A Scoping Review of Programs of Active Arts Engagement in International Medical Curricula
Bibliographic record
Abstract
Introduction: Arts and humanities are often positioned as ‘additive’ to medical education, rather than ‘intrinsic’. They are also used to teach skills and perspective-taking more than utilising their transformative potential to propel personal insight and social advocacy. There is, therefore, a need for more meaningful and strategic integration of the arts in medical curricula. Existing reviews combine active and receptive arts engagement, although these methods represent different magnitudes of engagement. Methods: This review aimed to synthesise the use of active arts engagement in undergraduate medical curricula internationally. We searched seven databases for articles published between 1991–2024. Results: We reviewed 134 studies conducted in 27 countries (total n = 10,700). Most programs were medium-intensity (e.g., standalone modules), used visual and performing arts, and aimed to foster skills mastery, perspective-taking, and personal insight. Studies on artmaking for social advocacy were lacking, as was data about program evaluation and learner assessment. Almost all survey instruments used were unvalidated. Discussion: Studies of active arts engagement are disproportionately low compared to receptive engagement, signaling missed opportunities to leverage the benefits of the arts. Most studies were conducted in high-income countries, illuminating that lower-income countries do not have a strong voice in the knowledge exchange. To avoid devaluing the arts in medical curricula, we suggest that medical educators: a) direct attention to creative opportunities to engage students with social advocacy; b) collaborate with arts/humanities professionals and international medical educators; c) consider more meaningful and strategic integrations of active arts engagement into medical curricula, approaching them with the same rigor as other medical education programs to maximise their pedagogical potential.
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 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 | 0.026 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.028 | 0.032 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".