Migration patterns of undergraduate medical students in elective exchanges: a prospective online survey
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».