The Good, the Bad and the Necessity of Locum Tenens
Bibliographic record
Abstract
Context: Recent Family Physician graduates practicing as locum tenens has been sometimes presented as a double-edged sword in addressing the Family Medicine workforce crisis. While the concept of locums dates back to the 1970s, examination of the advantages and disadvantages that drive the decision to do locums is needed in the current context. Objective: To explore the factors influencing early career family physicians’ (FPs) decision to do locums. Study Design and Analysis: Constructivist Grounded Theory (CGT) study using in-depth interviews via Zoom. Analysis conducted according to CGT methodology. Setting: FP practices in Ontario, Canada. Population Studied: 38 FPs practicing in Ontario, who completed their training between 2017 to 2022. Results: 9 participants were currently working as a locum, 14 participants had done locums prior to establishing a practice, and 15 had chosen not to locum but go directly into practice, often taking on an available practice. Participants were pulled towards doing locums because they offered opportunities to experience different practice styles and locations, allowed scheduling flexibility, and were viewed as a potential way to enhance work-life balance. Other prominent attractions included the numerous locums available, as well as the opportunity to provide needed coverage for their physician colleagues (e.g. parental leave). Factors pushing participants away from deciding to locum were the inability to provide continuity of care for patients and limited autonomy in altering established clinic protocols. The financial instability of doing locums was also seen as a disadvantage but was lessened by the availability of locums, with long-term locums being most attractive. However, some participants expressed that moving constantly from locum to locum was challenging, first, in identifying a new locum opportunity, and second, in learning about that clinic and the patients for whom they were responsible. Conclusions: Study findings suggest that several push and pull factors influence the decision to do locums following graduation. Reasons for locums showed similarities to previous research but findings illuminate the current status of locum tenens in the context of increasing family physician shortages in Ontario, Canada.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".