The nature and validity of implicit bias training for health care providers and trainees: A systematic review

Author:

Hagiwara Nao1ORCID,Duffy Conor2ORCID,Cyrus John3ORCID,Harika Nadia4,Watson Ginger S.5ORCID,Green Tiffany L.6ORCID

Affiliation:

1. Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22903, USA.

2. Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA.

3. Research and Education Department, Health Sciences Library, Virginia Commonwealth University, Richmond, VA 23298, USA.

4. Department of Pediatrics, Virginia Commonwealth University, Richmond, VA 23219, USA.

5. Virginia Modeling Analysis & Simulation Center, Old Dominion University, Suffolk, VA 23435, USA.

6. Departments of Population Health Sciences and Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, WI 53726, USA.

Abstract

The number of health care educational institutions/organizations adopting implicit bias training is growing. Our systematic review of 77 studies (published 1 January 2003 through 21 September 2022) investigated how implicit bias training in health care is designed/delivered and whether gaps in knowledge translation compromised the reliability and validity of the training. The primary training target was race/ethnicity (49.3%); trainings commonly lack specificity on addressing implicit prejudice or stereotyping (67.5%). They involved a combination of hands-on and didactic approaches, lasting an average of 343.15 min, often delivered in a single day (53.2%). Trainings also exhibit translational gaps, diverging from current literature (10 to 67.5%), and lack internal (99.9%), face (93.5%), and external (100%) validity. Implicit bias trainings in health care are characterized by bias in methodological quality and translational gaps, potentially compromising their impacts.

Publisher

American Association for the Advancement of Science (AAAS)

Reference109 articles.

1. Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (National Academies Press 2003); www.ncbi.nlm.nih.gov/books/NBK220358/.

2. A decade of studying implicit racial/ethnic bias in healthcare providers using the implicit association test

3. Implicit bias in healthcare professionals: a systematic review

4. S. Heath AMA joins industry efforts against medical racism implicit bias (Patient Engagement Hit 2023); https://patientengagementhit.com/news/ama-joins-industry-efforts-against-medical-racism-implicit-bias.

5. Mandated Implicit Bias Training for Health Professionals—A Step Toward Equity in Health Care

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3