The Florida Mobile Health Adherence Project for People Living With HIV (FL-mAPP): Longitudinal Assessment of Feasibility, Acceptability, and Clinical Outcomes
Bibliographic record
Abstract
BACKGROUND: For people living with HIV (PLWH), antiretroviral therapy (ART) adherence is crucial to attain better health outcomes. Although research has leveraged consumer health information technologies to enhance ART adherence, no study has evaluated feasibility and clinical outcomes associated with the usage of a commercially available, regularly updated mobile health (mHealth) app for improving ART adherence among PLWH. OBJECTIVE: This study aimed to assess the feasibility, acceptability, and clinical outcomes of Care4Today, an existing, free, biprogrammatic mHealth app for improving ART adherence among PLWH. METHODS: The Florida mHealth Application Adherence Project (FL-mAPP) was a 90-day longitudinal pilot study conducted in 3 public HIV clinics in Florida, United States. After obtaining informed consent, 132 participants completed a survey and then were given the option to try an existing mHealth app to help with ART adherence. Of these, 33.3% (44/132) declined, 31.1% (41/132) agreed but never used the app, and 35.6% (47/132) used the app. All were asked to complete follow-up surveys at 30 days and 90 days after enrollment. Usage data were used to assess feasibility. Clinical outcomes of self-reported ART adherence and chart-obtained HIV viral load and CD4+ T-cell counts were compared among those who used the platform (users) versus those who did not (nonusers). Participants and HIV care providers also provided responses to open-ended questions about what they liked and did not like about the app; comments were analyzed using thematic analysis. RESULTS: Of 132 participants, 47 (35.6%) and 85 (64.4%) were categorized as users and nonusers, respectively. Among users, a Kaplan-Meier plot showed that 25 persons (53%) continued using the app after the 90-day follow-up. At 30-day follow-up, 13 (81.3%) of those who used the mHealth app reported ≥95% ART adherence, compared with 17 (58.6%) nonusers (P=.12). Overall, 39 (82%) users liked or somewhat liked using the platform. Participants' favorite features were medication reminders, ability to create custom reminders, and adherence reports. CONCLUSIONS: This longitudinal study found that a commercially available medication adherence mHealth app was a feasible and acceptable intervention to improve ART adherence among PLWH and engaged in clinical care across 3 public HIV clinics in the state of Florida. Overall, participants liked the Care4Today app and thought the medication reminders were their favorite feature. Generally, self-reports of ART adherence were better among users than nonusers, both at 30- and 90-day follow-ups. Further clinical research needs to address user fatigue for improving app usage.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".