Factors influencing medical students in a lower-middle income country to consider psychiatry as a career option
Bibliographic record
Abstract
Objective: To assess and identify the environmental, curriculum, teaching related factors and preconception about psychiatry that influence medical students' attitudes toward psychiatry careers after completing psychiatry rotations. Methods: This is a cross-sectional study involving fifth- and sixth-year medical students of four public medical schools in Ghana. Data was analyzed using chi-square test and logistic regression analysis. Results: Out of 1,041 clinical year medical students from the four public medical schools in Ghana, 475 students completed survey forms and provided responses related to their preference for a psychiatry career following the completion of a clinical rotation, yielding a response rate of (45.63%). Medical students who were identified as female (OR = 1.55; 95% CI: 1.01-2.35), were in their sixth year (OR = 1.65; 95% CI: 1.06-2.58), had diaspora-based psychiatrists participate in their clinical training (OR = 1.7; 95% CI: 1.10-2.62), and had considered psychiatry careers before undertaking psychiatry clinical rotation (OR = 3.19; 95% CI: 1.73-5.87) were more likely to consider psychiatry as a future career after completing a psychiatric rotation, when compared to their respective counterparts. Conclusion: Diverse factors have affected students' consideration of psychiatry as a future career. Health policy makers and health training institutions in low- and middle-income countries should consider designing programs that will impact positively on the preconceptions of medical students about psychiatry careers in addition reaching out to human resources abroad from within their nationals, particularly if these resources exist.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".