What Is Taught Versus What Is Learned: Health Advocacy in Specialist Graduate Medical Education
Bibliographic record
Abstract
PURPOSE: Health advocacy (HA) is a key component of competency frameworks in many global jurisdictions, yet how HA is taught is not well defined, particularly in specialty graduate medical education. This study explored how residents in these programs came to understand what HA is, what activities it entails, and what importance it carries. METHOD: This qualitative study conducted semistructured interviews of 39 specialty residents from 2 universities (University of Toronto and University of Ottawa) from July 2019 to June 2023. A reflexive thematic analysis was used, with sensitizing concepts of the formal, informal, and hidden curricula and the CanMEDS health advocate role to construct themes from this data set. RESULTS: Most trainees struggled to define what HA means, what good HA should look like, and which kinds of activities it signifies. The lack of definitional clarity meant that many non-HA activities became conflated with HA, particularly research and quality improvement. Few could recall clear formal curricular content, whereas exposure in clinical training environments was highly variable. Many perceived HA activities as threats to clinical efficiency, of little interest to residency program leadership, and of minimal currency in being competitive for eventual staff positions. Self-identified advocates frequently engaged in self-censoring behaviors because they thought their programs and leaders were often not supportive of this kind of work. CONCLUSIONS: Trainees struggled to understand what activities comprise HA because it was not prioritized in their programs or they encountered highly variable role modeling. Trainees who participated in HA activities experienced difficulties integrating HA into their overall clinical skill set due to a lack of institutional support. Health advocacy training requires consideration of structural and cultural reinforcements, including the adoption of curricula that integrate it with daily clinical care and address hidden curriculum effects.
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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 | 0.025 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.024 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".