Push and Pull Factors of Emigration among Physicians in Nigeria
Bibliographic record
Abstract
Physician emigration is escalating in developing countries. In Nigeria, this massive brain drain has gained the popular moniker ‘Japa syndrome’. This survey used a cross-sectional design to determined the factors causing physicians’ brain-drain from Nigeria. A convenience and snowball sampling were used, and 295/400 attendees of a cardiovascular symposium responded to comprehensive self-administered questionnaires (73.7% response rate). Most participants (79.4%) were aged 20-39 years (Mean 35 years SD ±10.17); female (58.6%); married (58.4%) and a family size below six (73.6%). About 85.8% were employed, and 55.9% worked in private establishments. The top three attractive destinations were UK (50.5%), Canada (43.3%), and USA (37.9%). The most frequent push factors found were low remuneration (71.2%), insecurity (62.7%), and difficult working environments (55.9%). Postgraduate-training frustrations (38.6%), and limited educational opportunities for oneself (37.6%), children (26.4%), or spouse (19.7%) were the least. High earning potential (76.6%), career growth opportunities (70.8%), and high-level equipment/technology (54.9%) were the most frequent pull factors. This practice threatens Nigeria's health system and should be addressed multi-sectorally. To reverse this ugly trend, we have to boost physicians’ remuneration, improve work environments and security. Providing innovative education and digital technology would also promote physicians’ retention.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".