New Zealand pharmacists’ views regarding the current prescribing courses: questionnaire survey
Bibliographic record
Abstract
Introduction New Zealand pharmacists must complete a joint prescribing course offered by Otago and Auckland universities only, to be qualified as pharmacist prescribers. Aim To identify knowledge and perceptions of New Zealand registered pharmacists, who are not pharmacist prescribers, on: pharmacist prescribing roles, courses and perceived barriers and facilitators to course uptake. Methods Participants comprised registered practising New Zealand pharmacists (n = 4025), across all New Zealand regions. Invitations to participate in a questionnaire survey were sent in March 2021. Data were analysed using thematic analysis and descriptive statistics. Results The response rate was 12% (482/4025), with 94% community pharmacists. Almost two-thirds (65%) had over 10 years of working experience. Nearly all (95%) agreed that pharmacist prescribing would improve healthcare delivery in New Zealand. Most reported that barriers to pharmacist prescribing course uptake were funding, lack of institutional support, up-to-date pharmacological/pharmaceutical knowledge, and 2 years of experience in collaborative health team prerequisites for enrolment, finding medical supervisors, and lack of remuneration for prescribing roles. Discussion Pharmacist prescribing in New Zealand is still in its growing phase. Optimising uptake of prescribing courses and role requires a multi-level approach including all stakeholders. Government/policymakers should consider pharmacist prescribing training and remuneration in their funding plans. Employing institutions should provide required time and human resources (staff backfills). Training providers should consider methods of course delivery and assessment that are suitable for trainees in full-time employment.
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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 | 0.004 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".