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Record W4402456067 · doi:10.1186/s12909-024-05981-3

Incorporating equity, diversity and inclusion (EDI) into the education and assessment of professionalism for healthcare professionals and trainees: a scoping review

2024· review· en· W4402456067 on OpenAlexaff
Darsh Shah, Nima Behravan, Nujud Al-Jabouri, Matthew Sibbald

Bibliographic record

VenueBMC Medical Education · 2024
Typereview
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCultural humilityHumilityPsychological interventionInclusion (mineral)Medical educationThematic analysisHealth careCultural diversityEquity (law)PsychologyMEDLINEDiversity (politics)Cultural competenceMedicineNursingQualitative researchPedagogySociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Current definitions of professionalism for healthcare trainees often lack equity, diversity and inclusion (EDI) in the expectations and assessment of professionalism. While professionalism teaching is incorporated in healthcare training, equity-deserving groups still experience discrimination. This scoping review investigates the literature to understand how EDI and associated domains of cultural humility, and advocacy can be incorporated in healthcare trainees' education and assessment of professionalism. METHODS: The Arksey and O'Malley framework was applied to this scoping review. MEDLINE, Embase & PsychINFO were searched up to March 2023, with terms surrounding health professionals, professionalism, EDI, cultural humility, and advocacy. Titles and abstracts (n = 3870) and full-texts (n = 140) were independently screened by two reviewers. Articles were included if they focused on EDI, cultural humility, or advocacy among healthcare students/trainees, and had outcomes related to professionalism. Articles lacking discussion of professionalism as an outcome were excluded. Themes were generated by mutual discussion. Risk of bias was assessed using the Cote et al. and Medical Education Research Study Quality Instrument (MERSQI) tools. RESULTS: 48 articles underwent thematic analysis. Studies investigated the disciplines of medicine, nursing, social work, physiotherapy, and dentistry. Most studies were qualitative in methodology (n = 23). Three themes emerged: (1) EDI-related interventions are associated with improved professionalism of healthcare trainees/workers (n = 21). Interventions employed were either an EDI-associated educational course (n = 8) or an exchange program to promote EDI competencies among trainees (n = 13). (2) Trainee definitions and perceptions of professionalism include themes related to EDI and cultural humility (n = 12). (3) Current standards of professionalism are perceived as non-inclusive towards historically-marginalized populations (n = 15). Literature investigating advocacy as it relates to professionalism is limited. CONCLUSION: This review identified that core EDI principles and its associated domains of cultural humility and advocacy are often viewed as integral to professionalism. These findings create a strong impetus to incorporate EDI principles within professionalism frameworks in healthcare education. Future research should employ standardized tools for professionalism assessment to provide more conclusive evidence. Incorporating patient perspectives of professionalism can inform actionable recommendations for fostering inclusive healthcare environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.076
metaresearch head score (Gemma)0.210
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.076
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.210
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0360.028
Science and technology studies0.0030.004
Scholarly communication0.0090.011
Open science0.0030.007
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.250
GPT teacher head0.606
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2024
Admission routes1
Has abstractyes

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