Charting a New Path: Re-constructing the Practice of Comprehensive Family Medicine
Bibliographic record
Abstract
Context: There is a crisis in Family Medicine with a critical decline in family physicians practicing comprehensive care. This shortage threatens the foundation of primary care which is the core of a high functioning health care system. Objective: To explore early career family physicians’ (FPs) decisionmaking process in their choice to practice comprehensive care. Study Design and Analysis: Grounded theory study using in-depth interviews via Zoom, with individual and team analysis. Setting: FP practices in Ontario, Canada. Population Studied: 38 family physicians practicing in Ontario, who completed their residency training within the last 5 years. Results: Participants’ stories revealed their journey in establishing a comprehensive care practice. Many participants began this journey doing locums. Reasons for locuming included: ‘testing the waters’ by experiencing different practice types; flexibility of hours worked with no responsibility for practice management and not being ready to commit to a patient roster. The next juncture in their journey was deciding to commit to a practice (either through purchasing a practice or taking over a practice of a retiring physician). For many participants, this settling into providing patient care from ‘cradle to grave’ took on a new definition, and was described as a ‘hybrid model’. They had much smaller patient rosters, often working 3 days per week providing officebased comprehensive care and 2 days a week practicing in a specific area of interest (e.g. women’s health, dermatology, hospitalist). The hybrid model of practice offered variety and for some mitigated burnout. Like any traveller on a journey, participants faced many contextual challenges that threatened the practice of comprehensive care. These included: the burden of administrative tasks; the deteriorating specialist-family physician relationship; lack of access to team-based models; inadequate remuneration; and a pervasive feeling that Family Medicine is undervalued, leaving them feeling ‘cynical and burned out’. Conclusions: Findings reveal how the definition and practice of comprehensive care is currently under construction influenced by both individual needs and expectations of early career FPs as well as the current context in which they practice. The findings have implications for educators in curriculum planning and for health workforce planning as this ‘hybrid model’ of delivering comprehensive care evolves in Family Medicine.
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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 | 0.036 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.030 | 0.067 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".