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Implicit bias assessment by career stage in medical education training: a narrative review

I tiakina i:
I whakaputaina i:BMC Medical Education vol. 25 (2025), p. 1
Kaituhi matua: Crump, Alisha
Ētahi atu kaituhi: May Saad Al-Jorani, Ahmed, Sunya, Ekas Abrol, Jain, Shikha
I whakaputaina:
Springer Nature B.V.
Ngā marau:
United States > US
Sexual orientation
Socioeconomic factors
Medical education
Citation management software
Gender
Medical students
Bias
Racism
Focus groups
Decision making
Stereotypes
Race
Patients
Literature Reviews
Negative Attitudes
Outcomes of Treatment
Database Design
Individualized Instruction
Medical Evaluation
Training Methods
Premedical Students
Eligibility
Educational Assessment
Database Management Systems
Cognitive Ability
Individual Characteristics
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Whakarāpopotonga:Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person based on individual characteristics. Early evaluation of implicit bias in medical training can prevent long-term adverse health outcomes related to racial bias. However, to our knowledge, no present studies examine the sequential assessment of implicit bias through the different stages of medical training. The objective of this narrative review is to examine the breadth of existing publications that assess implicit bias at the current levels of medical training, pre-medical, graduate, and postgraduate. Protocol for this study was drafted using the Scale for the Assessment of Narrative Reviews (SANRA). Keyword literature search on peer-reviewed databases Google Scholar, PubMed, Ebsco, ScienceDirect, and MedEd Portal from January 1, 2017, to March 1, 2022, was used to identify applicable research articles. The online database search identified 1,512 articles. Full screening resulted in 75 papers meeting the inclusion criteria. Over 50% of extracted papers (74%) were published between 2019 and 2021 and investigated implicit bias at the post-graduate level (43%), followed by the graduate level (34%), and pre-medical level (9.4%). Fourteen percent were classified as mixed. Studies at the medical and medical graduate level identified an implicit preference towards white, male, non-LGBTQIA+, thin, patients. Study findings highlight notable gaps within the sequential assessment of implicit bias, specifically at the pre-medical training level. Longitudinal epidemiological research is needed to examine the long-term effect of implicit biases on existing healthcare disparities.
ISSN:1472-6920
DOI:10.1186/s12909-024-06319-9
Puna:Healthcare Administration Database