Determinants of Residency Program Choice in Two Central African Countries: An Internet Survey of Senior Medical Students
Bibliographic record
Abstract
Background: Central African countries have an increasing burden of disease, low specialist workforce densities, and under-resourced postgraduate medical education. The residency program choice of today’s medical students will determine specialist workforce density in the near future. This study aims to elucidate the factors that influence the choice of residency programs among medical students of two Central African countries. Methods: We designed an online questionnaire in French and English with closed-ended, open-ended, and Likert scale questions. Links to both forms were shared via the international messaging application, WhatsApp, and data were collected anonymously for one month. Respondents were sixth- and seventh-year medical students enrolled in nine Cameroonian and Congolese schools. The threshold of significance was set at 0.05 for bivariate analysis. Results: There were 149 respondents in our study, 51.7% were female, and 79.2% were from Cameroon. Almost every student (98%) expressed the wish to specialize, and a majority (77.2%) reported an interest in a residency program abroad. Preferred destinations were France (13.7%), Canada (13.2%), and the U.S.A. (11.9%). The most popular specialties were cardiology (9.4%), pediatrics (9.4%) and obstetrics and gynecology (8.7%). The choice of specialty was made based on the respondent’s perceived skills (85.9%), anticipated pay after residency (79.2%), and patient contact (79.2%). Conclusion: Understanding which specialties interest Cameroonian and Congolese medical students and the reasons for these choices can help develop better local programs.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.009 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".