The Annual American Men’s Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2015 Key Indicators Report
Bibliographic record
Abstract
The American Men's Internet Survey (AMIS) is an annual Web-based behavioral survey of men who have sex with men (MSM) living in the United States. This Rapid Surveillance Report describes the third cycle of data collection (September 2015 through April 2016; AMIS-2015). The key indicators are the same as previously reported for AMIS (December 2013-May 2014, AMIS-2013; November 2014-April 2015, AMIS-2014). The AMIS survey methodology has not substantively changed since AMIS-2014. MSM were recruited from a variety of websites using banner advertisements and email blasts. Additionally, participants from AMIS-2014 who agreed to be recontacted for future research were emailed a link to the AMIS-2015 survey. Men were eligible to participate if they were age 15 years and older, resided in the United States, provided a valid US ZIP code, and reported ever having sex with a man. We examined demographic and recruitment characteristics using multivariable regression modeling (P<.05) stratified by participants' self-reported human immunodeficiency virus (HIV) status. The AMIS-2015 round of data collection resulted in 10,217 completed surveys from MSM representing every US state and Puerto Rico. Participants were mainly non-Hispanic white, older than 40 years, living in the US South, living in urban areas, and recruited from general social networking websites. Self-reported HIV prevalence was 9.35% (955/10,217). Compared to HIV-negative/unknown status participants, HIV-positive participants were more likely to have had anal sex without a condom with any male partner in the past 12 months (75.50%, 721/955 vs 63.09%, 5843/9262, P<.001) and more likely to have had anal sex without a condom with a serodiscordant or unknown status partner (34.45%, 329/955 vs 17.07%, 1581/9262, P<.001). The reported use of marijuana and other illicit substances in the past 12 months was higher among HIV-positive participants than HIV-negative/unknown status participants (marijuana use: 24.61%, 235/955 vs 22.96%, 2127/9262; other illicit substance use: 28.59%, 273/955 vs 17.51%, 1622/9262, respectively; both P<.001). Most HIV-negative/unknown status participants (79.11%, 7327/9262) reported ever having a previous HIV test, and 55.69% (5158/9262) reported HIV testing in the past 12 months. HIV-positive participants were more likely to report sexually transmitted infection (STI) testing and diagnosis compared to HIV-negative/unknown status participants (STI testing: 71.73%, 685/955 vs 38.52%, 3568/9262; STI diagnosis: 25.65%, 245/955 vs 8.12%, 752/9262, respectively; both P<.001).
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".