Evidence of Efficacy of the My Personal Health Guide Mobile Phone App on Antiretroviral Therapy Adherence Among Young African American Men Who Have Sex With Men at 1 Month: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Young African American men who have sex with men (AAMSM) experience disproportionately high HIV incidence and are less likely to achieve viral suppression compared to White men who have sex with men, an outcome that relies on antiretroviral therapy (ART) adherence. We created My Personal Health Guide, a talking relational agent-based mobile health app to improve ART adherence among young AAMSM. OBJECTIVE: The objective was to determine the efficacy of My Personal Health Guide on improving ART adherence among young AAMSM living with HIV. METHODS: We implemented a randomized controlled trial among young (aged 18-34 years) AAMSM with nonoptimal ART adherence throughout the United States between February 2020 and September 2023, predominantly through social media and by word of mouth, provider referral, and fliers in selected health care settings. Participants were randomized in a 1:1 ratio using permuted blocks of 8 to the intervention, My Personal Health Guide, or the attention control arm. ART adherence was assessed with Wilson's 3-item self-reported adherence measurement and dichotomized at ≥80%. Logistic regression models using backward selection were used to evaluate the efficacy of My Personal Health Guide on ≥80% ART adherence at 1-month follow-up. RESULTS: Among the 253 AAMSM at baseline, most (n=180, 71.1%) self-reported being ≥80% adherent to ART, over half (n=145, 57.3%) resided in the Southern United States, but all US regions were represented, nearly half (n=175, 42.3%) had some college education, over one-third (n=96, 37.9%) had less than optimal literacy, and approximately one-quarter (n=61, 24.1%) experienced housing insecurity in the past 6 months. The sample for analysis of the My Personal Health Guide app efficacy was 131 (intervention=76 and control=55). The odds of being ≥80% adherent to ART at 1-month follow-up were 3.97 (95% CI 1.26-12.55) times greater among participants randomized to the My Personal Health Guide app compared to the controls, after adjusting for ART adherence at baseline, treatment adherence self-efficacy, and ever being incarcerated. Additionally, for every 1-point increase in the HIV Treatment Adherence Self-Efficacy Scale, the odds of ≥80% ART adherence increased by 3% (odds ratio 1.03, 95% CI 1.00-1.06). CONCLUSIONS: Participants randomized to receive My Personal Health Guide reported nearly 4 times greater odds of being ≥80% adherent to ART compared to the attention control group at 1-month follow-up. To our knowledge, this is the first randomized controlled trial demonstrating improved medication adherence using a relational agent-based behavioral intervention. These findings provide evidence of short-term efficacy of My Personal Health Guide to improve ART adherence among young AAMSM. We recommend further research on the inclusion of relational agents in behavioral research, especially in populations affected by stigma and nonoptimal health literacy, where this nonhuman supportive and educational approach may be complementary to health care systems. TRIAL REGISTRATION: ClinicalTrials.gov NCT04217174; https://clinicaltrials.gov/study/NCT04217174.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".