Recruiting and retaining general practitioners in rural practice: systematic review and meta‐analysis of rural pipeline effects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To synthesise quantitative data on the effects of rural background and experience in rural areas during medical training on the likelihood of general practitioners practising and remaining in rural areas. STUDY DESIGN: Systematic review and meta-analysis of the effects of rural pipeline factors (rural background; rural clinical and education experience during undergraduate and postgraduate/vocational training) on likelihood of later general practice in rural areas. DATA SOURCES: MEDLINE (Ovid), EMBASE, Informit Health Collection, and ERIC electronic database records published to September 2018; bibliographies of retrieved articles; grey literature. DATA SYNTHESIS: Of 6709 publications identified by our search, 27 observational studies were eligible for inclusion in our systematic review; when appropriate, data were pooled in random effects models for meta-analysis. Study quality, assessed with the Newcastle-Ottawa scale, was very good or good for 24 studies, satisfactory for two, and unsatisfactory for one. Meta-analysis indicated that GPs practising in rural communities was significantly associated with having a rural background (odds ratio [OR], 2.71; 95% CI, 2.12-3.46; ten studies) and with rural clinical experience during undergraduate (OR, 1.75; 95% CI, 1.48-2.08; five studies) and postgraduate training (OR, 4.57; 95% CI, 2.80-7.46; eight studies). CONCLUSION: GPs with rural backgrounds or rural experience during undergraduate or postgraduate medical training are more likely to practise in rural areas. The effects of multiple rural pipeline factors may be cumulative, and the duration of an experience influences the likelihood of a GP commencing and remaining in rural general practice. These findings could inform government-led initiatives to support an adequate rural GP workforce. PROTOCOL REGISTRATION: PROSPERO, CRD42017074943 (updated 1 February 2018).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it