Combined Motivational Interviewing and Ecological Momentary Intervention to Reduce Hazardous Alcohol Use Among Sexual Minority Cisgender Men and Transgender Individuals: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Sexual minority cisgender men and transgender (SMMT) individuals, particularly emerging adults (aged 18-34 years), often report hazardous drinking. Given that alcohol use increases the likelihood of HIV risk behaviors, and HIV disproportionately affects SMMT individuals, there is a need to test interventions that reduce hazardous alcohol use and subsequent HIV risk behaviors among this population. Ecological momentary interventions (EMIs), which use mobile phones to deliver risk reduction messages based on current location and behaviors, can help to address triggers that lead to drinking in real time. OBJECTIVE: This study will test an EMI that uses motivational interviewing (MI), smartphone surveys, mobile breathalyzers, and location tracking to provide real-time messaging that addresses triggers for drinking when SMMT individuals visit locations associated with hazardous alcohol use. In addition, the intervention will deliver harm reduction messaging if individuals report engaging in alcohol use. METHODS: We will conduct a 3-arm randomized controlled trial (N=405 HIV-negative SMMT individuals; n=135, 33% per arm) comparing the following conditions: (1) Tracking and Reducing Alcohol Consumption (a smartphone-delivered 4-session MI intervention), (2) Tracking and Reducing Alcohol Consumption and Environmental Risk (an EMI combining MI with real-time messaging based on geographic locations that are triggers to drinking), and (3) a smartphone-based alcohol monitoring-only control group. Breathalyzer results and daily self-reports will be used to assess the primary and secondary outcomes of drinking days, drinks per drinking day, binge drinking episodes, and HIV risk behaviors. Additional assessments at baseline, 3 months, 6 months, and 9 months will evaluate exploratory long-term outcomes. RESULTS: The study is part of a 5-year research project funded in August 2022 by the National Institute on Alcohol Abuse and Alcoholism. The first 1.5 years of the study will be dedicated to planning and development activities, including formative research, app design and testing, and message design and testing. The subsequent 3.5 years will see the study complete participant recruitment, data collection, analyses, report writing, and dissemination. We expect to complete all study data collection in or before January 2027. CONCLUSIONS: This study will provide novel evidence about the relative efficacy of using a smartphone-delivered MI intervention and real-time messaging to address triggers for hazardous alcohol use and sexual risk behaviors. The EMI approach, which incorporates location-based preventive messaging and behavior surveys, may help to better understand the complexity of daily stressors among SMMT individuals and their impact on hazardous alcohol use and HIV risk behaviors. The tailoring of this intervention toward SMMT individuals helps to address their underrepresentation in existing alcohol use research and will be promising for informing where structural alcohol use prevention and treatment interventions are needed to support SMMT individuals. TRIAL REGISTRATION: ClinicalTrials.gov NCT05576350; https://www.clinicaltrials.gov/study/NCT05576350. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/55166.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.089 | 0.013 |
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".