Formative Work to Develop a Tailored HIV Testing Smartphone App for Diverse, At-Risk, HIV-Negative Men Who Have Sex With Men: A Focus Group Study
Bibliographic record
Abstract
BACKGROUND: Although gay, bisexual, and other men who have sex with men (MSM) are disproportionately affected by human immunodeficiency virus (HIV) infection, few test for HIV at regular intervals. Smartphone apps may be an ideal tool to increase regular testing among MSM. However, the success of apps to encourage regular testing among MSM will depend on how frequently the apps are downloaded, whether they continue to be used over months or years, and the degree to which such apps are tailored to the needs of this population. OBJECTIVE: The primary objectives of this study were to answer the following questions. (1) What features and functions of smartphone apps do MSM believe are associated with downloading apps to their mobile phones? (2) What features and functions of smartphone apps are most likely to influence MSM's sustained use of apps over time? (3) What features and functions do MSM prefer in an HIV testing smartphone app? METHODS: We conducted focus groups (n=7, with a total of 34 participants) with a racially and ethnically diverse group of sexually active HIV-negative MSM (mean age 32 years; 11/34 men, 33%, tested for HIV ≥10 months ago) in the United States in Miami, Florida and Minneapolis, Minnesota. Focus groups were digitally recorded, transcribed verbatim, and deidentified for analysis. We used a constant comparison method (ie, grounded theory coding) to examine and reexamine the themes that emerged from the focus groups. RESULTS: Men reported cost, security, and efficiency as their primary reasons influencing whether they download an app. Usefulness and perceived necessity, as well as peer and posted reviews, affected whether they downloaded and used the app over time. Factors that influenced whether they keep and continue to use an app over time included reliability, ease of use, and frequency of updates. Poor performance and functionality and lack of use were the primary reasons why men would delete an app from their phone. Participants also shared their preferences for an app to encourage regular HIV testing by providing feedback on test reminders, tailored testing interval recommendations, HIV test locator, and monitoring of personal sexual behaviors. CONCLUSIONS: Mobile apps for HIV prevention have proliferated, despite relatively little formative research to understand best practices for their development and implementation. The findings of this study suggest key design characteristics that should be used to guide development of an HIV testing app to promote regular HIV testing for MSM. The features and functions identified in this and prior research, as well as existing theories of behavior change, should be used to guide mobile app development in this critical area.
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 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 | 0.035 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".