A Peer Support Specialist–Delivered Sexual and Intimate Partner Violence Prevention Program for Women in Substance Use Treatment: Protocol for a Single-Arm Trial
Bibliographic record
Abstract
BACKGROUND: Women in substance use treatment are disproportionately affected by violence. Both a history of violence and substance use place women at risk for cumulative exposure to violence and adverse outcomes, including mental and physical health problems. Interventions are urgently needed to reduce these health disparities by preventing initial and repeated exposure to sexual and intimate partner violence among women with substance use disorders (SUDs). The Healthy Relationships and Interpersonal Violence Education (THRIVE) program adapts evidence-based strategies for this population and is informed by the information, motivation, behavioral skills theoretical model. Topics include the intersection of substance use and violence, consent, risk detection, protective behavioral strategies, and help seeking. THRIVE uses a novel approach by delivering the program via peer support specialists (PSSs), trained advocates in recovery from SUDs who can help overcome barriers to care, including stigma and accessibility. OBJECTIVE: The first objective is to determine program acceptability and feasibility. The second objective is to determine the preliminary effectiveness of THRIVE, including its effect on violence-related knowledge and attitudes, protective behaviors, exposure to sexual and intimate partner violence, substance use, and mental health. METHODS: The study entailed a single-arm trial of THRIVE with 71 women in behavioral and medication-assisted substance use treatment, recruited from 3 outpatient and residential treatment sites. Interview data assessing intervention acceptability and feasibility were collected from participants and PSSs. Participants completed assessments at 4 time points over 3 months (baseline, after the intervention, and 1- and 3-month follow-ups). Self-report questionnaires assessed (1) violence prevention knowledge, attitudes, and behaviors; (2) exposure to sexual and intimate partner violence; and (3) substance use and mental health. To determine acceptability and feasibility, both quantitative and qualitative data were collected on feasibility (recruitment and retention), adherence, and acceptability (engagement, perceived usefulness, barriers and facilitators to participation and adoption, and working alliance with PSSs). RESULTS: Of the 92 women recruited and enrolled, 71 (77%) completed the intervention, 58 (63%) completed the 1-month follow-up, and 44 (48%) completed the 3-month follow-up between June 2024 and March 2025. The mean age of enrolled participants was 35 (SD 9.87) years, and the majority were White (n=79, 86%), followed by Black (n=4, 4%) and other racial and ethnic identities (n=7, 8%). CONCLUSIONS: THRIVE will address critical gaps in the field by (1) expanding violence prevention strategies to SUD treatment settings, (2) integrating sexual and intimate partner violence prevention, (3) incorporating a focus on illicit substance use, and (4) engaging PSSs to overcome barriers to care. The long-term objective of this project is to develop an accessible, scalable, and efficacious prevention program that reduces the incidence of exposure to sexual and intimate partner violence, substance use, and violence-related mental health disorders for women in substance use treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT06608979; https://clinicaltrials.gov/study/NCT06608979. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/68673.
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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 | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.073 | 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".