Incorporating the interaction between health and work into the undergraduate medical curriculum – a qualitative evaluation of a teaching pilot in English medical schools
Bibliographic record
Abstract
Introduction: There is a growing recognition of the impact of work on health both positive and negative. It is important that all health care professionals are equipped to understand the effects of work and worklessness on health and help patients remain in work or manage a healthy return to work where appropriate. Despite explicit reference to health and work in the General Medical Council’s Outcomes for Graduates, currently, this is not a theme that is integrated across the undergraduate medical curricula.Aim: This study evaluates medical tutors’ and undergraduates’ perspectives of a selection of health and work topics in a teaching pilot to consider the suitability and appropriateness for delivery, integration into the curriculum, tailoring of the resources, and appropriateness and expected attainment of learning objectives.Methods: Qualitative, semi-structured interviews and focus groups were carried out with five medical tutors and 36 undergraduates. Interviews and focus groups were recorded, transcribed and thematically analysed.Results: Medical tutors and undergraduates identified suitability of appropriate subject specialities and years of teaching, whether learning objectives were important and if these had been achieved, and recommendations for future delivery.Discussion: Medical tutors were committed to delivering the health and work topics with the flexibility of tailoring the resources to existing subject specialities and with respect to the year of study. Learning objectives were perceived appropriate by tutors, despite ambivalence about their importance from some undergraduates. Resources were identified as having relevance to public health undergraduate teaching and during general practice placements.
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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 | 0.029 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".