Preferences for a Mobile HIV Prevention App for Men Who Have Sex With Men
Bibliographic record
Abstract
BACKGROUND: The Centers for Disease Control and Prevention recommends that sexually active men who have sex with men (MSM) in the United States test for human immunodeficiency virus (HIV) at least three times per year, but actual testing frequency is much less frequent. Though mHealth is a popular vehicle for delivering HIV interventions, there are currently no mobile phone apps that target MSM with the specific aim of building an HIV testing plan, and none that focuses on developing a comprehensive prevention plan and link MSM to additional HIV prevention and treatment resources. Previous research has suggested a need for more iterative feedback from the target population to ensure use of these interventions. OBJECTIVE: The purpose of this study is to understand MSM's preferences for functionality, format, and design of a mobile phone-based HIV prevention app and to examine MSM's willingness to use an app for HIV prevention. METHODS: We conducted focus group discussions with 38 gay and bisexual men, with two in-person groups in Atlanta, two in Seattle, and one online focus group discussion with gay and bisexual men in rural US regions. These discussions addressed MSM's general preferences for apps, HIV testing barriers and facilitators for MSM, and ways that an HIV prevention app could address these barriers and facilitators to increase the frequency of HIV testing and prevention among MSM. During focus group discussions, participants were shown screenshots and provided feedback on potential app functions. RESULTS: Participants provided preferences on functionality of the app, including the type and delivery of educational content, the value of interactive engagement, and the importance of social networking as an app component. Participants also discussed preferences on how the language should be framed for the delivery of information, identifying that an app needs to be simultaneously fun and professional. Privacy and altruistic motivation were considered to be important factors in men's willingness to use a mobile HIV prevention app. Finally, men described the potential impact that a mobile HIV prevention app could have, identifying individual, interpersonal, and community-based benefits. CONCLUSIONS: In summary, participants described a comprehensive app that should incorporate innovative ideas to educate and engage men so that they would be motivated to use the app. In order for an app to be useful, it needs to feel safe and trustworthy, which is essential when considering the app's language and privacy. Participants provided a range of preferences for using an HIV prevention app, including what they felt MSM need with regards to HIV prevention and what they want in order to engage with an app. Making an HIV prevention app enjoyable and usable for MSM is a difficult challenge. However, the usability of the app is vital because no matter how great the intervention, if MSM do not use the app, then it will not be useful.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".