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Record W3169029287 · doi:10.2196/publichealth.5476

The Annual American Men's Internet Survey of Behaviors of Men Who have Sex with Men in the United States: 2014 Key Indicators Report

2016· article· en· W3169029287 on OpenAlexvenueno aff
Travis Sanchez, María Zlotorzynska, Craig Sineath, Erin Kahle, Patrick S. Sullivan

Bibliographic record

VenueJMIR Public Health and Surveillance · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthCenter for AIDS Research, University of WashingtonEmory University
KeywordsMen who have sex with menDemographyMedicineCondomAnal sexGerontologyYoung adultHuman immunodeficiency virus (HIV)Family medicine

Abstract

fetched live from OpenAlex

The American Men's Internet Survey (AMIS) is an annual Web-based behavioral survey of men who have sex with men (MSM) who live in the United States. The purpose of this Rapid Surveillance Report is to report on the second cycle of data collection (November 2014 through April 2015; AMIS-2014) on the same key indicators previously reported for AMIS (December 2013 through May 2014; AMIS-2013). The AMIS survey methodology has not substantively changed since AMIS-2013. MSM were recruited from a variety of websites using banner advertisements or email blasts. Adult men currently residing in the United States were eligible to participate if they had ever had sex with a man. We examined demographic and recruitment characteristics using multivariable regression modeling (P<.05) stratified by the participants' self-reported human immunodeficiency virus (HIV) status. The AMIS-2014 round of data collection resulted in 9248 completed surveys from MSM representing every US state. Participants were mainly white, 40 years or older, living in the US South, living in urban/suburban areas, and recruited from a general social networking website. Self-reported HIV prevalence was 11.34% (1049/9248). Compared with 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 (76.55% vs 67.17%; P<.001) and more likely to have had anal sex without a condom with their last male sex partner who was discordant/unknown HIV status (39.66% vs 18.77%; P<.001). Marijuana and other illicit substance use in the past 12 months was more likely to be reported by HIV-positive participants than HIV-negative/unknown status participants (26.02% vs 21.27%, and 27.26% vs 17.60%, respectively; both P<.001). The vast majority (86.90%, 7127/8199) of HIV-negative/unknown status participants had been previously HIV tested, and 58.23% (4799/8199) had been tested in the past 12 months. Sexually transmitted infection (STI) testing and diagnosis was also more likely to be reported by HIV-positive participants than HIV-negative/unknown status participants (71.02% vs 37.34%, and 20.59% vs 7.54%, respectively; both P<.001). HIV-negative/unknown status participants <40 years of age were more likely than those 40 years or older to have had anal sex without a condom, were more likely to report substance use, were less likely to have been HIV tested, but were more likely to been tested for and diagnosed with an STI. Compared with those from general social networking, HIV-negative/unknown status participants from a geospatial social networking website were more likely to have reported all risk behaviors but were more likely to have been HIV tested, STI tested, and diagnosed with an STI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.350
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations43
Published2016
Admission routes1
Has abstractyes

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