Beyond empathy: a qualitative exploration of arts and humanities in pre-professional (baccalaureate) health education
Bibliographic record
Abstract
For nearly four decades, researchers have explored the integration of arts and humanities content into health professions education (HPE). However, enduring controversies regarding the purpose, efficacy, and implementation of humanities initiatives suggest that the timing and context of trainees' exposure to such content is a key, but seldom considered, factor. To better understand the affordances of introducing humanities-based health curriculum prior to the HPE admissions gateway, we conducted a qualitative instrumental case study with participants from Canada's first Health Humanities baccalaureate program. Fully anonymized transcripts from semi-structured interviews (n = 11) and focus groups (n = 14) underwent an open-coding procedure for thematic narrative analysis to reveal three major temporal domains of described experience (i.e., prior to, during, and following their participation in a 12-week semester-long "Introduction to Health Humanities" course). Our findings demonstrate that perceptions of arts- and humanities content in health education are generated well in advance of HPE admission. Among other findings, we define a new concept-epistemological multicompetence-to describe participants' emergent capability to toggle between (and advocate for the role of) multiple disciplines, arts and humanities particularly, in health-related teaching and learning at the pre-professional level. Improved coordination of baccalaureate and HPE curricula may therefore enhance the development of capabilities associated with arts and humanities, including: epistemological multicompetence, aesthetic sensibility, and other sought-after qualities in HPE candidates. In conclusion, attending to the pre-professional admissions gateway presents a new, capabilities-driven approach to enhancing both the implementation and critical understanding of arts and humanities' purpose, role, and effects across the "life course" of health professions education.
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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 | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".