Achievement of non‐cognitive goals of undergraduate medical education: perceptions of medical students, residents, faculty and other health professionals
Bibliographic record
Abstract
BACKGROUND: Professionalism is increasingly emphasised in medical education. Non-cognitive goals, including values, attitudes and skills, remain challenging to define and measure. The purpose of this study was to better understand these goals and their achievement in the MD programme. METHODS: Graduating medical students, faculty preceptors, residents and other health professionals (OHPs) completed a systematically developed mailed survey, rating achievement of 25 attribute statements. Following analyses of means and standard deviations, factor analysis of responses was conducted. Responses were compared across respondent groups. RESULTS: The overall response rate was 50.1% (191/396), comprising 57.5% of the students, 54.1% of the faculty members, 30.9% of the residents and 50% of the OHPs. Five items received mean ratings over 4/5; none were below 3/5. Five factors explained 65% of variance. They were: 'Teamwork and interprofessional skills'; 'Duty and responsibility'; 'Communication and interpersonal skills'; 'Professionalism and values', and 'Trustworthiness and ethical behaviour'. The groups differed significantly on 2 factors: Teamwork and interprofessional skills (P < or = 0.0001) and Communication and interpersonal skills (P < or = 0.001). CONCLUSIONS: Important curriculum goals received high mean ratings. Ratings differed significantly across groups, suggesting differing perceptions of the extent to which goals were met. More study is needed to understand the basis of these perceptions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".