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Record W4411055053 · doi:10.2196/67292

Harm Reduction Contingency Management for Stimulant Use Reduction and Antiretroviral Therapy Adherence in HIV Primary Care: Protocol for an Implementation Effectiveness Study

2025· article· en· W4411055053 on OpenAlexvenueno aff
Gabriela Steiner, Stefan Baral, Elise D. Riley, Steven Shoptaw, Gabriel Chamie, Lauren Suchman, Kelly R. Knight, Phillip O. Coffin, Ayesha Appa

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute on Drug Abuse
KeywordsHarm reductionPreprintProtocol (science)StimulantContingency managementMedicineHuman immunodeficiency virus (HIV)Reduction (mathematics)Primary carePsychologyMedical emergencyNursingAlternative medicineFamily medicinePsychiatryIntervention (counseling)Computer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Stimulant use disorder has been linked with medication nonadherence and mortality among people living with HIV. Contingency management (CM) is a strategy incentivizing measurable behavior change that is recommended as the first-line treatment for stimulant use disorder and can support antiretroviral therapy (ART) adherence. However, CM is not widely implemented, in part due to feasibility concerns. Although reductions in substance use short of full abstinence can improve health outcomes, CM programs typically target complete abstinence from stimulant use rather than reduction. To optimize care for safety-net populations living with comorbid stimulant use disorder and HIV, we designed a novel CM program incentivizing both stimulant use reduction and ART adherence in the HIV ambulatory setting. OBJECTIVE: We aimed to (1) evaluate the feasibility of once-weekly CM in safety-net HIV ambulatory care and (2) assess the acceptability of CM among participants and care providers. METHODS: We will conduct a pilot, single-arm, hybrid implementation effectiveness trial offering a novel CM intervention in 2 low-barrier, ambulatory HIV clinics. Patients with stimulant use disorder and suboptimal ART adherence will be offered 12 weeks of once-weekly CM including incentives for positive-tenofovir and negative-stimulant results on urine point-of-care assays. We will assess stimulant use once weekly using tests with a 4-day detection window, allowing participants to use stimulants during select days of the week but earn incentives by reducing their frequency of use from near-daily use. We will assess feasibility and acceptability using quantitative process methods and qualitative in-depth interviews, guided by the RE-AIM (reach, effectiveness, acceptability, implementation, and maintenance) evaluation framework. We will define preliminary effectiveness by proportion of stimulant-negative and tenofovir-positive urine tests, as well as changes in HIV viral suppression before and after participation. RESULTS: Recruitment and CM visits have concluded as of September 2024. Quantitative and qualitative evaluation is underway and is expected to continue through October 2025. CONCLUSIONS: This novel CM program offers dual incentives targeting stimulant use reduction and ART adherence. We hypothesize that incentivizing stimulant use reduction is acceptable to our target safety-net population. Demonstration of a feasible, acceptable model may serve as a first step toward wider use of stimulant-reduction CM in the safety-net setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT06564792; https://clinicaltrials.gov/study/NCT06564792. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/67292.

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)0.042
metaresearch head score (Gemma)0.032
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 score0.099
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.032
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0030.003
Science and technology studies0.0050.003
Scholarly communication0.0040.003
Open science0.0040.003
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0990.012

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 head0.266
GPT teacher head0.609
Teacher spread0.343 · 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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