Does prior healthcare experience predict success on clinical courses and add value to admissions processes?
Bibliographic record
Abstract
Abstract Objectives This work sought to assess whether prior clinical experience provided any guide to likely course achievement from three completed cohorts of Physician Associates at the University of Sheffield. Methods Sixty students who entered the PA course at TUoS since it began in 2016 were included in the study. Each students’ original course application was reviewed for healthcare experience and mapped against first sit examination scores. Statistical analysis was undertaken with a two-tailed t-test. Results No correlation was found between previous healthcare experience and performance in examinations. Students with previous healthcare experience performed slightly worse than those without in the OSCE examination but not at a level of statistical significance. Conclusions The use of clinical experience as part of the criteria of entry does not predict success on a Physician Associate course. We support the position of the 2010 Ottawa conference that quality assured methodologies along with objective cut offs for previous academic attainment are the most appropriate way to select students for clinical courses.
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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 | 0.001 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".