Perceptions, barriers, and career priorities among prospective medical school applicants in Scotland
Notice bibliographique
Résumé
BACKGROUND: Total medical school applicant numbers in the UK are steadily declining. This is a particular problem in the devolved nations including Scotland, where the number of local applicants has not increased in line with the expansion of medical school places. This study aims to understand how prospective Scottish-domiciled medical school applicants perceive medical careers and the NHS, the potential barriers to medical school and which factors are most important when making careers decisions, including whether these factors differ depending on demographic background. METHODS: An online cross-sectional survey was delivered to prospective medical school applicants in S5 and S6 (the last two years of secondary education) Scotland during the 2024–2025 UCAS application cycle. Students were invited to participate if they were considering or have considered medicine as a career in the past. Chi-squared analysis was performed to identify differences in responses by demographics. RESULTS: There were 416 respondents, representing a quarter of the Scottish-domiciled students who applied to medicine during the 2024-25 cycle. There are demonstrable differences in career priorities and perceptions of working as a doctor by ethnicity, sex and widening participation (WP) status. Respondents held generally negative views about the demanding and inflexible nature of working within the NHS, although identified positives such as being able to give back to the community and the variety of work. The majority of respondents had been discouraged from applying to medicine by at least one person, usually due to difficulties in the working lives of doctors, rather than barriers in the application process. CONCLUSIONS: Prospective applicants have concerns about working conditions and careers after graduation which may be impacting their decision on whether to apply for medicine. This necessitates coordinated efforts from medical schools, NHS trusts and other stakeholders to improve the perceptions of doctors and NHS careers generally. The survey will be delivered UK-wide in the 2025-26 application round, to shed light on whether these patterns are seen across the four nations.
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 | 0,001 | 0,057 |
| 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 | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 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 ».