crime activities often associated with gangs has remained stable between 2006 and 2010 (Egley & Howell, 2013). Evidence provided from longitudinal study of serious juvenile offenders suggests that most do not make a career of crime, and original crimes do not predict future offending patterns (MacArthur Foundation, 2012). Furthermore, most serious juvenile offenders reduced their offending over time regardless of the intervention used. Based on self-reports

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of antisocial activities, the majority (92%) of adolescent serious offenders decreased or limited illegal activity during the first 3  years following their court involvement. Institutional placement and type of setting appear to have little effect on who continues with antisocial acts and who will desist. Once again, the effect of substance abuse is noted as having a strong relationship to offending behavior. The presence of a substance use disorder and the level of substance use are both strongly and independently related to the level of self-reported offending and number of arrests. Over a 7-year study period, youth with a substance use disorder and those who were heavy users were more likely to continue to offend and be arrested, and spent less time working or attending school (MacArthur Foundation, 2012). Interventions that showed substantial reduction in alcohol-, drug-, and nondrug-related offences included significant family involvement and treatment lasting for more than 3 months. Youth outcomes are positively impacted by the quality and matching of services to individual needs, and a positive institutional experience. Youth who received communitybased supervision and aftercare services following residential placement are more likely to remain successfully engaged in the community. Benefits increased for those who received transitional services (inside–outside model). This review of research highlights how adolescent risk taking and delinquent behavior result from an interaction between the normal developmental attributes of adolescence and the environmental influences of early childhood (National Research Council, 2013). We now know how strongly individual development is affected by the interplay between the brain and an adolescent’s environment. The likelihood and seriousness of offending, as well as the effects of interventions, are strongly influenced by social determinants of health, such as poverty and social supports. Such evidence has direct bearing on

public policy and the push to transform the justice system to implement a more developmentally appropriate way of handling youth who come to the attention of the juvenile justice system. Over the past 15 years, there has been an increase in the growth of the science of risk and protective factors, as well as of criminogenic factors and characteristics, increased use of evidence-based practices (EBPs) and programs, and in the development and use of validated assessment instruments. The importance of advancing youth work on an ecological platform and serving youth closer to home with family, using a strength-based approach, is known. The challenge is in translating the robust body of knowledge into practice. Lisey, Howell, Kelly, Chapman, and Carver (2010) suggest youth-centered programming that closely aligns services with the needs of the individual by combining both preventive and intervention strategies. Three approaches are suggested to translate research evidence on effective programs into practice: direct evaluation of each program to confirm its effectiveness, implement with fidelity programs with demonstrated evidence of effectiveness, and implement best practices guidelines shown effective through a metaanalysis of research findings. Yet, challenges to uptake remain—such as provider acceptance of EBPs, limited understanding of the difficulties associated with implementation, and underestimation of the power of inertia in clinical practice (Miller, Sorensen, Selzer, & Brigham, 2006). It is the strong, consistent, adaptive agency leaders and champions who advocate in support of change who are key to achieving sustainability. Leadership efforts that are symbolic of the future include codification of evidencebased criteria in legislation and in policy. Leaders seek to reconcile the gap between the public’s support of offender rehabilitation and the professional view of critical priorities for juvenile justice (Mears, Shollenberger, Willison, Owens, & Butts, 2010). The greatest gaps exist

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in perceived importance on issues of rehabilitation and system capacity for program and policy evaluation. Juvenile justice system reform, then, needs to focus on evidence integrated into a comprehensive strategy that deploys preventive and treatment programming for youth in a cost-effective manner that impacts health, welfare, and problem behaviors.

Deborah Shelton Aud, S., Hussar, W., Kena, G., Bianco, K., Frohlich, L., Kemp, J., & Tahan, K. (2011). The condition of education 2011 (NCES 2011-033). Washington, DC: U.S. Government Printing Office. Bonnie, R. J., Johnson, R. L., Chemers, B. M., & Schuck, J. A. (Eds). (2013). Reforming juvenile justice: A developmental approach. Committee on Assessing Juvenile Justice Reform. In Committee on Law and Justice, Division of Behavioral and Social Sciences and Education. Washington, DC: National Academies Press. Centers for Disease Control and Prevention. (2012). Youth risk behavior surveillance— United States, 2011. Morbidity and Mortality Weekly Report, 61(4). Retrieved from https:// www.cdc.gov/mmwr/preview/mmwrhtml/ ss6104a1.htm Egley, A., Jr., & Howell, J. C. (2013). Highlights of the 2011 National Youth Gang Survey. Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention [Online]. Retrieved from https://www.ojjdp.gov/pubs/242884.pdf Finkelhor, D., Turner, H., Hamby, S., & Ormrod, R. (2011). Polyvictimization: Children’s exposure to multiple types of violence, crime, and abuse (OJJDP Bulletin). Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Finkelhor, D., Turner, H., Ormrod, R., Hamby, S., & Kracke, K.  (2009). Children’s exposure to violence:  A  comprehensive national survey. Washington, DC:  U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Hawkins, J. D., Herrenkohl, T. I., Farrington, D. P., Brewer, D., Catalano, R.  F., Harachi, T.  W., & Cothern, L.  (2000). Predictors of youth violence.

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Washington, DC:  U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Lisey, M. W., Howell, J. C., Kelly, M. R., Chapman, G., & Carver, D. (2010). Improving the effectiveness of juvenile justice programs: A new perspective on evidence-based practice. Washington, DC: Georgetown Public Policy Institute, Georgetown University. MacArthur Foundation. (2012). Models for change: Research on pathways to desistance December 2012 update. Retrieved from https://www .modelsforchange.net/publications/357 McCurley, C., & Snyder, H. (2004). Risk, protection, and family structure. Pittsburgh, PA:  National Center for Juvenile Justice. Mears, D. P., Shollenberger, T. L., Willison, J. B., Owens, C. E., & Butts, J. A. (2010). Practitioner views of priorities, policies, and practices in juvenile justice. Crime & Delinquency, 56(4), 535–563. Miller, W. R., Sorensen, J. L., Selzer, J. A., & Brigham, J. S. (2006). Disseminating evidencebased practices in substance abuse treatment:  A  review with suggestions. Journal of Substance Abuse Treatment, 35, 25–39. Sedlak, A., Mettenburg, J., Basena, M., Petta, I., McPherson, K., Greene, A., & Li, S. (2010). Fourth National Incidence Study of Child Abuse and Neglect (NIS-4): Report to Congress. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families. Sickmund, M., & Puzzanchera, C. (2014). Juvenile offenders and victims: 2014 national report. Pittsburgh, PA: National Center for Juvenile Justice. U.S. Census Bureau. Current Population Survey. (2010a). Annual social and economic supplement. Table C-3: Living arrangements of children under 18 years and marital status of parents, by age, sex, race, and Hispanic origin and selected characteristics of the child for all children: 2010. Retrieved from https://www.census .gov/hhes/families/data/children.html U.S. Census Bureau. Current Population Survey. (2010b). Annual social and economic supplement. Table POV46: Poverty status by state. Retrieved from https://www.census.gov/ hhes/www/cpstables/032011/pov/toc.htm U.S. Department of Health and Human Services, Administration for Children and Families,

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Administration on Children, Youth, and Families, Children’s Bureau. (2011). Child maltreatment 2010. Retrieved from https://www .acf.hhs.gov/ programs/ cb/ stats_ research/ index.htm#can

