Migration patterns of undergraduate medical students in elective exchanges: a prospective online survey
Bibliographic record
Abstract
Background An international and global medical education programme can help to develop health professionals' skillsets and can be a career-defining factor during the progression from student to practising physician. Our aim is to analyse migration patterns of medical students for elective exchanges and identify intentions for continued migration. Specifically, our objectives were to determine the most popular countries and specialty types that students in the medical and health professions intend to go for elective exchanges; to assess the different factors that contribute to a student's choice to migrate for an elective; and to assess factors leading to the intent of permanent migration after completion of study at the home institution. Methods Our research deals with experiential learning in a global health setting through analysis of the trends and patterns of medical students pursuing medical electives worldwide. We used a multilingual online questionnaire, completed by students from 15 different countries across a timeframe of 1 month (April 2018). American, European, Asian, and African universities who are part of the Global Educational Exchange in the Medical and Health professions (GEMx) sent an email with the link to the questionnaire to their medical students. The questionnaire was conducted electronically and participants, who were selected via the school's respective student databases, were asked to complete the survey after their electives had been completed. Findings We analysed responses from 363 students from 15 countries (15 from Kenya; 116 Italy; 20 Nigeria; 16 Rwanda; 5 Ireland; 74 India; 53 Egypt; 47 Indonesia; 11 Mexico; and one response each from Israel, Germany, the Democratic Republic of the Congo, Qatar, Algeria, and Canada). Country mean ages ranged between 21 years and 25 years; 224 respondents (61·7%) were women. The most popular destination country for an elective was the USA (72 students from 10 countries). The most popular specialty types were surgery (74, 20·4%) and internal medicine (56, 15·4%). Students cited expanded medical training (26 [42·6%]) an enhanced CV (18 [29·5%]), and broadened research opportunities (5 [8·2%]) as the most important motivations for choosing an elective exchange to another country. Of those who intended permanent migration (101 [27·8%]), the most frequently cited reason for this migration was the expansion of opportunities in a desired specialty (41 [40·6%]) while the main factor deterring students from permanent migration was the desire to disseminate the acquired learning to native home country health-care providers and systems (159, 60·4%). Interpretation Students' elective experiences abroad not only significant steer the course of their careers as medical professionals, but are also crucial in creating a more holistic educational experience when combined with their home institution's curriculum. Global electives are an initiative that all schools should dedicate resources to pursuing. The elective process is vastly scalable and can be applied at medical schools in all regions of the world. Funding None.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".