MétaCan
Menu
Back to cohort
Record W4416449297 · doi:10.1186/s12909-025-08218-z

Perceptions, barriers, and career priorities among prospective medical school applicants in Scotland

2025· article· en· W4416449297 on OpenAlexaboutno aff
Courtney Krstić, Emma Fletcher, Clare Owen, Sally Curtis, Paul Garrud, Gail Nicholls

Bibliographic record

VenueBMC Medical Education · 2025
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Medical schoolVariety (cybernetics)PerceptionWork (physics)Prospective cohort study

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.000

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.

Opus teacher head0.009
GPT teacher head0.343
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBMC Medical EducationSame topicMedical Education and AdmissionsFrench-language works237,207