CHILDBIRTH EDUCATION Childbirth education focuses on the learning needs of expectant families and covers a broad range of topics from the physical care needs of expectant women to the psychosocio-cultural needs of the new family. The goal of childbirth education is to assist families in acquiring the knowledge and skills necessary to achieve a healthy transition through the childbearing process and initial phases of parenthood. Classes range from courses designed for those considering pregnancy through courses dealing with infant care needs and early-parenting skills. Nurses are the professional practitioners who assume the primary responsibility of teaching childbirth education classes within the United States. Nurses are in a unique position to serve as childbirth educators because of their broad knowledge base, including both the biological and the behavioral sciences. In addition, nursing’s focus on caring and emphasis on client education enable nurses to guide families toward their childbirth goals with sensitivity using appropriate educational methods. Nurses are the health professionals within the hospital environment who provide the majority of hands-on care and labor support as well as postpartum and newborn instruction. Thus, nurses are in a strategic position to act as patient advocates and to provide anticipatory guidance regarding the birth decisions that are often required within an increasingly complex health care system. Formal childbirth education in the United States began with classes in hygiene, nutrition, and baby care provided by the

American Red Cross. During the early 20th century, classes on childbirth and family care became increasingly available to American women. As society’s view of childbirth shifted from the female-controlled social model to the medical illness model during the first half of the 20th century, the focus of classes turned to the management of childbirth pain (Ondeck, 2000). Contemporary childbirth education dates back to the work of Dick-Read, Lamaze, and Bradley. The notion of pain during labor as secondary to fear and the use of psychological conditioning methods to reduce both the fear and the pain became the basis for “natural childbirth.” Although philosophical differences still exist among childbirth education methods, common aspects of all programs include education on (a) the physical process of labor, (b) physical and psychological conditioning methods, and (c) supportive assistance from significant others during the birthing process. A number of organizations have affected the progress of childbirth education in the United States. Lamaze International, formerly the American Society of Psychoprophylaxis in Obstetrics, was organized in 1960. The American Society of Psychoprophylaxis in Obstetrics began certifying childbirth educators in 1965 and offered one of the first attempts to provide consistency in quality of childbirth education. The International Childbirth Education Association was also founded in 1960 as a consumer group in New York City. It was devoted to a philosophy of consumers working with health professionals for the benefit of the laboring family (Ondeck, 2002). The American Academy of Husband Coached Childbirth was established in 1970 to certify childbirth educators in the Bradley method of childbirth. Bradley method educators are proponents of unmedicated childbirth with significant husband/ partner involvement (Monto, 1996). A number of related keywords were used to search the Cumulative Index to Nursing and Allied Health Literature (CINAHL),

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PubMed, and PsychINFO databases for nursing research and evidence-based practice articles published between 2011 and 2016. Search terms (with respective number of research and evidence-based practice articles in parentheses) included: childbirth education (424 and 81), childbirth education classes (68 and 9), childbirth education fathers (10 and 2), childbirth education and positive birth outcomes (12 and 2), prepared childbirth (education) (42 and 11), and childbirth preparation (23 and 1). The range of research topics relates to (a) postpartum skills, such as parenting and breastfeeding; (b) classes for special populations, such as fathers; (c) examination of the benefits of childbirth education on birth outcomes; (d) success of self-care measures during pregnancy and labor; (e) effects of childbirth education on the need for medical interventions, such as cesarean delivery; (f) parental and birth coach perceptions of childbirth education needs and satisfaction; (g) optimizing teaching strategies; and (h) use of the media (Internet, videos, and smartphone apps) for childbirth education. Quantitative research articles dominate the list. Quasi-experimental and correlational methods predominated in the quantitative studies; however, several randomized control trials were noted. As in previous years, grounded theory and phenomenology were the preferred qualitative research methods with an increasing number of ethnographic studies. In addition, a number of mixed-method studies were identified. Evidence-based practice articles are becoming more evident. Systematic reviews and quality-improvement reports related to new programs are increasingly available to practitioners. Very few authors identified a specific theoretical framework. However, several frameworks are noted, such as the Roy Adaptation Model, Bandura’s self-efficacy model, and Lazarus and Folkman’s stress and coping theory. There is a rise in the number of research articles focusing on expectant fathers. Themes generally focused on increasing the

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participation of fathers during and following childbirth education classes. Widarsson, Engström, Tydén, Lundberg, and Hammar (2015) identified a theme of “paddling upstream,” whereby fathers found participation in the childbirth experience to be a struggle. Both the health care and the prenatal education systems are focused on the mother’s needs and traditional gender roles resulting in a perception of gender-related biases. The use of electronic sources for childbirth education continues to be a growing focus of research. In addition to examining the impact of the Internet as a means of obtaining childbirth education, attention has been given to examining the use of other electronic information avenues, such as social media, smartphones, and a variety of apps. Fleming, Vandermause, and Shaw (2014) report that mothers are using a wide variety of electronic means to both prepare for birth and during the childbirth process. Fathers were reported to be less involved with seeking education via electronic means. However, the wide variety of information available, some of unknown quality, was reported to be potentially harmful and anxiety provoking. The benefits of childbirth education continue to be a focus for nurse researchers with a continued focus on pain relief and birth outcomes. Guszkowska (2014) found that a prenatal exercise program has a more beneficial effect on fear of childbirth than traditional childbirth education classes. In addition, control of labor pain relief was seen to be under the control of the health care providers, particularly in the traditional education group. Stoll, Edmonds, and Hall (2015) report that women having more access to childbirth education and more confidence in their knowledge were less likely to report fear of childbirth and less likely to desire a cesarean section. Serçekus and Başkale (2016) report similar findings of a reduction in fear and increase in self-efficacy related to childbirth.

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An emerging concept in the childbirth education literature is mindfulness training during pregnancy and childbirth education classes. Fisher, Hauck, Bayes, and Byrne (2012) found that a mindfulness-based childbirth education program facilitated expectant parents’ sense of control in labor as well as their participation in decision making. In addition, Byrne, Hauck, Fisher, Bayes, and Schutze (2014) report a significant improvement in self-efficacy, fear, and anxiety scores in parents participating in mindfulness education. The increase in the global nature of nursing research on childbirth education is evident. A wide variety of countries on six continents are represented in the nursing research literature. Many of these studies are based on ethnographic designs and contribute muchneeded information on the needs and perceptions of a variety of ethnic groups. Although topics show a wide conceptual scope of interest, little depth is currently available. Notable topics lacking in the recent research and evidence-based practice literature include the impact of childbirth education classes on childbirth complications and the postnatal experience of parents following preparatory courses. Topics in this area might include the needs of those scheduled for repeat or primary cesarean section, childbirth needs of mothers with medical conditions such as preeclampsia or diabetes, needs of mothers with a previous history of postpartum mood disorders, and so forth. Although the expectant father has received more attention in recent years, there continues to be a concern for gender issues related to childbirth with the needs of the expectant father underrepresented in the literature. In addition, the information available on tailoring childbirth education to the needs of vulnerable populations is scant despite the continued discrepancies noted in pregnancy outcomes for minority and marginalized

groups. Spirituality needs of the expectant family are rarely mentioned in the research literature. Attention to the spiritual needs associated with childbirth may be fruitful as a concept to explore related to the childbirth education needs of families.

