Assessing Antimicrobial Resistance in Papillomavirus-Related Infections: A Comprehensive Review of Prevalence, Impact on Treatment Strategies, and Implications for Disease Control Efforts.
Bibliographic record
Abstract
Aims: Assessment is a key promoter of student learning and in setting appropriate standards. In this review, we explore and assess current evidence on the assessment and evaluation of prescribing competencies, through a formal systematic literature review and a review of policies of regulatory bodies. We aim to make recommendations to promote existing best practice but also suggest additional steps for both institutional and national practice. Methods: PubMed®, Embase®, the Allied and Complementary Medicine and CINAHL databases were systematically searched in August 2023 for studies in English from Europe, United States of America, Canada, Australia and New Zealand that reported assessment of prescribing competencies among medical and nonmedical students/practitioners. Additional articles were identified through citation tracking. Results: A total of 20,514 articles were retrieved, of which 54 met the inclusion criteria. The largest source of articles was the United Kingdom. Medical students represented the largest population studied. Written assessments largely utilised Selected Response formats while skills assessments in educational environments were varied in format, including scenario-based skills tests and OSCEs. Test reliability was generally described using Classical Test Theory. None of the included studies considered differential attainment by students with protected characteristics. Conclusion: Research on assessment in prescribing competencies would benefit from structured reporting of methods and findings. Estimation of the predictive validity of assessments, at both national and institutional levels, is essential. This would help establish whether OSCEs or similar tests have incremental predictive validity over written tests. Situational Judgement Tests would be a valuable addition to assessment practices.
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 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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".