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Record W3171065708 · doi:10.1186/s12889-021-11091-2

Sexual health norms and communication patterns within the close social networks of men who have sex with men and transgender women in Lima, Peru: a 2017 cross-sectional study

2021· article· en· W3171065708 on OpenAlexaff
Amrita Ayer, Eddy R. Segura, Amaya Perez‐Brumer, Susan Chávez-Gomez, Rosario Fernández, Jessica Gutierrez, Karla Rojas Suárez, Jordan E. Lake, Jesse L. Clark, Robinson Cabello

Bibliographic record

VenueBMC Public Health · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersNational Institute of Mental HealthNational Institutes of Health
KeywordsMedicineBiostatisticsCross-sectional studyPublic healthTransgenderTransgender PersonReproductive healthDemographyTransgender peopleTransgender womenSexual behaviorEpidemiologyMen who have sex with menGender studiesClinical psychologyEnvironmental healthSyphilisPopulationFamily medicineHuman immunodeficiency virus (HIV)Sociology

Abstract

fetched live from OpenAlex

BACKGROUND: Social networks, norms, and discussions about sexual health may inform sexual practices, influencing risk of human immunodeficiency virus (HIV) or sexually transmitted infection (STI) acquisition. To better understand social networks of Peruvian men who have sex with men (MSM) and transgender women (trans women), we examined key social network members (SNMs), participant perceptions of these network members' opinions toward sexual health behaviors, and associations between network member characteristics and condomless anal intercourse (CAI). METHODS: In a 2017 cross-sectional study, a convenience sample of 565 MSM and trans women with HIV-negative or unknown serostatus was asked to identify three close SNMs; describe discussions about HIV and STI prevention with each; and report perceived opinions of condom use, HIV/STI testing, and partner notification of STIs. Generalized estimating equations evaluated relationships between SNM characteristics, opinions, and discussions and participant-reported CAI. RESULTS: Among participants who identified as MSM, 42.3% of key SNMs were perceived to identify as gay. MSM "never" discussed HIV and STI prevention concerns with 42.4% of heterosexual SNMs, but discussed them "at least once weekly" with 16.9 and 16.6% of gay- and bisexual- identifying SNMs, respectively. Among participants who identified as trans women, 28.2% of key SNMs were perceived as heterosexual; 25.9%, as bisexual; 24.7%, as transgender; and 21.2%, as gay. Trans women discussed HIV/STI prevention least with cis-gender heterosexual network members (40.2% "never") and most with transgender network members (27.1% "at least once weekly"). Participants perceived most of their close social network to be completely in favor of condom use (71.2% MSM SNMs, 61.5% trans women SNMs) and HIV/STI testing (73.1% MSM SNMs, 75.6% trans women SNMs), but described less support for partner STI notification (33.4% MSM SNMs, 37.4% trans women SNMs). Most participants reported CAI with at least one of their past three sexual partners (77.5% MSM, 62.8% trans women). SNM characteristics were not significantly associated with participant-reported frequency of CAI. CONCLUSIONS: Findings compare social support, perceived social norms, and discussion patterns of Peruvian MSM and trans women, offering insight into social contexts and sexual behaviors. TRIAL REGISTRATION: The parent study from which this analysis was derived was registered at ClinicalTrials.gov (Identifier: NCT03010020 ) on January 4, 2017.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.403
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2021
Admission routes1
Has abstractyes

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