Rethinking research in the medical humanities: a scoping review and narrative synthesis of quantitative outcome studies
Bibliographic record
Abstract
OBJECTIVES: The rise of medical humanities teaching in medical education has introduced pressure to prove efficacy and utility. Review articles on the available evidence have been criticised for poor methodology and unwarranted conclusions. To support a more nuanced discussion of how the medical humanities work, we conducted a scoping review of quantitative studies of medical humanities teaching. METHODS: Using a search strategy involving MEDLINE, EMBASE and ERIC, and hand searching, our scoping review located 11 045 articles that referred to the use of medical humanities teaching in medical education. Of these, 62 studies using quantitative evaluation methods were selected for review. Three iterations of analysis were performed: descriptive, conceptual, and discursive. RESULTS: Descriptive analysis revealed that the medical humanities as a whole cannot be easily systematised based on simple descriptive categories. Conceptual analysis supported the development of a conceptual framework in which the foci of the arts and humanities in medical education can be mapped alongside their related epistemic functions for teaching and learning. Within the framework, art functioned as expertise, as dialogue or as a means of expression and transformation. In the discursive analysis, we found three main ways in which the relationship between the arts and humanities and medicine was constructed as, respectively, intrinsic, additive and curative. CONCLUSIONS: This review offers a nuanced framework of how different types of medical humanities work. The epistemological assumptions and discursive positioning of medical humanities teaching frame the forms of outcomes research that are considered relevant to curriculum decision making, and shed light on why dominant review methodologies make some functions of medical humanities teaching visible and render others invisible. We recommend the use of this framework to improve the rigor and relevance of future explorations of the efficacy and utility of medical humanities teaching.
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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 | 0.238 | 0.454 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.042 | 0.039 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".