Factors associated with plans for early retirement among Ontario family physicians during the COVID-19 pandemic: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Higher numbers of family physicians (FPs) stopped practicing or retired during the COVID-19 pandemic, worsening the family doctor shortage in Canada. Our study objective was to determine which factors were associated with FPs' plans to retire earlier during the COVID-19 pandemic. METHODS: We administered two cross-sectional online surveys to Ontario FPs asking whether they were "planning to retire earlier" as a result of the pandemic during the first and third COVID-19 pandemic waves (Apr-Jun 2020 and Mar-Jul 2021). We used logistic regression to determine which factors were associated with early retirement planning, adjusting for age. RESULTS: The age-adjusted proportion of FP respondents planning to retire earlier was 8.2% (of 393) in the first-wave and 20.5% (of 454) in the third-wave. Planning for earlier retirement during the third-wave was associated with age over 50 years (50-59 years odds ratio (OR) 5.37 (95% confidence interval (CI):2.33-12.31), 60 years and above OR 4.18 (95% CI: 1.90-10.23)), having difficulty handling increased non-clinical responsibilities (OR 2.95 (95% CI: 1.79-4.94)), feeling unsupported to work virtually (OR 1.96 (95% CI: 1.19-3.23)) or in-person (OR 2.70 (95% CI: 1.67-4.55)), feeling unable to provide good care (OR 1.82 (95% CI: 1.10-3.03)), feeling work was not valued (OR 1.92 (95% CI: 1.15-3.23)), feeling frightened of dealing with COVID-19 (OR 2.01 (95% CI: 1.19-3.38)), caring for an elderly relative (OR 2.36 (95% CI: 1.69-3.97)), having difficulty obtaining personal protective equipment (OR 2.00 (95% CI: 1.16-3.43)) or difficulty implementing infection control practices in clinic (OR 2.10 (95% CI: 1.12-3.89)). CONCLUSIONS: Over 20% of Ontario FP respondents were considering retiring earlier by the third-wave of the COVID-19 pandemic. Supporting FPs in their clinical and non-clinical roles, such that they feel able to provide good care and that their work is valued, reducing non-clinical (e.g., administrative) responsibilities, dealing with pandemic-related fears, and supporting infection control practices and personal protective equipment acquisition in clinic, particularly in those aged 50 years or older may help increase family physician retention during future pandemics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".