Evaluating the UK’s first national prescribing assessment for GPs in training using an online survey
Bibliographic record
Abstract
Background GP trainees may not have experienced a systematic and comprehensive education in safe prescribing. Therefore, a self-assessment prescribing review was developed. Aim To determine whether the assessment was feasible, had face validity, and did not disadvantage particular groups of participants. Design & setting An online survey that evaluates the opinions of GPs in training of a prescribing assessment in the UK. All full-time UK trainees who started their final year of GP training in August 2019 undertook the prescribing assessment along with their trainers, after which they completed an online anonymous feedback questionnaire. Method The questionnaire completed by trainees sought their opinions of the assessment, and collected ethnicity and disability data. The trainer questionnaire was similar but did not include any demographic information. Results The questionnaire was completed by 1741 trainees and 1576 trainers. There was no evidence that ethnic group and disability were related to aspects of the review. Most of the trainees (76.4%, n = 1330) and trainers (82.0%, n = 1293) agreed or strongly agreed that the prescribing review was helpful for assessing and learning about the trainee’s prescribing. However, most participants (63.2%, n = 1092) took >4 hours to review their prescriptions. A majority of trainees (90.2%, n = 1571) reported that completing the assessment had resulted in a change in their prescribing practice. Conclusion The majority of trainers and trainees reported that the prescribing assessment was helpful. The study was not able to assess whether there had been an actual change in practice that resulted in an error reduction.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".