Implementation of harm reduction services for people who use drugs provided by pharmacy staff: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The disparities and risk trajectories experienced by people who use drugs (PWUD) highlight the critical need for equity-oriented strategies. Pharmacy staff (pharmacists, pharmacy technicians and assistants) make essential contributions to public health, and their role in the response to the drug overdose crisis can be understood as an extension of their public health role. Their involvement in overdose prevention strategies, such as take-home naloxone programmes and prescribed opioid medication management, has been documented. Still, their role in harm reduction services for PWUD has yet to be mapped. This gap has led to challenges when implementing harm reduction services in pharmacy-related settings. This review aims to summarise literature that focuses on the implementation of harm reduction services for PWUD provided by pharmacy staff. METHODS AND ANALYSIS: This scoping review will adhere to the Arksey and O'Malley framework for conducting scoping reviews. The electronic databases MEDLINE, Embase, CINAHL, Web of Science Core Collection, SCOPUS and Google Scholar were searched on 4 June 2024, using terms related to pharmacy staff, PWUD and harm reduction services. This review will consider peer-reviewed literature in English, Spanish and French focused on describing or evaluating the implementation of harm reduction services for PWUD by pharmacy staff. Two independent reviewers will screen titles and abstracts and conduct the full-text screening to determine eligibility. Findings will be presented as a narrative summary and supported by tabular and graphical formats. Knowledge partner engagement will guide all steps in this study. ETHICS AND DISSEMINATION: Formal ethical approval is not required, as primary human or animal data will not be collected. A manuscript summarising the results will be written and submitted to a peer-reviewed journal for publication. Other outlets for dissemination will include local presentations and conference presentations. TRIAL REGISTRATION DETAILS: Open Science Framework (https://osf.io/vn6ht).
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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 | 0.115 | 0.079 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.063 | 0.015 |
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".