Bobbe Ann Gray Byrne, J., Hauck, Y., Fisher, C., Bayes, S., & Schutze, R. (2014). Effectiveness of a mindfulness-based childbirth education pilot study on maternal self-efficacy and fear of childbirth. Journal of Midwifery & Women’s Health, 59(2), 192–197. Fisher, C., Hauck, Y., Bayes, S., & Byrne, J. (2012). Participant experiences of mindfulness-based childbirth education:  A  qualitative study. BioMed Central Pregnancy and Childbirth, 12, 126. Fleming, S., Vandermause, R., & Shaw, M. (2014). First time mothers preparing for birth in an electronic world:  Internet and mobile phone technology. Journal of Reproductive Health and Infant Psychology, 32, 240–253. Guszkowska, M. (2014). The effect of exercise and childbirth classes on fear of childbirth and locus of labor pain control. Anxiety, Stress, and Coping, 27(2), 176–189. Monto, M. A. (1996). Lamaze and Bradley childbirth classes: Contrasting perspectives toward the medical model of birth. Birth, 23(4), 193–201. Ondeck, M. (2000). Historical development. In F. H. Nichols & S. S. Humenick (Eds.), Childbirth education. Practice, research, and theory (pp. 18–31). Philadelphia, PA: Saunders. Serçekus, P., & Baskale, H. (2016). Effects of antenatal education on fear of childbirth, maternal self-efficacy and parental attachment. Midwifery, 34, 166–172. Stoll, K., Edmonds, J. K., & Hall, W. A. (2015). Fear of childbirth and preference for cesarean delivery among young American women before childbirth: A survey study. Birth, 42(3), 270–276. Widarsson, M., Engström, G., Tydén, T., Lundberg, P., & Hammar, L. M. (2015). “Paddling upstream”: Fathers’ involvement during pregnancy as described by expectant fathers and mothers. Journal of Clinical Nursing, 24(7–8), 1059–1068.

CHILD LEAD EXPOSURE LEVELS

CHILD LEAD EXPOSURE LEVELS It is estimated that more than half a million American preschool children suffer from a blood lead level (BLL) more than 5 mcg/ dL (American Academy of Pediatrics [AAP], 2016), the level the Centers for Disease Control and Prevention (CDC) considers to cause risks for children. By lowering the reference value BLL from 10 mcg/dL to 5 mcg/dL in 2012, the CDC recognized a ninefold increase in lead-exposed children. In other words, there are a significant amount of children who are exposed to low levels of lead. These children were previously unreported and therefore no action was taken to decrease their exposure to lead. Acknowledging these low levels may allow parents, educators, and health care providers to work together to remediate the sources of lead, which may have previously been ignored (Leafe, Irigoyen, DeLago, Hassan, & Braitman, 2015). Past modifications have been made to decrease the amount of lead found in the United States: removal of lead from residential paint and gasoline, changing lead pipes to those made with polyvinyl chloride, and decreasing imported ceramics. Although no lead exposure is considered safe, decreased cognition has been noted in children with a BLL as low as 5 mg/dL (AAP, 2016). Exposure to environmental lead begins in the prenatal period, when physiologic stress mobilizes lead from its storage in the maternal bone into the blood. From here, it easily crosses the placenta and is deposited in fetal tissue (Cleveland, Minter, Cobb, Scott, & German, 2008a, 2008b). For this reason, it is recommended that pregnant women and women of child-bearing age be mindful of potential lead exposures in their home and work environments. In addition, by recognizing these concerning sources of lead, the exposure can be minimized as infants and children are introduced to their developmental environment. Absorption of lead

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is dependent on age and nutritional status; young children and those who have diets high in fats are most susceptible. Any child in a lower income family or living in deteriorating housing is at increased risk for high lead levels (American Academy of Pediatrics Committee on Environmental Health, 2005). Lead-based paint was commonly used in homes until 1978, when the federal government banned lead-containing paint for consumers. Lead-risk screening tools reflect on the age of the home that the child lives in, as there is a correlation between the age of the home and the BLL. In fact, nearly 40% of the houses built in the United States before 1960 contain lead-based paint (AAP, 2016). As lead is most commonly ingested through the exposure to lead-contaminated paint and the resulting dust, soil, and paint chips, the ban of lead-based paint has decreased this exposure. Once ingested, lead is distributed in the blood and eventually is deposited in the bones and teeth. At high, constant levels, this ingestion results in irreversible health issues. The deleterious effects of lead exposure have been known for 100 years; however, progress in prevention has been slow. Some of the reasons for this are related to society’s indifference to problems of poor and vulnerable populations (Yeoh, Woolfenden, Wheeler, Alperstein, & Lanphear, 2009). A magnitude of health problems are more likely to occur in children with BLLs greater than 5 mcg/ dL. At higher exposures (BLL >20 mcg/dL), damage to the nervous, hematopoietic, endocrine, and renal systems may occur. At lower level exposures, health problems may include altered cognitive and neurobehavioral processes, including learning disabilities, intellectual impairment, and antisocial behavior. Researchers have demonstrated that some of these effects may be seen in children with BLL as low as 3 mcg/dL (Bellinger, 2004; Canfield et al., 2003; Chiodo, Jacobson, & Jacobson, 2004; Lanphear, 2005; Lanphear, Deitrich, Auinger, & Cox, 2000; Needleman & Landrigan, 2004).

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Lead exposure was previously thought to be a problem reserved for poor innercity minority populations. It was previously believed that poor parenting contributed to the problem. Many considered the elimination of lead in gasoline and paint sufficient to eradicate the problem of lead poisoning. In 1991, the CDC issued comprehensive guidelines for preventing and treating the problem of childhood lead exposure. These guidelines were issued after the CDC accumulated large amounts of scientific evidence from animal and human studies that supported the hypothesis that the deleterious effects of lead exposure occur at levels previously thought to be harmless. The guidelines were updated in 2005 and emphasize the need for effective strategies to eliminate environmental lead hazards and a policy for universal screening of BLLs for infants, children, adolescents, and pregnant women was established. Only a few years later, in 2012, the positive BLL was lowered to 5 mcg/dL, as even low levels of lead were noted to affect children. As a result of the changes made since the turn of the century, the direct results of primary and secondary efforts at prevention of lead toxicity have significantly reduced the BLL among young U.S. children. This reduction is of particular importance as the major sources of environmental lead exposure have been greatly decreased through the elimination of lead in gasoline, the banning of lead-based paint for residential use, and the elimination of lead solder from food and beverage cans in the 1970s. Although this environmental removal has decreased lead exposure, the CDC recognizes that children who are African American, living in poverty, enrolled in Medicaid, and/or living in older housing built (before 1978) have the highest risk for lead exposure and therefore lead poisoning. Although few nurse researchers have examined the effects of low-level lead exposure on the neurobehavioral development of children, low-level lead exposure certainly falls within the realm of the phenomena of

concern to the discipline. Lead exposure is unquestionably of clinical significance; until all lead is abated from the environment, clinicians will be faced with screening children for lead exposure, preventing exposure through educational efforts with families and the community, and treating the effects of this preventable public health problem. Gibson, Love, Hardie, Bancroft, and Turner (1892) were some of the first providers to identify childhood lead poisoning. An association of symptoms was seen between chronic high levels of lead in adult patients and a young child with previously idiopathic peripheral paralysis. Gibson et al. hypothesized that the source of the lead poisoning was paint, and they described the long-lasting effects of the exposure. Because the belief of the time was that lead poisoning was an acute illness with no long-term repercussions, Gibson and colleagues’ opinions were ignored. It was not until the early 1970s that cross-sectional and longitudinal studies of low-level lead exposure were conducted. These early studies of lead exposure involved comparisons of a lead-exposed group and a comparison group on intelligence test measures. As knowledge accumulated and research strategies became more sophisticated, researchers began to assess the influence of covariates, such as parental intelligence, socioeconomic status, and parental education level (Gatsonis & Needleman, 1992). Although conflicting results were common, lead exposure and neurobehavioral deficits remained significantly associated. The earliest studies of lead poisoning were conducted on children who had a BLL of 60 mcg/dL or more and were symptomatic. During the 1970s, researchers focused on asymptomatic children who had a BLL in the range of 40 mcg/dL to 50 mcg/dL. Conclusions about the effects of lead exposure were difficult to make from these studies because of their methodological shortcomings. In 1979, researchers conducted a major investigation of large cohorts of asymptomatic children and used

