Evidence map›Paper›PMID 38388855›Full record

ArticleAdvances in health sciences education : theory and practice2024

Assessing supervisor versus trainee viewpoints of entrustment through cognitive and affective lenses: an artificial intelligence investigation of bias in feedback.

Brian C Gin, Olle Ten Cate, Patricia S O'Sullivan, Christy Boscardin

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In one paragraph

Article in Advances in health sciences education : theory and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. A Qualitative Systematic Review of the Role of Entrustment in Pre-Registration Healthcare Practice-Based Learning: Implications for Dietetics Education.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Brian C GinDepartment of Pediatrics, University of California San Francisco, 550 16th St Floor 4, UCSF Box 0110, San Francisco, CA, 94158, USA. brian.gin@ucsf.edu.ORCID 0000-0001-7655-3750
Olle Ten CateUtrecht Center for Research and Development of Health Professions Education, University Medical Center, Utrecht, the Netherlands.ORCID 0000-0002-6379-8780
Patricia S O'SullivanDepartment of Medicine, University of California San Francisco, San Francisco, USA.ORCID 0000-0002-8706-4095
Christy BoscardinDepartment of Medicine, University of California San Francisco, San Francisco, USA.ORCID 0000-0002-9070-8859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The entrustment framework redirects assessment from considering only trainees' competence to decision-making about their readiness to perform clinical tasks independently. Since trainees and supervisors both contribute to entrustment decisions, we examined the cognitive and affective factors that underly their negotiation of trust, and whether trainee demographic characteristics may bias them. Using a document analysis approach, we adapted large language models (LLMs) to examine feedback dialogs (N = 24,187, each with an associated entrustment rating) between medical student trainees and their clinical supervisors. We compared how trainees and supervisors differentially documented feedback dialogs about similar tasks by identifying qualitative themes and quantitatively assessing their correlation with entrustment ratings. Supervisors' themes predominantly reflected skills related to patient presentations, while trainees' themes were broader-including clinical performance and personal qualities. To examine affect, we trained an LLM to measure feedback sentiment. On average, trainees used more negative language (5.3% lower probability of positive sentiment, p < 0.05) compared to supervisors, while documenting higher entrustment ratings (+ 0.08 on a 1-4 scale, p < 0.05). We also found biases tied to demographic characteristics: trainees' documentation reflected more positive sentiment in the case of male trainees (+ 1.3%, p < 0.05) and of trainees underrepresented in medicine (UIM) (+ 1.3%, p < 0.05). Entrustment ratings did not appear to reflect these biases, neither when documented by trainee nor supervisor. As such, bias appeared to influence the emotive language trainees used to document entrustment more than the degree of entrustment they experienced. Mitigating these biases is nonetheless important because they may affect trainees' assimilation into their roles and formation of trusting relationships.

Indexed as

Artificial IntelligenceClinical CompetenceStudents, MedicalTrustBiasCognitionFeedbackFemaleFormative FeedbackHumansMaleArtificial intelligenceClinical supervisionEntrustmentFeedbackGender biasLarge language modelsNatural language processing

Identifiers

PMID38388855
PMCPMC11549112

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Registered trials

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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.