A Multilingual, Culturally Competent Mobile Health Intervention to Improve Treatment Adherence Among Women Living With HIV: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Adherence to HIV care is complex, as barriers to care are multidimensional, particularly for ethnic minority women. Mobile health (mHealth) solutions are supportive in improving HIV health care outcomes. In the United States, however, mHealth interventions are not widely implemented in public HIV clinics and have not been customized for women. There is an unmet need for culturally and linguistically appropriate mHealth interventions that address the health care needs of minority women living with HIV. OBJECTIVE: This study aims to describe a protocol investigating the feasibility of an mHealth intervention for treatment adherence among women living with HIV. This is a two-phase, mixed methods, pilot randomized controlled trial that begins with qualitative patient interviews to inform the system design. Participants will be block randomized by language (English, Spanish, and Haitian Creole) to 1 of 2 study arms. METHODS: Women (age ≥18 years) who were followed up at the women's HIV clinic of an academic medical center, with a recent history of nonadherence to HIV care (missed appointments, unsuppressed viral load, or not taking medications as prescribed), will be enrolled. The experimental arm will receive the intervention, which includes health reminders and psychoeducational messaging, plus clinical standard of care reminders. The psychoeducational messaging will target patient-level barriers of HIV stigma and medical mistrust and resilience as a patient-level strength. The control arm will receive standard of care reminders only (ie, mailed appointments and automated telephone calls). All aspects of the study and intervention will be offered in the participants' preferred language. The primary outcome is the feasibility and acceptability of the study. The secondary outcomes are changes in self-reported medication adherence, depression symptoms, HIV stigma, medical mistrust, resilience, and clinic attendance and viral suppression extracted from the participants' medical records. Data will be assessed at baseline (T0) and 2 subsequent clinic visits-approximately 3 to 4 months from the baseline (time 1; T1) and 6 to 9 months from the baseline (time 2; T2). Qualitative data will be transcribed and analyzed iteratively. Bivariate analyses will compare data by the study group (chi-square, odds ratios, and t tests). Exploratory analyses will be conducted for each outcome variable-T1 and T2 values will be compared with values at T0 by the study group. RESULTS: As of March 2020, baseline quantitative data were collected on 54 participants (28 English speakers, 14 Spanish speakers, and 12 Haitian Creole speakers). The first 3 focus groups (1 in each of the 3 languages) were completed, with a total of 20 participants. The findings are currently being integrated into the beta version of the mHealth texting system. CONCLUSIONS: The findings of this novel HIV adherence intervention may shed light on the barriers and facilitators of HIV health care and the mechanisms of an mHealth intervention that is customized for ethnic minority women living with HIV. TRIAL REGISTRATION: ClinicalTrials.gov NCT03738410; https://clinicaltrials.gov/ct2/show/NCT03738410. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17656.
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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 | 0.038 | 0.034 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.094 | 0.014 |
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".