Willingness and attitudes of the general public towards the involvement of medical students in their healthcare
Bibliographic record
Abstract
OBJECTIVES: To determine if patients allow medical students to perform less invasive procedures compared to more invasive procedures, and how this is related to patient demographics and previous experience with medical students. METHODS: A cross-sectional survey was conducted in six areas of Birmingham, UK. All members of the general public over the age of 18 were eligible, excluding non-English speaking people and those with cognitive impairments. Respondents were asked to rank their willingness for medical students to perform history taking/examinations and clinical procedures of varying degrees of invasiveness. RESULTS: We received a total of 293 responses. For both history taking/examinations and clinical procedures, people were more willing to allow medical students to perform less invasive procedures rather than more invasive procedures. White and older people were more willing to allow all history taking/examinations procedures; additionally, women were more willing to allow history taking. White, female, and older participants were more willing to allow blood pressure measurement; whilst older people and those with previous experience were more willing to allow venepuncture. No significant associations were found for intubation. CONCLUSIONS: The public is less willing for medical students to perform more invasive procedures. This may severely limit opportunities to attain clinical competencies.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".