A Mobile Application to Collect Daily Data on Preexposure Prophylaxis Adherence and Sexual Behavior Among Men Who Have Sex With Men: Use Over Time and Comparability With Conventional Data Collection
Bibliographic record
Abstract
BACKGROUND: We studied the use of a mobile application (app) to measure human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP) adherence and sexual behavior, assessed determinants of app use, and we compared data in app and questionnaires. METHODS: Men who have sex with men participating in the Amsterdam PrEP project (AMPrEP) on daily or event-driven PrEP at the Public Health Service of Amsterdam completed the data on sexual risk behavior and PrEP adherence through a standard questionnaire every 3 months and on a daily basis using the project's app. Regression analyses were used to assess factors associated with app use. Among those who reported 90% or greater of data in the app, the number of PrEP pills taken and number of unknown casual sex partners were compared between the app and the questionnaires by Wilcoxon signed-rank test. RESULTS: Of all participants (n = 374), 94% (352 of 374) reported data in the app at least once; 72% (261 of 362) reported data ≥90% of the days in the sixth month and 62% (222 of 359) in the 12th month following PrEP initiation.Factors associated with reporting data in the app were using daily PrEP and recent initiation of PrEP. The reported numbers of pills taken and unknown sexual partners were comparable between app and questionnaires. CONCLUSIONS: The AMPrEP app was used frequently, especially by those using a daily PrEP regimen. Data collected by app regarding adherence and sexual risk behavior were consistent with questionnaire data among those who used the app consistently. An app is a promising tool to measure PrEP adherence and sexual risk behavior.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".