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shed deciduous teeth rather than BLLs to measure lead exposure (Needleman et al., 1979). These researchers controlled for major confounding variables and concluded that a BLL was associated with lower IQ, decreased attention span, and poor speech and language skills in the children studied. Long-term follow-up of these children led the researchers to conclude that the effects of low-level lead exposure (equivalent to BLL ≤25 mcg/dL) persisted throughout young adulthood; failure to complete high school, reading disabilities, and delinquency were behaviors exhibited by children who had elevated BLLs at age 7 years (Needleman, Riess, Tobin, Biesecker, & Greenhouse, 1996). Scientists criticized the work done by Needleman et al. (1979) because the study lacked baseline data about early cognitive abilities of the subjects. For instance, it was proposed that the affected children may have had neurological deficits at birth that would lead them to certain behaviors (increased mouthing) that predisposed them to be lead exposed. To address this issue, subsequent studies were designed to follow large numbers of subjects from birth through early school age, and major outcomes (e.g., IQ level, motor development, cognitive development) were measured and large numbers of covariates were controlled. Numerous investigators using comparable designs reported similar findings; thus, a solid consensus among investigators began to emerge that lead was toxic at extremely low concentrations. Research with lead-exposed primates strengthened the consensus. The toxic level of lead was initially redefined by the CDC as a BLL of 10 mcg/dL or less and has more recently been defined as a BLL of 5 mcg/dL or less. Recently, nurse researchers have used Dixon’s Integrative Environmental Health Model (Dixon & Dixon, 2002) to identify knowledge gaps related to public policy that have prevented the development of effective strategies to create environmental lead-exposure policy change (Perron & O’Grady, 2010).

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Researchers continue to study the effects of low-level lead exposure on the development of infants, children, and adolescents. Longitudinal studies involving large and diverse populations that involve standardized measurement and control of known confounders will need to be undertaken. Although these efforts are worthwhile, future efforts also could focus on (a) identifying mediators of lead exposure effects, (b) investigating the effects of strategies to lower BLLs (chelation and environmental lead abatement) on the neurobehavioral outcomes of children, (c) investigating the synergistic effects of other environmental exposures on neurocognitive development, (d) investigating the effects of educational strategies to inform parents about preventing or reducing environmental lead exposure, and (e) looking into reducing the notable BLL to 3 mcg/dL or even 0 mcg/dL due to the belief that any lead exposure is bad exposure. Furthermore, investigations of the effectiveness of earlyintervention strategies for children identified with elevated lead levels need to be conducted. The continued efforts of preventing lead exposure will help to protect millions of children against the long-lasting effects of lead exposure.

Jennifer L. Nahum American Academy of Pediatrics. (2016). Lead exposure and lead poisoning. Retrieved from https://www.aap.org/en-us/about-the-aap/ aap-press-room/pages/With-No-Amount-of -Lead-Exposure-Safe-for-Children,-American -Academy-of-Pediatrics-Calls-For-Stricter -Regulations.aspx American Academy of Pediatrics Committee on Environmental Health. (2005). Lead exposure in children:  Prevention, detection, and management. Pediatrics, 116(4), 1036–1046. Bellinger, D. C. (2004). Lead. Pediatrics, 113(Suppl. 4), 1016–1022. Canfield, R. L., Henderson, C. R., Cory-Slechta, D. A., Cox, C., Jusko, T. A., & Lanphear, B. P. (2003). Intellectual impairment in children with blood lead concentrations below 10 microg

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per deciliter. New England Journal of Medicine, 348(16), 1517–1526. Centers for Disease Control and Prevention. (1991). Preventing lead poisoning in young children. Atlanta, GA:  U.S. Department of Health and Human Services. Chiodo, L. M., Jacobson, S. W., & Jacobson, J. L. (2004). Neurodevelopmental effects of postnatal lead exposure at very low levels. Neurotoxicology and Teratology, 26(3), 359–371. Cleveland, L. M., Minter, M. L., Cobb, K. A., Scott, A. A., & German, V. F. (2008a). Lead hazards for pregnant women and children:  Part  1. American Journal of Nursing, 108(10), 40–49. Cleveland, L. M., Minter, M. L., Cobb, K. A., Scott, A. A., & German, V. F. (2008b). Lead hazards for pregnant women and children: Part 2: More can still be done to reduce the chance of exposure to lead in at-risk populations. American Journal of Nursing, 108(11), 40–47; quiz 47. Dixon, J. K., & Dixon, J. P. (2002). An integrative model for environmental health research. Advances in Nursing Science, 24(3), 43–57. Gatsonis, C. A., & Needleman, H. L. (1992). Recent epidemiologic studies of low-level lead exposure and the IQ of children: A meta-analytic review. In H. L. Needleman (Ed.), Human lead exposure (pp. 243–255). Boca Raton, FL: CRC Press. Gibson, J. L., Love, W., Hardie, D., Bancroft, P., & Turner, A. J. (1892). Notes on lead poisoning as observed among children in Brisbane. In L. Huxtable (Ed.), Transactions from the Third Intercolonial Medical Congress of Australasia (pp. 76–77). Sydney, Australia: Charles Potter. Lanphear, B. P. (2005). Childhood lead poisoning prevention:  Too little, too late. Journal of the American Medical Association, 293(18), 2274–2276. Lanphear, B. P., Dietrich, K., Auinger, P., & Cox, C. (2000). Cognitive deficits associated with blood lead concentrations 70 years undergoing cardiac surgery. American Journal of Cardiology, 111(1), 137–142. Xiong, G. L., Jiang, W., Clare, R., Shaw, L. K., Smith, P. K., Mahaffey, K. W., . . . Newby, L. K. (2006). Prognosis of patients taking selective serotonin reuptake inhibitors before coronary artery bypass grafting. American Journal of Cardiology, 98(1), 42–47. Yin, Y. Q., Luo, A. L., Guo, X. Y., Li, L. H., & Huang, Y. G. (2007). Postoperative neuropsychological change and its underlying mechanism in patients undergoing coronary artery bypass grafting. Chinese Medical Journal, 120(22), 1951–1957.

