Acceptability of the LetSync App Wireframes for an mHealth Intervention to Improve HIV Care Engagement and Treatment Among Black Partnered Sexual Minority Men: Findings from In-Depth Qualitative Interviews
Bibliographic record
Abstract
BACKGROUND: HIV disparities continue to be a significant challenge affecting Black sexual minority men in the United States. Inadequate engagement and retention of patients in HIV care has been associated with poor health outcomes. Interventions to improve sustained commitment to HIV care are needed. Mobile health interventions can help facilitate access to and use of HIV health services, particularly among individuals at risk for disengaging with care. OBJECTIVE: We designed the LetSync app wireframes for a mobile health intervention using a couple-centered design approach to improve HIV engagement and treatment among Black sexual minority men and their partners. The objective of this study was to gauge future app user interest and elicit feedback to improve the design, development, and usability of the LetSync app. METHODS: We conducted in-depth interviews with 24 Black sexual minority men to assess the acceptability of the LetSync app wireframes between May 2020 and January 2021. Participants reviewed the LetSync app wireframes and provided feedback regarding perceived usefulness and interest in future app use and suggestions for improvement. RESULTS: Participants indicated interest in the future LetSync app and noted that the wireframes' features were acceptable and usable. In our study, the future LetSync app was frequently referred to as a potential resource that could help facilitate users' engagement in HIV care through the following mechanisms: enable scheduling of appointments and timely reminders for clinic visits; help improve HIV medication adherence; encourage and motivate participants to ask questions to their health care provider and stay engaged in conversations during clinic visits; facilitate effective communication by assisting couples with planning, coordination, and management of daily routines; help participants understand their partner's health needs, including access to and use of health care services; and facilitate participants' ability to improve their relationship skills, partner support, and self-efficacy in managing conflict. In addition to near-universal interest in potential daily app use, study participants indicted that they would recommend the LetSync app to other family members, friends, and people in their social networks who are living with HIV. CONCLUSIONS: Our findings revealed considerable interest in future app use for HIV care management, which could possibly increase the chance of the LetSync app being successfully adopted by Black sexual minority men in couples. Owing to its interactive and couple-centered approach, the LetSync app could help improve communication between Black sexual minority men and their partners and health providers. In addition, the LetSync app could provide an acceptable modality for these men to receive support in accessing HIV care services.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".