HIV Risk Behaviors, Perceptions, and Testing and Preexposure Prophylaxis (PrEP) Awareness/Use in Grindr-Using Men Who Have Sex With Men in Atlanta, Georgia
Bibliographic record
Abstract
Geosocial-networking smartphone applications such as Grindr can help men who have sex with men (MSM) meet sexual partners. Given the high incidence of HIV in the Deep South, the purpose of our study was to assess HIV risk and preexposure prophylaxis (PrEP) awareness and use in a sample of HIV-uninfected, Grindr-using MSM residing in Atlanta, Georgia (n = 84). Most (n = 71; 84.6%) reported being somewhat or very concerned about becoming HIV infected. Most (n = 74; 88.1%) had been tested for HIV in their lifetimes. About three fourths (n = 65; 77.4%) were aware of PrEP, but only 11.9% currently used the medication. HIV continues to disproportionately impact MSM and represents a significant source of concern. As the number of new infections continues to rise, it is important to decrease risks associated with acquisition and transmission of HIV by increasing rates of HIV testing and the use of biobehavioral interventions such as PrEP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".