The Impact of UK Medical Students’ Demographics and Socioeconomic Factors on Their Self-Reported Familiarity With the Postgraduate Training Pathways and Application Process: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: UK medical graduates can apply for specialty training after completing a 2-year internship (foundation training). Postfoundation training application requirements vary depending on specialty but fundamentally require key skills such as teaching, research, and leadership. OBJECTIVE: This study investigated whether medical student demographics impact their self-reported familiarity with the Post-Foundation Training Pathways (PFTPs) and Post-Foundation Application Process (PFAP). METHODS: This was a cross-sectional study using a Bristol Online Survey. We invited all UK medical students to answer a range of questions about their demographics. Students were then asked to rank their familiarity with PFTPs and PFAP on a scale of 1 to 5 (1=least familiar and 5=most familiar). The responses were collected between March 2022 and April 2022 and exported for further analysis. Statistical analysis was conducted in Stata (version 17.1; StataCorp) using chi-square tests. RESULTS: A total of 850 students from 31 UK medical schools took part. There was a significant difference between gender and self-reported familiarity with PFTPs (P<.001) and PFAP (P<.001), with male students expressing higher familiarity. Similarly, there was a difference between ethnicity and self-reported familiarity with PFTPs (P=.02) and PFAP (P<.001), with White students more likely to express higher familiarity than their Black, Asian, or Mixed Ethnic counterparts. Lastly, there was an overall difference between medical background and age and self-reported familiarity with PFTPs and PFAP (all P<.001), with students from medical backgrounds and older students being more likely to express higher familiarity. CONCLUSIONS: The impact of gender, ethnicity, age, and medical background on students' self-reported familiarity with PFTPs and PFAP is significant. Further studies are required to evaluate the impact of these factors on tested knowledge of PFTPs and PFAP and whether this impacts the success rate of postfoundation applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".