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Record W4413871854 · doi:10.2196/72283

Improving Access to HIV Prevention Services in Community Pharmacies in the US Southeast: Protocol for a Hybrid Type 1 Effectiveness-Implementation Study

2025· article· en· W4413871854 on OpenAlexvenueno aff
Daniel I. Alohan, Alexis Hudson, Christina Chandra, Seth Zissette, Rachel Rothman, Sophia A. Hussen, Alvan Quamina, Henry N. Young

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsPreprintPharmacyHuman immunodeficiency virus (HIV)Protocol (science)MedicineComputer scienceFamily medicineWorld Wide WebAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Despite advancements in HIV prevention, many Americans, particularly those from historically underserved communities (eg, racially and sexually minoritized individuals and people who use drugs), continue to face significant barriers to accessing crucial HIV prevention services such as HIV testing and pre-exposure prophylaxis. Integrating these services into community pharmacies is a viable yet underused solution to overcoming access-related challenges. However, few studies have used an implementation science approach to assess the implementation and effectiveness of such services in pharmacy settings. OBJECTIVE: The Pharmacy-Based Access to HIV Prevention Services study aims to develop and evaluate a sustainable pharmacy-based model for increasing access to HIV testing and prevention services (eg, pre-exposure prophylaxis dispensing) in community pharmacy settings. METHODS: We are using a hybrid type 1 effectiveness-implementation study design to evaluate the implementation and effectiveness of HIV testing and prevention services within community pharmacies, particularly among those that offer non-HIV-related screenings (eg, COVID-19, blood pressure, and cholesterol screening) and those that do not. We apply 3 well-established implementation science frameworks-the Exploration, Preparation, Implementation, Sustainment framework, the Consolidated Framework for Implementation Research, and the Systems Engineering Initiative for Patient Safety-to assess multilevel factors influencing the adoption of HIV prevention services in community pharmacy settings. This study consists of three phases: (1) a mixed methods exploration phase to identify barriers and facilitators of implementing HIV prevention services in community pharmacies, (2) a preparation phase to assess the effectiveness of two HIV training programs designed for pharmacy staff, and (3) an implementation and sustainment phase to evaluate the effectiveness and implementation of HIV prevention services in these settings. RESULTS: The Pharmacy-Based Access to HIV Prevention Services study was funded in June 2023 by the National Institute of Mental Health (R01MH123470) and launched in September 2023. Recruitment and enrollment for the first phase, including data collection, are currently underway. We have exceeded our Phase 1 pharmacy staff survey target, with 310 participant surveys completed (goal: 300). Completion is anticipated by early 2026. CONCLUSIONS: Expanding access to HIV prevention services through community pharmacies is a promising and accessible approach to addressing social and health inequities in HIV, supporting the goal of Ending the HIV Epidemic in the United States. Implementation science, with its systematic frameworks, is essential to advancing this goal. Our study is among the first to use an implementation science approach to integrate HIV prevention services within community pharmacies in high-prevalence HIV areas. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72283.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.089
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.089
Threshold uncertainty score0.471

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0890.057
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0050.005
Science and technology studies0.0060.004
Scholarly communication0.0040.005
Open science0.0050.004
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0690.012

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.

Opus teacher head0.803
GPT teacher head0.818
Teacher spread0.016 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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