Variation in Experiences and Attainment in Surgery Between Ethnicities of UK Medical Students and Doctors (ATTAIN): Protocol for a Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: The unequal distribution of academic and professional outcomes between different minority groups is a pervasive issue in many fields, including surgery. The implications of differential attainment remain significant, not only for the individuals affected but also for the wider health care system. An inclusive health care system is crucial in meeting the needs of an increasingly diverse patient population, thereby leading to better outcomes. One barrier to diversifying the workforce is the differential attainment in educational outcomes between Black and Minority Ethnic (BME) and White medical students and doctors in the United Kingdom. BME trainees are known to have lower performance rates in medical examinations, including undergraduate and postgraduate exams, Annual Review of Competence Progression, as well as training and consultant job applications. Studies have shown that BME candidates have a higher likelihood of failing both parts of the Membership of the Royal Colleges of Surgeons exams and are 10% less likely to be considered suitable for core surgical training. Several contributing factors have been identified; however, there has been limited evidence investigating surgical training experiences and their relationship to differential attainment. To understand the nature of differential attainment in surgery and to develop effective strategies to address it, it is essential to examine the underlying causes and contributing factors. The Variation in Experiences and Attainment in Surgery Between Ethnicities of UK Medical Students and Doctors (ATTAIN) study aims to describe and compare the factors and outcomes of attainment between different ethnicities of doctors and medical students. OBJECTIVE: The primary aim will be to compare the effect of experiences and perceptions of surgical education of students and doctors of different ethnicities. METHODS: This protocol describes a nationwide cross-sectional study of medical students and nonconsultant grade doctors in the United Kingdom. Participants will complete a web-based questionnaire collecting data on experiences and perceptions of surgical placements as well as self-reported academic attainment data. A comprehensive data collection strategy will be used to collect a representative sample of the population. A set of surrogate markers relevant to surgical training will be used to establish a primary outcome to determine variations in attainment. Regression analyses will be used to identify potential causes for the variation in attainment. RESULTS: Data collected between February 2022 and September 2022 yielded 1603 respondents. Data analysis is yet to be competed. The protocol was approved by the University College London Research Ethics Committee on September 16, 2021 (ethics approval reference 19071/004). The findings will be disseminated through peer-reviewed publications and conference presentations. CONCLUSIONS: Drawing upon the conclusions of this study, we aim to make recommendations on educational policy reforms. Additionally, the creation of a large, comprehensive data set can be used for further research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40545.
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 | 0,008 | 0,008 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».