Competence and confidence with prescribing in pharmacy and medicine: a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Prescribing is a growing scope of practice for pharmacists. The objective of this scoping review is to explore themes within the literature related to prescribing competence and confidence in the disciplines of pharmacy and medicine. METHODS: Online databases MEDLINE, EMBASE and Global Health were used to identify articles from inception to October 2018. Articles describing either the competence or confidence of physician, pharmacist or student prescribing, including inappropriate prescribing and prescribing errors were included. KEY FINDINGS: After applying the inclusion and exclusion criteria, 33 eligible articles remained. Many studies demonstrate that medical students and junior doctors are not competent in prescribing when they enter practice, and their perceived confidence is often higher than their assessed competence. There were fewer studies about pharmacist competence and confidence with prescribing; however, they described pharmacists that felt competent to prescribe but lacked confidence. Themes from the review included self-awareness, lack of education and educational improvements, prescribing errors and resources, prescribing culture and barriers to prescribing, gender differences and benefits to prescribing. CONCLUSIONS: There is little consensus from the outcomes of these studies related to prescribing competence or confidence. While some reflect positively on prescribing competence and confidence, others show major deficits in competence and lack of confidence. Further research needs to be done to evaluate pharmacist competence and confidence with respect to prescribing.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it