Target users’ acceptance of a pharmacist-led prescribing service for pre-exposure prophylaxis (PrEP) for human immunodeficiency virus (HIV)
Bibliographic record
Abstract
Background: Pre-exposure prophylaxis (PrEP) for human immunodeficiency virus (HIV) is a highly effective way to reduce virus transmission. There have been increasing calls to improve access to PrEP in Canada. One way to improve access is by having more prescribers available. The objective of this study was to determine target users' acceptance of a PrEP-prescribing service by pharmacists in Nova Scotia. Methods: A triangulation, mixed-methods study was conducted consisting of an online survey and qualitative interviews underpinned by the Theoretical Framework of Acceptability (TFA) constructs (affective attitude, burden, ethicality, intervention coherence, opportunity cost, perceived effectiveness and self-efficacy). Participants were those eligible for PrEP in Nova Scotia (men who have sex with men or transgender women, persons who inject drugs and HIV-negative individuals in serodiscordant relationships). Descriptive statistics and ordinal logistic regression were used to analyze survey data. Interview data were deductively coded according to each TFA construct and then inductively coded to determine themes within each construct. Results: A total of 148 responses were captured by the survey, and 15 participants were interviewed. Participants supported pharmacists' prescribing PrEP across all TFA constructs from both survey and interview data. Identified concerns related to pharmacists' abilities to order and view lab results, pharmacists' knowledge and skills for sexual health and the potential for experiencing stigma within pharmacy settings. Conclusion: A pharmacist-led PrEP-prescribing service is acceptable to eligible populations in Nova Scotia. The feasibility of PrEP prescribing by pharmacists should be pursued as an intervention to increase access to PrEP.
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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 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".