MyPEEPS Mobile App for HIV Prevention Among Transmasculine Youth: Adaptation Through Community-Based Feedback and Usability Evaluation
Bibliographic record
Abstract
BACKGROUND: Transgender men and transmasculine youth are at high risk for acquiring HIV. Growing research on transgender men demonstrates increased HIV risk and burden compared with the general US population. Despite biomedical advancements in HIV prevention, there remains a dearth of evidence-based, sexual health HIV prevention interventions for young transgender men. MyPEEPS (Male Youth Pursuing Empowerment, Education, and Prevention around Sexuality) Mobile is a web-based app that builds on extensive formative community-informed work to develop an evidence-based HIV prevention intervention. Our study team developed and tested the MyPEEPS Mobile intervention for 13- to 18-year-old cisgender young men in a national randomized controlled trial, which demonstrated efficacy to reduce sexual risk in the short term-at 3-month follow-up. Trans men and transmasculine youth resonated with basic HIV educational information and sexual scenarios of the original MyPEEPS app for cisgender men, but recognized the app's lack of transmasculine specificity. OBJECTIVE: The purpose of this study is to detail the user-centered design methods to adapt, improve the user interface, and enhance the usability of the MyPEEPS Mobile app for young transgender men and transmasculine youth. METHODS: The MyPEEPS Mobile app for young transgender men was adapted through a user-centered design approach, which included an iterative review of the adapted prototype by expert advisors and a youth advisory board. The app was then evaluated through a rigorous usability evaluation. RESULTS: MyPEEPS Mobile is among the first mobile health interventions developed to meet the specific needs of young transgender men and transmasculine youth to reduce HIV risk behaviors. While many of the activities in the original MyPEEPS Mobile were rigorously developed and tested, there was a need to adapt our intervention to meet the specific needs and risk factors among young transgender men and transmasculine youth. The findings from this study describe the adaptation of these activities through feedback from a youth advisory board and expert advisors. Following adaptation of the content, the app underwent a rigorous usability assessment through an evaluation with experts in human-computer interaction (n=5) and targeted end users (n=20). CONCLUSIONS: Usability and adaptation findings demonstrate that the MyPEEPS Mobile app is highly usable and perceived as potentially useful for targeting HIV risk behaviors in young transgender men and transmasculine youth.
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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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".