COST ANALYSIS OF NURSING CARE Cost analysis of nursing care reflects a body of administrative studies that focus on quantifying nursing costs needed to deliver care to individual clients or aggregates in a variety of settings, using a variety of practice models and analysis tools. All cost analysis is based on assumptions that must be examined and made explicit when reporting findings. Much of the research on cost analysis of nursing care has focused on “costing out”

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nursing services for the purpose of measuring productivity, comparing costs of various nursing delivery models, charging individual patients for true nursing costs, and relating nursing costs to other cost models, most notably diagnostic-related group categories. The need and the motivation for these costing efforts have evolved with the economic underpinnings of the health care system, as have the methodologies and focuses of the settings. Cost analysis of nursing care focuses on justifying the cost-effectiveness of professional practice models, evaluating redesign efforts, and monitoring and controlling nursing costs within an ever-tightening, cost-conscious health care environment. Within the context of rising capitation penetration, cost analysis is essential to accurate capitation bidding and financial viability of the parent organization. As “best practices” benchmarking pushes the envelope of competitive bidding, demonstrating cost-effective nursing practice becomes essential to securing managed care contracts. Cost analysis research is a type of nursing administrative research that evaluates aspects of the delivery of nursing care. Cost analysis studies have been relevant to decision making by nursing administrators in selecting delivery models, treatment protocols, and justifying budgets, but such studies may become central to the survival of the entire profession for the future. Questions of appropriate skill mix cannot be determined solely on the basis of a cost per hour of service, cost per case, or cost per diagnostic-related group. Studies that combine traditional cost analysis with differential outcome analysis to secure a larger picture of the “true cost–benefit ratio” for specific nursing models are more appropriate. Recently, cost analysis has evolved to include the costs and factors associated with forfeiting reimbursement for poor patient outcomes under the Affordable Care Act (ACA). As hospitals compete with one another for an ever-increasing pool of money for best patient outcomes within the ACA, cost analysis of models to provide this competitive edge will merge.

The most notable characteristic of cost analysis studies is the variety of definitions, variables, and measurement tools used in the studies. Length of stay and nursing turnover are major variables included in cost studies. A major area of dispute for costing studies is the lack of a standard nursing acuity measure because of the proprietary nature of most acuity systems. Cost and efficiency of nursing procedures or treatments continue to be studied. Another important area for cost analysis is evaluation of cost differences among professional practice models. However, most of these studies use proprietary practice models that are difficult to duplicate in other settings. Variables are identified in these studies that do impact nursing costs, such as nursing turnover, ratio of productive to nonproductive hours, and nursing satisfaction. Given the growth of capitation, cost analysis of nursing services will need to take new directions. As critical pathways (benchmark performance tools) evolve as care guides, the costs of pathway changes on nursing delivery, patient outcomes, and case costs must be calculated. What are the most efficient and effective pathways toward resolution of a given health problem? What practice setting is appropriate for patients at each step of the pathway? For example, when is it safe to transfer a fresh open-heart-surgery patient from critical care to a step-down environment? (Earliest transfer to a least costly delivery mode saves money.) These calculations may be critical for institutions to secure managed care contracts in a cost-competitive environment. Determining what activities can be safely eliminated from a pathway without negatively impacting care outcomes will have cost and resource savings as we move to “best demonstrated practices.” Finally, we must move toward a cost– benefit analysis model that incorporates the outcomes of practice. The financial reality of competitive reimbursement pools for the ACA makes it imperative that institutions identify ways to better balance cost and quality so that they maximize imbursement. In addition, we need to further quantify the

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costs of increased patient mortality and failure to rescue that are associated with changes in nurse/patient ratios and the level of nursing qualifications.

Mary L. Fisher

CRITICAL CARE NURSING The development of critical care as a specialty is fairly recent, paralleling the growth and development of intensive care units (ICUs) in the 1960s and 1970s. The first ICUs were areas in the hospital designated for the care of patients recovering from anesthesia who required close monitoring during a period of physiological instability. Recognition of the efficiency and effectiveness that was gained from segregating any patients who required intensive nursing care for a short period of time was spurred by experiences in managing groups of critically ill patients, such as those injured in the Boston Cocoanut Grove fire of 1942 and victims of the polio epidemics of the 1950s (Lynaugh & Fairman, 1992). The development of the mechanical ventilator and the technological advances in coronary care led to recognition of the need for specialized skill and knowledge among nurses caring for these patients. The American Association of CriticalCare Nurses (AACN) has played a major role in encouraging research through its own small grants program, through joint funding initiatives with corporations. AACN publishes the American Journal of Critical Care, a scientific research journal, and Critical Care Nurse, a clinical journal featuring research. AACN also publishes evidence-based resources for the clinical practitioner, including a monthly magazine, AACN Bold Voices, and a weekly electronic newsletter. The other nursing journals publishing critical care

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research include Heart and Lung, Nursing Research, and Biological Research for Nursing. Nurse researchers have increasingly published in medical research journals, such as Critical Care Medicine, published by the Society of Critical Care Medicine (SCCM). Yet, in spite of the evolving interdisciplinary nature of major professional critical care societies, leaders of these societies recognized in 2009 that there was no consensus on the agenda for critical care research in the United States. Thus the four largest U.S. professional societies involved in critical care—the AACN, the American College of Chest Physicians (ACCP), the American Thoracic Society (ATS), and the SCCM—gathered to formally establish the Critical Care Societies Collaborative (CCSC) to explore shared common research issues (Deutschman, Ahrens, Cairns, Sessler, & Parsons, 2012). Experts from each of the four CCSC societies created a clinical research collaborative, the U.S. Critical Illness and Injury Trials Group (USCIITG), and formed the Multisociety Strategic Planning Task Force for Critical Care Research. The purpose of the task force was to identify and develop a comprehensive agenda for critical care research generated from feedback from a broad range of stakeholders. The task force identified key overarching themes and challenges to research, including (a) the insulating effect of conducting research in “silos,” (b) the absence of linkages among diverse areas of research, (c) the impact of phenotypic heterogeneity on the complexity of critical illness and severe injury, and (d) the critical need for infrastructure support of clinical research. Research priorities were categorized under major concentrations, starting with the goals of basic science and cellular research: (a) delineation of factors transforming a normal stress response into critical illness; (b) investigation of the role of the host response in initiation, transition, and resolution of critical illness; (c) description of the microbiome in healthy persons, and its role and transitions in critical illness; and (d) integration of research into

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the biology of tissue repair with investigation into mechanisms underlying critical illness (Deutschman et al., 2012). Translational research from basic science should aim to integrate studies of mechanisms of critical illness and interventions, based on rigorous standardized methodology and study design, while attempting to account for the effects of treatment/management on disease progression. Clinical research priorities identified by the task force reflect a growing concern by critical care leaders to broaden the scope of inquiry beyond the strictly pathophysiological aspects of critical illness. Through testing the effectiveness of interventions to treat distressing patient symptoms, such as pain, fatigue, dyspnea, confusion, and delirium, as well as family symptoms, such as anxiety, depression, and stress disorder, the task force noted the increasing urgency of initiating quality palliative and end-of-life care among critically ill patients. The task force broadened the mission of critical care research beyond the bedside to the quality of the environment of care, reflecting AACN’s priority for creating a healthy work environment, a theme that includes the need to develop reproducible metrics for quality-improvement processes, to assess strategies that enhance communication and coordination of health care delivery, and to test tools and methods, such as central line checklists and multidisciplinary rounds, that aim to improve sharing of knowledge, application of knowledge, promotion of a positive learning environment, and reduction of cognitive overload, errors, and burnout. The task force recognized the need for interprofessional, evidence-based research in the delivery of critical care education and training, through the incorporation of scientific evidence from the diverse fields of cognitive psychology, systems engineering, and social science. According to the task force, the relative importance of critical factors, such as team interactions, deliberate practice, patient assessment, and debriefing in

