Rural clinical placements in clinical education: impact on rural practice interest in Canada: a scoping review.
Bibliographic record
Abstract
Statistics Canada defines rural areas as towns or municipalities outside the commuting zone of larger urban centres.(1) Clinical students included are students in the nursing and medical field at all levels of education. There is an inequitable distribution of healthcare professionals in Canada.(2) Research has shown that 8% of physicians practice in rural areas, whereas 19% of Canadians live in rural areas. (3, 4) This trend has raised concerns about inequitable access to healthcare practitioners in rural regions. Despite concerns raised, there is a lack of comprehensive research investigating incentives for nursing and medical students to stay and practice in rural settings. Furthermore, much of the research that investigates healthcare student settlement in rural areas is outdated, and given the COVID-19 pandemic, many intentions have changed. Objective This scoping review seeks to explore the influence of rural clinical placements on the choice of practice locations among nursing and medical students in Canada. The aim is to address the critical gap in healthcare provision in rural areas by assessing whether experiential learning in these settings encourages graduates to pursue careers in similarly underserved areas. In studying the effectiveness of clinical placements on self-reported interest, methods of improving long-term outcomes for primary healthcare staffing in rural areas can be evaluated and applied to current training. The goal is to address disparities in healthcare accessibility and gain an understanding of policy development and educational practices. Design A scoping review Methodology The review will synthesise available qualitative and quantitative literature in English language spanning from 1970 to the present to ascertain the relationship between rural clinical placements during educational training and the subsequent selection of rural practice settings. Publications will be sourced from scientific databases such as CINAHL and Ebscohost. Grey literature will also be included, and journal citations will be searched. Screening will be carried out by two independent reviewers, and all disputes will be settled by a third reviewer.
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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 | 0.015 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.019 | 0.045 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".