Variation in Experiences and Attainment in Surgery Between Ethnicities of UK Medical Students and Doctors (ATTAIN): Protocol for a Cross-Sectional Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".