A systematic review of the arts and humanities in psychiatry education
Bibliographic record
Abstract
This systematic review characterizes the published literature on arts and humanities curricula for psychiatry learners that include any form of program evaluation. Authors searched three databases (Medline ALL, Embase.com, and PsycINFO) to identify articles on arts and humanities in psychiatry education. Criteria for the review included articles reporting outcome measures for arts and humanities learning activities in psychiatry learners. For those articles meeting inclusion criteria, a descriptive analysis was performed as well as an assessment of the level of program evaluation using the Kirkpatrick framework. Of 1,287 articles identified, 35 met inclusion criteria. About half of the programs included medical students (n = 17, 49%). Film and television was the most frequent arts and humanities subject (n = 16, 46%). Most studies incorporated a non-randomized, non-controlled design (n = 30, 86%). Twenty-two (63%) achieved a Kirkpatrick Level 1 designation, 12 achieved Level 2 (34%), and one study achieved Level 3 (3%). Arts and humanities programs have a promising role in psychiatry education. At present, significant heterogeneity in the extant literature makes it difficult to draw general conclusions that could guide future program development. This review underscores the need for rigorous evaluative methods of arts and humanities programs for psychiatry learners.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".