ArticleBMC medical education2023
A scoping review to identify and organize literature trends of bias research within medical student and resident education.
Article in BMC medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhysician bias refers to the unconscious negative perceptions that physicians have of patients or their conditions. Medical schools and residency programs often incorporate training to reduce biases among their trainees. In order to assess trends and organize available literature, we conducted a scoping review with a goal to categorize different biases that are studied within medical student (MS), resident (Res) and mixed populations (MS and Res). We also characterized these studies based on their research goal as either documenting evidence of bias (EOB), bias intervention (BI) or both. These findings will provide data which can be used to identify gaps and inform future work across these criteria.
methodsOnline databases (PubMed, PsycINFO, WebofScience) were searched for articles published between 1980 and 2021. All references were imported into Covidence for independent screening against inclusion criteria. Conflicts were resolved by deliberation. Studies were sorted by goal: 'evidence of bias' and/or 'bias intervention', and by population (MS or Res or mixed) andinto descriptive categories of bias.
resultsOf the initial 806 unique papers identified, a total of 139 articles fit the inclusion criteria for data extraction. The included studies were sorted into 11 categories of bias and showed that bias against race/ethnicity, specific diseases/conditions, and weight were the most researched topics. Of the studies included, there was a higher ratio of EOB:BI studies at the MS level. While at the Res level, a lower ratio of EOB:BI was found.
conclusionsThis study will be of interest to institutions, program directors and medical educators who wish to specifically address a category of bias and identify where there is a dearth of research. This study also underscores the need to introduce bias interventions at the MS level.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.