How early career family physicians integrate social accountability in practice: Findings from a multi-provincial study
Bibliographic record
Abstract
Context: Social accountability is a focal point in medical education and informs evolving roles and expectations of family physicians. Research pertaining to social accountability in medicine has focused on undergraduate education, and there is more limited research about postgraduate training and early practice. Objective: We explored how early career family physicians (ECFPs) integrate social accountability in practice, including factors that influence practice choices and challenges related to social accountability. Study Design and Analysis: In this qualitative study we first applied a framework for defining social accountability at three different levels (individual patient, community, and system), and used inductive thematic analysis to explore how ECFPs make choices about practice and challenges related to social accountability. Setting or Dataset: We used data collected through a larger mixed-methods study investigating factors shaping practice intentions and choices of ECFPs and residents, with semi-structured interviews conducted in British Columbia, Ontario, and Nova Scotia. Population Studied: 31 ECFPs, with n=15 from NS, n=7 from BC, and n=9 from ON. Results: Social accountability was most commonly discussed at individual and community levels of patient proximity, with limited examples at the system level. We found that physician values are a strong driver of social accountability in practice, and these informed the choice to pursue medicine and family medicine specifically. ECFPs valued providing holistic care and professional satisfaction was closely tied to social accountability. Practice models were described as barriers or enablers of socially accountable practice. Participants highlighted that the unsupported fee-for-service practice particularly hinders ability to address complex needs. Conclusions: Findings highlight the importance of adequately preparing physicians to engage with policy and systems level issues pertaining to health. Values rooted in social accountability that predate medical education demonstrate an opportunity to shift education away from instilling social accountability as a value, and toward curricula that can provide physicians with the tools required to engage with community and system level policy issues. It will also be necessary to continuously support practice environments that are conducive to practicing social accountability across all levels.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".