Community pharmacists’ acceptance of prescribing pre-exposure prophylaxis (PrEP) for human immunodeficiency virus (HIV)
Bibliographic record
Abstract
Background: Pre-exposure prophylaxis (PrEP) for human immunodeficiency virus (HIV) prevention is highly effective. Pharmacists can increase PrEP accessibility through pharmacist prescribing. This study aimed to determine pharmacists' acceptance of a pharmacist PrEP prescribing service in Nova Scotia. Methods: A triangulation mixed methods study consisting of an online survey and qualitative interviews was conducted with Nova Scotia community pharmacists. The survey questionnaire and qualitative interview guide were underpinned by the 7 constructs of the Theoretical Framework of Acceptability (affective attitude, burden, ethicality, opportunity costs, intervention coherence, perceived effectiveness and self-efficacy). Survey data were analyzed descriptively and with ordinal logistic regression to determine associations between variables. Interview transcripts were deductively coded according to the same constructs and then inductively coded to identify themes within each construct. Results: A total of 214 community pharmacists completed the survey, and 19 completed the interview. Pharmacists were positive about PrEP prescribing in the constructs of affective attitude (improved access), ethicality (benefits communities), intervention coherence (practice alignment) and self-efficacy (role). Pharmacists expressed concerns about burden (increased workload), opportunity costs (time to provide the service) and perceived effectiveness (education/training, public awareness, laboratory test ordering and reimbursement). Conclusion: A PrEP prescribing service has mixed acceptability to Nova Scotia pharmacists yet represents a model of service delivery to increase PrEP access to underserved populations. Future service development must consider pharmacists' workload, education and training as well as factors relating to laboratory test ordering and reimbursement.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".