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Record W2619635310 · doi:10.1186/s12909-017-0932-1

The effect of white coats and gender on medical students’ perceptions of physicians

2017· article· en· W2619635310 on OpenAlexaff
Malika A. Ladha, Aleem Bharwani, Kevin McLaughlin, Henry T. Stelfox, Adam Bass

Bibliographic record

VenueBMC Medical Education · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPerceptionCompetence (human resources)Ethnic groupFamily medicineMedicineWhite coatWhite (mutation)Medical educationPsychologySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the fact that medical schools spend a considerable effort to rate clinical instructors, there is limited evidence regarding the effect of physical characteristics on instructor ratings. White coats have been shown to alter patients' perceptions of physicians although it has not been determined if preceptors who wear white coats are rated differently than their colleagues. METHODS: Second year medical students were administered a questionnaire with four clinical scenarios depicting medical errors accompanied by a picture of a physician of different sexes and ethnicities. The packages were randomized so that the physicians depicted either had or did not have a white coat. RESULTS: White coats did not alter the perception of physicians' ratings by medical students although sex and ethnicity/case were associated with the perception of trustworthiness, physician management, competence, professionalism and the perception of medical error. CONCLUSIONS: Physical characteristics may alter students' ratings of physicians.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.415
Teacher spread0.395 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations10
Published2017
Admission routes1
Has abstractyes

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