simulation, should be explored. Such efforts in team-based learning may help to examine the differences between high-performing and low-performing units, as well as to determine which scenarios of team-based learning have the greatest value for patient outcomes. In 2012, in response to the Institute of Medicine (IOM’s) The Future of Nursing report, AACN launched an innovative program designed to empower bedside nurses as clinician leaders and change agents whose initiatives measurably improve patient outcomes with bottom-line impact to the hospital (Aylett, 2012). The AACN Clinical Scene Investigator Academy, otherwise known as the AACN CSI Academy, joined with selected hospitals with the goal of developing enhanced skills in leadership, project management, and social entrepreneurship in the bedside nurse. Implemented over a 16month program and conducted in the nurses’ local community, a team of up to four nurses work with a CSI faculty member, an internal mentor, and the chief nursing officer to identify critical patient care areas of inquiry and implement unit-based projects with the goal of achieving quantifiable improvements in patient outcomes and decreases in hospital expenses. Ideally, learning is integrated into the nurses’ existing patient care responsibilities. In a staged rollout over 3 years, the AACN CSI Academy provided each participating hospital with a $10,000 implementation grant to support the teams’ learning and project implementation. In the pilot program, initiatives developed by the nurse participants resulted in substantial improvements in patient outcomes, including an 80% reduction in heel ulcers at one hospital and significant reductions in communication errors, medical errors, and injury-causing falls at another (Aylett, 2012). Across the seven hospitals participating in the program, the nurseled projects were also reported to have saved $2.6 million. Once the program was extended to 42 hospitals nationwide, it was reported that the 163 CSI Academy critical care nurses

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developed patient care projects that not only improved the patient outcomes but also produced potential financial savings of more than $28 million annually (Advance Healthcare Network for Nurses, 2015). Among the other outcomes, improvement projects were reported to have demonstrated decreases in: 1. ICU and progressive care unit (PCU) lengths of stay by 1.0 day 2. Days on mechanical ventilation by 14% or approximately by 1.0 day 3. Health care–acquired infections and ICU complications by 50% 4. Patient falls by 50% 5. Pressure ulcers by 40% 6. Catheter-associated urinary tract infections by 70% 7. Confusion assessment method for the ICU (CAM-ICU) positive scores by 14% In its report titled, Crossing the Quality Chasm, the IOM estimated that developing evidence to improve clinical practice and disseminating that evidence to be used by clinicians for improving patient outcomes takes on an average 17 years (IOM, 2001; Munro & Savel, 2016). In their editorial on this problematic time lag, Munro and Savel (2016) note of the accomplishments of the AACN CSI Academy and their many projects to speed up the translational process. For example, these authors point out that although early mobility in the ICU has been the subject of research for less than a decade, more than 30 mobility protocols have already been widely implemented. One of the most important recent development is the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3; Singer et al., 2016). Given that sepsis is a leading cause of mortality and critical illness worldwide (Fleischmann et al., 2016; Vincent et al., 2014), and is a serious predictor of long-term cognitive impairment and functional disability among survivors (Iwashyna, Ely, Smith, & Langa, 2010), the theoretical

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mechanisms and clinical pathogenesis of sepsis, and its evolution to septic shock and multiple organ dysfunction syndrome (MODS), has long perplexed critical care researchers and clinicians alike. It has been 15 years since the last sepsis consensus conference occurred in 2001 (Levy et al., 2003). In a recent commentary by one of the major authors of the new guidelines, Deutschman (2016) opined that theoretically, we still do not what sepsis is, what its essence is in the ontological sense; the conference guidelines concluded that based on the best available evidence, sepsis can be defined as a syndrome characterized by “life-threatening organ dysfunction caused by a dysregulated host response to infection” (Singer et al., 2016, p. 804). Yet, because no gold standard diagnostic test for sepsis exists, this pathobiological definition of sepsis does not help the clinician treat the patient. Although it is known to involve the early activation of both pro- and anti-inflammatory responses, it has also been shown to possess linkages with major disruptions in nonimmunologic pathways such as cardiovascular, neurological, autonomic, hormonal, bioenergetic, metabolic, and coagulation, all of which have prognostic significance (Singer et al., 2016). Thus, through a painstaking, detailed, and rigorous process, the task force turned from seeking a definition, which cannot yet be operationalized, to the option of seeking clinical criteria for sepsis that were clear and fulfilled multiple domains of usefulness and varied forms of validity, including construct, predictive, ecologic, and Delphi consensus methods. As the theoretical definition of sepsis emphasizes organ dysfunction, the task force agreed that the following clinical criteria apply to the sepsis syndrome, as measured by the Sepsis-Related Organ Failure Assessment (SOFA) score (Vincent et al., 1996):

Organ dysfunction can be identified as an acute change in total SOFA score of 2 or more points consequent to the

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infection. The baseline SOFA score can be assumed to be zero in patients not known to have preexisting organ dysfunction. A  SOFA score of 2 or more reflects an overall mortality risk of approximately 10% in a general hospital population with suspected infection. Even patients presenting with modest dysfunction can deteriorate further, emphasizing the seriousness of this condition and the need for prompt and appropriate intervention, if not already being instituted. In lay terms, sepsis is a life-threatening condition that arises when the body’s response to an infection injures its own tissues and organs. (Singer et al., 2016, p. 805) In addition, the guidelines also propose the qSOFA (Quick SOFA) clinical criteria for rapid identification of sepsis: (a) respiratory rate greater than 22 breaths/minute) (b) altered mentation, and (c) systolic blood pressure less than 100 mmHg (Singer et al., 2016). Adult patients with suspected infection can be rapidly identified as being more likely to have poor outcomes typical of sepsis if they have at least two of the qSOFA clinical criteria. The qSOFA has particular nursing implications for patients residing out-of-hospital, present at the emergency department, hospitalized in general hospital ward settings, or residing in nursing homes. Septic shock is defined as a Subset of sepsis in which particularly profound circulatory, cellular, and metabolic abnormalities are associated with a greater risk of mortality than with sepsis alone. Patients with septic shock can be clinically identified by a vasopressor requirement to maintain a mean arterial pressure of 65 mmHg or greater and serum lactate level greater than 2 mmol/ L (>18 mg/dL) in the absence of hypovolemia. This combination is associated with hospital mortality rates greater than 40%. (Singer et al., 2016, p. 801)

To date, the specific nursing implications of the Sepsis-3 consensus guidelines for critical care nursing practice have not been published. In 2013, Kleinpell, Aitken, and Schorr provided an extensive, evidence-based update on the recommendations issued from the Surviving Sepsis Campaign. The emphasis in the Surviving Sepsis Campaign is placed on early recognition and implementation of sepsis bundles within specific timelines (Dellinger et al., 2013). The most salient take-home message of Sepsis-3 for the critical care nurse is the importance of early recognition and assertive action when the patient demonstrates altered mentation, hypotension, and tachypnea. Critical care has been a researchintensive discipline, both in medicine and in nursing. The initial narrow focus on maintaining physiological stability of the cardiopulmonary system undoubtedly contributed to the early commitment to research-based practice. Critical care nurse scientists have been extraordinarily productive, creative, and sophisticated in their investigations. Clinical research in intensive care settings presents multiple challenges because of the ethical concerns of obtaining informed consent, the demands of time and availability at the bedside, the need for institutional access to vulnerable subjects, and the overwhelming number of intervening variables that pose threats to the explanatory power of study findings. Such factors include patient-related factors, such as differences in gender, age, phenotype, previous access to health care, socioeconomic status, presence of comorbidities, variations in mental status, baseline nutritional adequacy, immune function, and unique psychological responses to the illness and the environment, for example, agitation, delirium, and pain. Interventionrelated factors are difficult to control for because critically ill patients receive multiple interventions at once, such as diagnostic and surgical procedures, mechanical ventilation, and powerful medications, as

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well as nursing activities related to complications of immobility. The potential for infection, injury, medication errors, sensory deprivation and overload, and effect of noise on quality of sleep are particularly formidable environmental factors that can impact the patient’s outcome. Finally, known and unknown variations in patient management by the health care team can alter patient outcomes, and then it is up to the investigator to decide how to handle the problem. To address some of these concerns, Sole (2010) recommended the following strategies to new investigators: (a) be self-directed, focusing on a clinical question which is important to you, such the effect of positioning; (b) develop an initial study on basic and familiar clinical concepts, such as airway, breathing, and circulation; (c) seek out collaborators and mentors who can support you and become coinvestigators; and (d) plan a simple pilot study within the context of the team, which is the “most essential part of the infrastructure” (p. 333). The days of the lone researcher are long over. Future research in critical care nursing continues to require the multidisciplinary efforts of all health care providers, who make such a difference in patient outcomes.

