Determinants of willingness to practice medicine in underdeveloped areas
Bibliographic record
Abstract
Purpose Appropriate access to formally-trained health workers for people living in rural and underdeveloped areas is a continuing challenge worldwide. The purpose of this paper is to investigate the willingness of formally-trained health workers to practice in underdeveloped areas and its main determinants among medical students in the western provinces of Iran. Design/methodology/approach A total of 753 medical students from four provinces in western Iran (Kermanshah, Ilam, Lorestan and Kurdistan) were surveyed cross-sectionally in 2017. A self-administrated questionnaire was used to collect data on sociodemographic characteristics, willingness to practice in underdeveloped areas, intrinsic (e.g. desire to help others and self-interest in medicine) and extrinsic (e.g. the high income of physicians and social prestige) motivations of the study population. Multivariable logistic regression was used to identify the main determinants of willingness to practice in underdeveloped areas among medical students after their graduation. Findings The results indicated that 58.3 percent of students were willing to practice in underdeveloped areas. While 59 percent of the study population had a strong extrinsic motivation to study medicine, the remaining 41 percent of the study population had a strong intrinsic motivation to study medicine. The logistic regression results indicated that low parental professional and educational status, an experience of living in rural areas and having strong intrinsic motivation were associated with greater willingness to practice in underdeveloped areas. Originality/value This is the first study to investigate the willingness to practice in underdeveloped areas and its main determinants among medical students in the west of Iran.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".