Evaluation of resident attitudes and self-reported competencies in health advocacy
Bibliographic record
Abstract
BACKGROUND: The CanMEDS Health Advocate role, one of seven roles mandated by the Royal College of Physicians and Surgeons Canada, pertains to a physician's responsibility to use their expertise and influence to advance the wellbeing of patients, communities, and populations. We conducted our study to examine resident attitudes and self-reported competencies related to health advocacy, due to limited information in the literature on this topic. METHODS: We conducted a pilot experience with seven internal medicine residents participating in a community health promotion event. The residents provided narrative feedback after the event and the information was used to generate items for a health advocacy survey. Face validity was established by having the same residents review the survey. Content validity was established by inviting an expert physician panel to review the survey. The refined survey was then distributed to a cohort of core Internal Medicine residents electronically after attendance at an academic retreat teaching residents about advocacy through didactic sessions. RESULTS: The survey was completed by 76 residents with a response rate of 68%. The majority agreed to accept an advocacy role for societal health needs beyond caring for individual patients. Most confirmed their ability to identify health determinants and reaffirmed the inherent requirements for health advocacy. While involvement in health advocacy was common during high school and undergraduate studies, 76% of residents reported no current engagement in advocacy activity, and 36% were undecided if they would engage in advocacy during their remaining time as residents, fellows or staff. The common barriers reported were insufficient time, rest and stress. CONCLUSIONS: Medical residents endorsed the role of health advocate and reported proficiency in determining the medical and bio-psychosocial determinants of individuals and communities. Few residents, however, were actively involved in health advocacy beyond an individual level during residency due to multiple barriers. Further studies should address these barriers to advocacy and identify the reasons for the discordance we found between advocacy endorsement and lack of engagement.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".