Unclear if future physicians are learning about patient-centred care: Content analysis of curriculum at 16 medical schools
Bibliographic record
Abstract
Given barriers of patient-centred care (PCC) among physicians and trainees, this study assessed how medical schools addressed PCC in curriculum. The authors used content analysis to describe PCC in publicly-available curriculum documents of Canadian medical schools guided by McCormack’s PCC Framework, and reported results using summary statistics and text examples. The authors retrieved 1459 documents from 16 medical schools (median 49.5, range 16–301). Few mentioned PCC (301, 21.2%), and even fewer thoroughly or accurately described PCC. Significantly more clerkship versus pre-clerkship (24.0% vs 12.6%, p p Overall, few documents mentioned or described PCC or related concepts. This varied by school, and was more frequent in clerkship and elective courses, suggesting that student exposure may be brief and variable. Thus, it remains unclear if medical students are fully exposed to what PCC means and how to implement it. Future research is needed to confirm if PCC content in medical curriculum is lacking.
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 | 0.007 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".