Characterizing Geosocial-Networking App Use Among Young Black Men Who Have Sex With Men: A Multi-City Cross-Sectional Survey in the Southern United States
Bibliographic record
Abstract
BACKGROUND: Understanding where and how young black men who have sex with men (YBMSM) in the southern United States meet their sexual partners is germane to understanding the underlying factors contributing to the ongoing HIV transmission in this community. Men who have sex with men (MSM) commonly use geosocial networking apps to meet sexual partners. However, there is a lack of literature exploring geosocial networking app use in this particular population. OBJECTIVE: Our aim was to examine the characteristics, preferences, and behaviors of a geographically diverse sample of geosocial networking app-using YBMSM in the southern United States. METHODS: Data were collected from a sample of 75 YBMSM across three cities (Gulfport, Mississippi; Jackson, Mississippi; and New Orleans, Louisiana). Multiple aspects of geosocial networking app use were assessed, including overall app use, age of participant at first app use, specific apps used, reasons for app use, photos presented on apps, logon times and duration, number of messages sent and received, and characteristics of and behaviors with partners met on apps. Survey measures of app-met partner and sexual behavior characteristics assessed at midpoint (Day 7) and completion visits (Day 14) were compared using McNemar's test or Wilcoxon signed-rank test. In addition, we assessed activity spaces derived from GPS devices that participants wore for 2 weeks. RESULTS: , P=.011). CONCLUSIONS: Use of geosocial networking apps to meet sexual partners among our sample of YBMSM in the southern United States was common, with a diverse range of app use behaviors being reported. Further research should characterize the association between geosocial networking app use and engagement in sexual behaviors that increase risk for HIV acquisition and transmission. In addition, geosocial networking apps present a promising platform for HIV prevention interventions targeting YBMSM who use these apps.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".