Acad Med. 2025 Sep 15. doi: 10.1097/ACM.0000000000006268. Online ahead of print.
ABSTRACT
PURPOSE: Blinding in pediatric residency recruitment and the influence of implicit biases have not been formally studied. This study examined whether blinding to race and/or gender influences the selection of candidates for pediatric residency interviews and assessed the role of respondent implicit bias.
METHOD: An electronic survey was sent to all U.S. pediatric residency program directors in spring 2023. Nonresponders were sent weekly reminders for 5 weeks (survey remained open for 6 weeks). Respondents rated 5 fictitious applicants, each randomly assigned a gender (male, female, or blinded) and race (Black, White, or blinded), and completed an Implicit Association Test (IAT) to assess unconscious attitudes about race. The survey then asked about current strategies to mitigate unconscious bias in residency recruitment.
RESULTS: Responses were received from 85 of 202 programs (42%). All 85 program leaders reported using implicit bias training, with 64 of 83 (77%) using blinding and 74 of 84 (88%) using standardized rubrics to score applications as strategies to mitigate bias. The IAT revealed no statistically significant difference in the proportion of respondents with a positive implicit attitude toward Black versus White people (W = 840, P = .20). Statistically significant main effects were found for applicant race and interaction between applicant race and respondent IAT score, with respondents rating applicants with unknown race lower by a mean (95% CI) of 0.61 (0.07-1.16) points on the 5-point scale than the same applicants presenting as White or Black (t222 = 2.2, P = .03) and respondents rating White or unknown race applicants lower when their implicit attitudes toward Black people were more positive (t207 = -4.0, P < .001 and t208 = -2.9, P = .004, respectively).
CONCLUSIONS: Blinding applicant race may adversely impact some applicants’ interview prospects, suggesting that caution be applied when considering blinding to address implicit bias.
PMID:40953379 | DOI:10.1097/ACM.0000000000006268
