The Annual American Men's Internet Survey of Behaviors of Men Who Have Sex With Men in the United States: 2016 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 fourth cycle of data collection (September 2016 through February 2017; AMIS 2016). The key indicators are the same as previously reported for AMIS (December 2013 through May 2014, AMIS 2013; November 2014 through April 2015, AMIS 2014; and September 2015 through April 2016, AMIS 2015). The AMIS survey methodology has not substantively changed since AMIS 2015. MSM were recruited from a variety of websites using banner advertisements and email blasts. Additionally, participants from AMIS 2015 who agreed to be recontacted for future research were emailed a link to the AMIS 2016 survey. Men were eligible to participate if they were ≥15 years old, resided in the United States, provided a valid US zone improvement plan code, and reported ever having sex with a man or identified as gay or bisexual. We examined demographic and recruitment characteristics using multivariable regression modeling (P<.05) stratified by participants' self-reported HIV status. The AMIS 2016 round of data collection resulted in 10,166 completed surveys from MSM representing every US state, Puerto Rico, Guam, and the US Virgin Islands. Participants were mainly non-Hispanic white, over the age of 40 years, living in the Southern United States and urban areas, and recruited from general social networking websites. Self-reported HIV prevalence was 10.80% (1098/10,166). Compared to HIV-negative/unknown-status participants, HIV-positive participants were more likely to have had anal sex without a condom with a male partner in the past 12 months (75.77% vs 65.88%, P<.001) and more likely to have had anal sex without a condom with a serodiscordant or unknown-status partner (33.24% vs 16.06%, P<.001). The reported use of marijuana, methamphetamines, and other illicit substances in the past 12 months was higher among HIV-positive participants than among HIV-negative/unknown-status participants (28.05% vs 24.99%, 11.48% vs 2.16%, and 27.60% vs 18.22%, respectively; all P<.001). Most HIV-negative/unknown-status participants (79.93%, 7248/9068) reported ever having a previous HIV test, and 56.45% (5119/9068) reported undergoing HIV testing in the past 12 months. HIV-positive participants were more likely to report testing and diagnosis of sexually transmitted infections than HIV-negative/unknown-status participants (70.86% vs 40.13% and 24.04% vs 8.97%, respectively; both P<.001).
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".