Carol Diane Epstein Advance Health Care Network for Nurses. (2015). AACN Clinical Scene Investigator Programgenerates clinical, fiscal results. Retrieved from http:// nursing.advanceweb.com/ News/ National- News/ AACN- Clinical- Scene - Investigator- Program- Generates- Clinical -Fiscal-Results.aspx Aylett, K. (2012). American Association of CriticalCare Nurses to launch hospital-based nurse leadership skill-building program. American Association of Critical-Care Nurses (AACN) Communications. Retrieved from http://www .aacn.org/wd/publishing/content/pressroom/ pressreleases/ 2012- oct- csi- academy- raleigh -release .content?menu=AboutUs

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Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., . . . Moreno, R.; Surviving Sepsis Campaign Guidelines Committee including the Pediatric Subgroup. (2013). Surviving sepsis campaign: International guidelines for management of severe sepsis and septic shock:  2012. Critical Care Medicine, 41(2), 580–637. Deutschman, C. S. (2016). Imprecise Medicine: The limitations of Sepsis-3. Critical Care Medicine, 44(5), 857–858. Deutschman, C. S., Ahrens, T., Cairns, C. B., Sessler, C. N., & Parsons, P. E.; Critical Care Societies Collaborative/USCIITG Task Force on Critical Care Research. (2012). Multisociety task force for critical care research: Key issues and recommendations. American Journal of Critical Care, 21(1), 15–23. Fleischmann, C., Scherag, A., Adhikari, N. K., Hartog, C. S., Tsaganos, T., Schlattmann, P., . . . Reinhart, K.; International Forum of Acute Care Trialists. (2016). Assessment of global incidence and mortality of hospital-treated sepsis. current estimates and limitations. American Journal of Respiratory and Critical Care Medicine, 193(3), 259–272. Goran, S. F. (2010). A second set of eyes: An introduction to tele-ICU. Critical Care Nurse, 30(4), 46–55; quiz 56. Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academies Press. doi:10.17226/10027 Iwashyna, T. J., Ely, E. W., Smith, D. M., & Langa, K. M. (2010). Long-term cognitive impairment and functional disability among survivors of severe sepsis. Journal of the American Medical Association, 304(16), 1787–1794. Kleinpell, R., Aitken, L., & Schorr, C.A. (2013). Implications of the new international sepsis guidelines for nursing care. American Journal of Critical Care, 22(3), 212–222. doi:10.4037/ ajcc2013158 Levy, M. M., Fink, M. P., Marshall, J. C., Abraham, E., Angus, D., Cook, D., . . . Ramsay, G.; International Sepsis Definitions Conference. (2003). 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Intensive Care Medicine, 29(4), 530–538. Lynaugh, J. E., & Fairman, J. (1992). New nurses, new spaces: A preview of the AACN History Study. American Journal of Critical Care, 1(1), 19–24.

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Munro, C. L., & Savel, R. H. (2016). Narrowing the 17-year research to practice gap. American Journal of Critical Care, 25(3), 194–196. Singer, M., Deutschman, C. S., Seymour, C. W., Shankar-Hari, M., Annane, D., Bauer, M., . . . Angus, D. C. (2016). The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). Journal of the American Medical Association, 315(8), 801–810. Sole, M. L. (2010). How I  learned my ABCs: Action, back to basics, collaboration, discovery. American Journal of Critical Care, 19(4), 326–334. Swafford, K., Culpepper, R., & Dunn, C. (2016). Use of a comprehensive program to reduce the incidence of hospital-acquired pressure ulcers in an intensive care unit. American Journal of Critical Care, 25(2), 152–155. Vincent, J. L., Marshall, J. C., Namendys-Silva, S. A., François, B., Martin-Loeches, I., Lipman, J., . . . Sakr, Y.; ICON investigators. (2014). Assessment of the worldwide burden of critical illness: The intensive care over nations (ICON) audit. Lancet Respiratory Medicine, 2(5), 380–386. Vincent, J. L., Moreno, R., Takala, J., Willatts, S., De Mendonça, A., Bruining, H., . . . Thijs, L. G. (1996). The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Medicine, 22(7), 707–710.

CULTURAL/ TRANSCULTURAL FOCUS Cultural/transcultural focus is the study of shared meanings within and among groups. Culture is derived from social, political, and historical processes that influence individual and community beliefs and behaviors. Nurse investigators pursue this focus to explicate the association between culture and health and to provide culturally congruent care. The growing recognition of cultural influences on health care disparities has reinforced the call for practitioner competence. Projections that racial and ethnic minorities will be the

majority in the United States by 2030 has also increased focus on the need for more and better research to understand both individual preferences and social determinants of health. The current impact of cultural/transcultural research (C/TCR) on evidence-based patient care has been limited. The studies have relied on self-assessment of individual cultural competence rather than on direct observation of practitioner behaviors. Furthermore, culture receives only cursory emphasis in most curricula or practice settings, and consensus is lacking on the core components of cultural education. Few nurses are cultural experts. Different perspectives on the meaning of C/TCR exist. To some, the terms are essentially synonymous, and questions of disciplinary origin are unimportant. Researchers in the Leininger tradition regard transcultural nursing as the proper term for a formal, worldwide area of study and practice about culture and caring within nursing. C/TCR is found in a great variety of research and clinical journals. Some C/TCR studies (particularly interventions and randomized controlled trials) may be found in the Cochrane database for evidence-based practice. The searchers are cautioned that (a) the names of racial or ethnic groups are often used only as descriptive labels, and findings do not advance a true cultural knowledge; (b) race, culture, and ethnicity lack consensual definitions and are often used interchangeably; (c) acceptable names for groups change over time (e.g., Negro, Black, Afro-American, African American); (d) the name of the highest stage of cultural knowledge changes over time, with cultural competence or cultural proficiency being currently preferred; (e) databases on special populations are often nonexistent or inadequate; (f) although reports specify a focus on a cultural group, discussion may not relate findings to that group; and (g) findings ascribed to culture are often not distinguished from the effects of socioeconomic status, history, or political structures.

