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Record W3003372532 · doi:10.2196/14803

Stigma and Web-Based Sex Seeking Among Men Who Have Sex With Men and Transgender Women in Tijuana, Mexico: Cross-Sectional Study

2020· article· en· W3003372532 on OpenAlexvenueno aff
Cristina Espinosa da Silva, Laramie R. Smith, Thomas L. Patterson, Shirley J. Semple, Alicia Vera, Stéphanie Santos Costa Nunes, Gudelia Rangel, Heather A. Pines

Bibliographic record

VenueJMIR Public Health and Surveillance · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious DiseasesNational Institute on Drug Abuse
KeywordsMen who have sex with menSexual orientationStigma (botany)Psychological interventionSexual minorityTransgenderPsychologyRespondentDemographySexual identitySex partnersLogistic regressionCondomClinical psychologyMedicineSocial psychologyHuman sexualityHuman immunodeficiency virus (HIV)SyphilisGender studiesPsychiatryFamily medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Stigma toward sexual and gender minorities is an important structural driver of HIV epidemics among men who have sex with men (MSM) and transgender women (TW) globally. Sex-seeking websites and apps are popular among MSM and TW. Interventions delivered via Web-based sex-seeking platforms may be particularly effective for engaging MSM and TW in HIV prevention and treatment services in settings with widespread stigma toward these vulnerable populations. OBJECTIVE: To assess the potential utility of this approach, the objectives of our study were to determine the prevalence of Web-based sex seeking and examine the effect of factors that shape or are influenced by stigma toward sexual and gender minorities on Web-based sex seeking among MSM and TW in Tijuana, Mexico. METHODS: From 2015 to 2018, 529 MSM and 32 TW were recruited through venue-based and respondent-driven sampling. Interviewer-administered surveys collected information on Web-based sex seeking (past 4 months) and factors that shape or are influenced by stigma toward sexual and gender minorities (among MSM and TW: traditional machismo, internalized stigma related to same-sex sexual behavior or gender identity, and outness related to same-sex sexual behavior or gender identity; among MSM only: sexual orientation and history of discrimination related to same-sex sexual behavior). A total of 5 separate multivariable logistic regression models were used to examine the effect of each stigma measure on Web-based sex seeking. RESULTS: A total of 29.4% (165/561) of our sample reported seeking sex partners on the Web. Web-based sex seeking was negatively associated with greater endorsement of traditional machismo values (adjusted odds ratio [AOR] 0.36, 95% CI 0.19 to 0.69) and greater levels of internalized stigma (AOR 0.96, 95% CI 0.94 to 0.99). Web-based sex seeking was positively associated with identifying as gay (AOR 2.13, 95% CI 1.36 to 3.33), greater outness (AOR 1.17, 95% CI 1.06 to 1.28), and a history of discrimination (AOR 1.83, 95% CI 1.08 to 3.08). CONCLUSIONS: Web-based sex-seeking is relatively common among MSM and TW in Tijuana, suggesting that it may be feasible to leverage Web-based sex-seeking platforms to engage these vulnerable populations in HIV prevention and treatment services. However, HIV interventions delivered through Web-based sex-seeking platforms may have limited reach among those most affected by stigma toward sexual and gender minorities (ie, those who express greater endorsement of traditional machismo values, greater levels of internalized stigma, lesser outness, and nongay identification), given that within our sample they were least likely to seek sex on the Web.

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)0.001
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.351
Teacher spread0.309 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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