Intervention With WhatsApp Messaging to Compare the Effect of Self-Designed Messages and Standardized Messages in Adherence to Antiretroviral Treatment in Young People Living With HIV in a Hospital in Lima, Peru: Protocol for a Nonblinded Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Young people living with HIV face challenges in consistently adhering to antiretroviral therapy (ART). Although mobile health interventions, particularly those using SMS text messaging, have been implemented to improve ART adherence, many lack a focus on specific behavioral mechanisms. Interventions incorporating behavioral change techniques (BCTs), especially those emphasizing customization, may enhance effectiveness. WhatsApp offers potential for delivering tailored, behaviorally grounded interventions with diverse communication features. We hypothesize that WhatsApp messages self-designed by participants, with spontaneous targeting of BCTs, could be more effective than standard WhatsApp messages designed by the researchers to improve ART adherence. OBJECTIVE: The objective of this study is to evaluate the effectiveness of WhatsApp messages created by participants (self-designed) compared to WhatsApp messages designed by the researchers (standardized) over adherence to ART at 16 weeks of intervention in young people living with HIV who receive HIV care under routine conditions at a public hospital in Lima, Peru. METHODS: A 2-arm randomized controlled trial with a parallel assignment of 1:1, with no blinding of study intervention, was performed. Eligible participants are consenting people living with HIV aged 18-29 years who receive HIV care at the study center and whose mobile phones support WhatsApp. Following informed consent and a baseline survey on clinical and personal preferences (eg, timing and frequency of messages), participants are randomized to the control group (messages designed by the research team) or to the experimental group (messages designed by participants), stratified by sex, educational level, current ART intake, and history of ART abandonment. Participants in both groups receive up to 3 WhatsApp messages per week for 16 weeks. ART adherence, the primary outcome, is measured using the Simplified Medication Adherence Questionnaire (SMAQ) at 4, 8, 12, and 16 weeks. Monthly feedback questionnaires on user experience are also administered. The WhatsApp chat format allows two-way communication between participants and the research team throughout the study. We will compare ART adherence between 2 groups at 16 weeks under the intention-to-treat principle, with no interim analysis planned. Based on an estimated 10% difference in adherence, 78.9% power, and a 2-sided α of .05, the target sample size was set at 120, later increased to 131 to include a 2-week pilot phase. RESULTS: In March 2024, we started enrolling and randomizing participants. The study follow-up will continue until the last participant completes 16 weeks of intervention (November 2024). As of February 2025, we are in the process of data curation. CONCLUSIONS: This trial will compare the effectiveness of standardized vs self-designed WhatsApp messages on ART adherence measured at 16 weeks among young people living with HIV receiving routine care in a low-resource setting in Lima. TRIAL REGISTRATION: ClinicalTrials.gov NCT06500013; https://clinicaltrials.gov/ct2/show/NCT06500013. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/66941.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.004 |
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".