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Most quantitative C/TCR is theory based. Extant models of cultural competence focus solely on clinician attributes rather than on patient outcomes. Frequently used frameworks for understanding health beliefs, preferences, and practices of diverse groups include Leininger’s culture care theory, self-care, health-seeking behavior, health belief models, stress and coping, self-efficacy, and transitions. The transtheoretical model of health behavior change is becoming popular for its focus on stages of change. The cultural appropriateness of existing frameworks for particular groups continues to be called into question. For example, health belief models have been criticized for inadequately recognizing real (rather than perceived) barriers to care, spirituality, and the interconnectedness (rather than the individuality) of African American women. Studies seeking explanatory models of illness are increasing, a welcome trend because this approach, which parallels an intake history and involves all aspects of the disease course and clinical encounter, seems relevant and practical to clinicians as well as to researchers. Although most data-collection strategies, including physiological measurements, are used in C/TCR, the most frequently used are focus groups, interviews, ethnographies, participant observation, and written questionnaires. Qualitative approaches have long been recognized as well suited to C/TCR and are frequently used. The overwhelming majority of C/TCR has been intracultural, descriptive, small scale, and nonprogrammatic. The typical study is an interview or survey on health knowledge, health beliefs, and practices, or a concept like self-efficacy within one designated group conducted by a single investigator. However, cross-national nursing studies, studies with large sample sizes, studies done by interdisciplinary or international teams, and programmatic research are becoming more frequent. The challenges associated with conducting research with other cultures can be numerous and researcher expertise

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and sensitivity in cross-cultural contexts are required. Methodological research, including studies of recruiting and retaining subjects and instrumentation, is growing rapidly. The quality of measurement in C/TCR is improving steadily. The standards for rigorous translation are widely recognized, and both the cultural fit of items and the psychometric properties of an instrument for the target group are increasingly being reported and studied. Instruments, such as the Cultural Self-Efficacy Scale and the Cultural Awareness Scale, are being developed to measure the outcomes of programs to promote multicultural awareness. There are three major needs in C/TCR. First is the need for additional intervention studies. More investigators must move from descriptive studies to interventions to randomized controlled trials. The sheer volume of very similar studies of the health beliefs, family values, gender roles, and importance of family decision making, folk remedies, or spirituality within certain groups suggests a sufficient base for culturally adapted intervention studies. A second great need is for the application of existing guidelines for culturally competent research. Research needs to be planned to be culturally competent. Culturally competent research is broader than efforts to select culturally appropriate instruments or to recruit appropriate subjects. Interventions and data-collection methods must be culturally congruent and protection of human subjects must be assured. The third great need of C/TCR is for research to be planned and conducted with greater community involvement. More studies, particularly programmatic studies, are needed on Native American health. Studies of multiracial or multiethnic persons are rare but urgently needed, given the growing numbers of people who identify themselves as having multiple heritages. Studies of rural, occupational, and sexual subcultures (groups not defined by race or ethnicity) are needed, as are comparative explorations of cultural

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perspectives on ethics. A growing trend is the recent acknowledgment of the health care disparities experienced by the lesbian, gay, bisexual, and transgender community. Folk and alternative healing practices and their possible combinations with biomedical approaches need systematic, sensitive study. The studies of cultural adaptations of care in homes, development of brief rapid strategies

for cultural assessment, and development of the economic case for culturally competent care are needed to ensure that culture is considered fundamental to strategies for improving population health and reducing health disparities.

Sharol F. Jacobson Karen Bauce

D DATA ANALYSIS Data analysis is a systematic method for examining data gathered for a research investigation to support interpretations and conclusions about the data and inferences about the population. Although applicable to both qualitative and quantitative research, data analysis is more often associated with quantitative research. Quantitative data analysis involves the application of logic and reasoning through the use of statistics, an applied branch of mathematics, to numeric data. Qualitative data analysis involves the application of logic and reasoning, a branch of philosophy, to nonnumeric data. Both require careful execution and are intended to give meaning to data by organizing disparate pieces of information into understandable and useful aggregates, statements, or hypotheses. Statistical data analysis is based on probability theory and involves using specific statistical tests or measures of association between two or more variables. Each of these tests or statistics (e.g., t, F, β, χ2, φ, η, etc.) has a known distribution that allows calculation of probability levels for different values of the statistic under different assumptions—that is, the test (or null) hypothesis and the sample size or the degrees of freedom. Specific tests are selected because they provide the most meaningful representation of the data in response to specific research questions or hypotheses posed. The selection of specific tests, however, is restricted to those for which the available data meet certain required assumptions of the tests. For example, some tests are appropriate for (and

assume) nominal or categorical data, others assume ordinal data, and still others assume an interval level of measurement. Although each test has its own set of mathematical assumptions about the data, all statistical tests assume random sampling. Several statistical computer programs (e.g., Statistical Package for the Social Sciences [SPSS], Statistical Analysis System [SAS]) are available to aid the investigator with the tedious and complex mathematical operations necessary to calculate these test statistics and their sampling distributions. However, these programs only serve to expedite calculations and ensure accuracy. There is a hidden danger in the ease with which one may execute these computer programs; the investigator must understand the computer programs to use them appropriately. To ensure that data analysis is valid and appropriate for the specific research question or hypothesis, the investigator also must fully understand the statistical procedures themselves and the underlying assumptions of these tests. Most quantitative data analysis uses a null hypothesis statistical test approach. The logic of null hypothesis statistical testing is one of modus tollens, denying the antecedent by denying the consequent. That is, if the null hypothesis is correct, our nonzero findings cannot occur, but as these findings did occur, the null hypothesis must be false. Cohen (1994) and others have argued convincingly that by making this reasoning probabilistic for null hypothesis statistical testing, we invalidate the original syllogism. Despite decades of articles by scientists from different disciplines questioning the usefulness and triviality of null hypothesis statistical testing (e.g., from sociology, psychology, public health, and nursing, see Labovitz, 1970; LeFort, 1993; Loftus, 1993; Rozeboom,

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1960; Walker, 1986), null hypothesis statistical testing still dominates analytic approaches. Some of the articles and arguments about the limits of null hypothesis statistical testing have led to more emphasis on the use of confidence intervals. Confidence intervals provide more information about our findings, particularly about the precision of population estimates from our sample data, but they are based on the same null hypothesis statistical testing logic that generates p-values. Thus, confidence intervals are subject to the same issues with respect to type 1 errors (rejecting the null when it is true) and type 2 errors (failing to reject the null when it is false). There is increased attention and sensitivity to factors that contribute to findings of statistical significance that has also led to more attention to power, sample sizes, and role of effect sizes (for substantive significance) for valid quantitative data analysis. If the sample size is too small, the study may be underpowered and unable to detect an important finding even if it is there. Conversely, if the sample size is too large, the study may be overpowered and may result in statistically significant findings that are substantively or clinically insignificant or meaningless. As a result, either could be challenged on ethical grounds, stressing the importance of appropriately powering studies for the planned data analysis. In contrast to quantitative data analysis, which requires that the investigator assign a numeric code to all data before beginning the analyses, qualitative data analysis consists of coding words, objects, and/or events into meaningful categories and/or themes as part of the actual data analyses. As qualitative data analysis involves nonnumeric data, there are no statistical probabilistic tests to apply to the coding of qualitative data. Historically, coding of qualitative data was done manually; today computer programs (e.g., NVivo and QSR) are available to aid the investigator in this laborious effort. However, as with the computer programs for quantitative analyses, computer programs

for qualitative data analysis are merely aids for the tedious and error-prone tasks of analysis. Inspite of using them the investigator still needs to make the relevant and substantive decisions and interpretations about codes, categories, and themes. Although quantitative data analysis allows for statistical probabilistic statements to support the investigator’s interpretations and conclusions, qualitative data analysis depends more exclusively on the strength and logic of the investigator’s arguments. Nonetheless, both types of data analysis ultimately rest on the strength of the original study design and the ability of the investigator to appropriately and accurately execute the analytic method selected.

Lauren S. Aaronson Cohen, J. (1994). The earth is round (p