ArticleBMC medical education2024
Elevating equity: advancing diversity and inclusivity through trialing bias reduction tools in the general internal medicine program resident application process.
Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundDecades of medical data show worse patient outcomes among racial and gender minorities due to implicit, explicit, and structural biases. Increasing representation of marginalized groups among care providers is imperative to help address this. Limited literature exists on bias awareness strategies for interviewers during the selection of applicants to General Internal Medicine (GIM) programs in Canada. This study examines the trial of bias reduction tools to increase interviewers' awareness of implicit biases.
methodsThe Model of Improvement framework guided the trail of an instructional video, the adapted implicit association test (IAT), and a paper awareness tool (PAT) to increase interviewers' awareness of implicit biases during the University of Alberta's GIM applicant selection. An anonymous online survey was disseminated to physician interviewers. Descriptive statistics (percentages) and a modified sentiment analysis was completed.
results10 of 14 interviewers completed the survey. Respondents reported an increased awareness of using bias reduction tools (IAT, 25%; video, 71%; PAT, 67%) to inform them on their implicit biases. The future use of IAT, video, and PAT was supported by 50%, 71%, and 67% of interviewers, respectively.
conclusionsInterviewers prefer the instructional video and PAT over the IAT. Textual responses suggest existing concerns for biases inherent to the interview process yet 70% (7/10) of respondents believe that interviews should have a weighting of 50% towards final ranking of candidates. As many institutions continue to rely on interviews to evaluate candidates, our findings indicate the need for a national study to develop a framework to mitigate inherent biases during interviewing of candidates.
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