Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Purpose: Observed assessments are integral to medical education but may be biased against structurally marginalized communities. Current understanding of assessment bias is limited because studies have focused on single specialties, levels of training, or social identity characteristics (SIDCs). This scoping review maps studies investigating bias in observed assessments in medical education arising from trainees' observable SIDCs at different medical training levels, with consideration of medical specialties, assessment environments, and assessment tools.
Method: MEDLINE, Embase, ERIC, PsycINFO, Scopus, Web of Science Core Collection, and Cochrane Library were searched for articles published between January 1, 2008, and March 15, 2023, on assessment bias related to 6 observable SIDCs: gender (binary), gender nonconformance, race and ethnicity, religious expression, visible disability, and age. Two authors reviewed the articles, with conflicts resolved by consensus or a third reviewer. Results were interpreted through group review and informed by consultation with experts and stakeholders.
Results: Sixty-six of 2,920 articles (2.3%) were included. These studies most frequently investigated graduate medical education [44 (66.7%)], used quantitative methods [52 (78.8%)], and explored gender bias [63 (95.5%)]. No studies investigated gender nonconformance, religious expression, or visible disability. One evaluated intersectionality. SIDCs were described inconsistently. General surgery [16 (24.2%)] and internal medicine [12 (18.2%)] were the most studied specialties. Simulated environments [37 (56.0%)] were studied more frequently than clinical environments [29 (43.9%)]. Bias favoring men was found more in assessments of intraoperative autonomy [5 of 9 (55.6%)], whereas clinical examination bias often favored women [15 of 19 (78.9%)]. When race and ethnicity bias was identified, it consistently favored White students.
Conclusions: This review mapped studies of gender, race, and ethnicity bias in the medical education assessment literature, finding limited studies on other SIDCs and intersectionality. These findings will guide future research by highlighting the importance of consistent terminology, unexplored SIDCs, and intersectionality.
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http://dx.doi.org/10.1097/ACM.0000000000005794 | DOI Listing |
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