Development of a Mobile App to Increase the Uptake of HIV Pre-exposure Prophylaxis Among Latino Sexual Minority Men: Qualitative Needs Assessment
Bibliographic record
Abstract
BACKGROUND: HIV disproportionally impacts Latino sexual minority men (SMM). Uptake of pre-exposure prophylaxis (PrEP), an effective biomedical intervention to prevent HIV, is low in this group compared with White SMM. Mobile health technology represents an innovative strategy to increase PrEP uptake among Latino SMM. OBJECTIVE: We aimed to describe the qualitative process leading to the development of SaludFindr, a comprehensive HIV prevention mobile app aiming to increase PrEP uptake, HIV testing, and condom use by Latino SMM. METHODS: We conducted 13 in-depth interviews with Latino SMM living in the Atlanta area to explore their main barriers and facilitators to PrEP uptake and to analyze their opinions of potential SaludFindr app functionalities. To explore potential app functions, we used HealthMindr, an existing HIV prevention app, as a template and added new proposed features intended to address the specific community needs. RESULTS: We identified general PrEP uptake barriers that, although common among non-Latino groups, had added complexities such as the influence of religion and family on stigma. Low perceived PrEP eligibility, intersectional stigma, lack of insurance, cost concerns, and misconceptions about PrEP side effects were described as general barriers. We also identified Latino-specific barriers that predominantly hinder access to existing services, including a scarcity of PrEP clinics that are prepared to provide culturally concordant services, limited availability of Spanish language information related to PrEP access, distrust of peers as credible sources of information, perceived ineligibility for low-cost services owing to undocumented status, fear of immigration authorities, and competing work obligations that prevent PrEP clinic attendance. Health care providers represented a trusted source of information, and 3 provider characteristics were identified as PrEP facilitators: familiarity with prescribing PrEP; being Latino; and being part of lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA+) group or ally. The proposed app was very well accepted, with a particularly high interest in features that facilitate PrEP access, including a tailored list of clinics that meet the community needs and a private platform to seek PrEP information. Spanish language availability and free or low-cost PrEP care represented the 2 main clinic criteria that would facilitate PrEP uptake. Latino representation in clinic staff and providers; clinic perception as a safe space for undocumented patients; and LGBTQIA+ representation was listed as additional criteria. Only 8 of 47 clinics listed on the Centers for Diseases Control and Prevention PrEP locator website for the Atlanta area fulfilled at least 2 main criteria. CONCLUSIONS: This study provides further evidence of the substantial PrEP uptake barriers that Latino SMM face; exposes the urgent need to increase the number of accessible PrEP-providing clinics for Latino SMM; and proposes an innovative, community-driven, and mobile technology-based tool as a future intervention to overcome some of these barriers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".