Rural doctor quota students in Germany – who are they? Data on first year students from two cohorts in the federal state of Saxony
Notice bibliographique
Résumé
The lack of physicians in rural areas is a universal problem. To increase the attractiveness of rural practice for medical students, the contribution of medical schools is undisputed. However, much of the evidence on interventions before and during undergraduate education comes from countries with large areas and low population density like Australia and Canada. In Germany, selective admission to medical studies for students who agree to become rural general practitioners is still a new concept. The aim of this study was to assess the sociodemographic characteristics, attitudes and career aspirations of the rural doctor quota students from one medical school in Germany compared to their non-quota counterparts. For this cross-sectional study, a paper-based anonymous questionnaire was distributed to all first year medical students at Leipzig University in two consecutive study years.Descriptive analyses and group differences were calculated using SPSS. The response rate was 87.3% with n = 604 completed questionnaires and 40 (6.6%) students self-classified as rural doctor quota students. Quota students grew up in rural areas significantly more often than their counterparts and had more working experience in the medical field. General practice was the preferred career option for 64.1% (25/39, versus 2.7% [15/549] of non-quota students). Working self-employed in one’s own medical practice was the preferred option for 71.1% (27/38) of quota students (vs. 28.0% [153/546] of non-quota students). Quota students valued a broad spectrum of patients, a long-term doctor–patient relationship, employee management and prestige more highly than their fellow students. Students from the rural doctor quota largely exhibit characteristics and attitudes that are compatible with future rural practice, despite showing little differences in sociodemographic items such as age and marital status. Not all students agree with the program objective. To demonstrate an impact on the health services, longitudinal data is necessary to monitor career choices over time.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 tête enseignante, 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 ».