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Record W4406428560 · doi:10.2196/66139

Awareness of Sexual Partner’s HIV Status Among Men Who Have Sex With Men in China: Cross-Sec. tional Survey Study

2025· article· en· W4406428560 on OpenAlexvenueno aff
Tingting Jiang, Wanjun Chen, Shaoqiang Jiang, Jinlei Zheng, Hui Wang, Lin He

Bibliographic record

VenueJMIR Public Health and Surveillance · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)ChinaPsychologyMen who have sex with menSexual behaviorDemographyHomosexualityEnvironmental healthMedicineSocial psychologyFamily medicineGeographySyphilisSociology

Abstract

fetched live from OpenAlex

Background: Men who have sex with men (MSM) constitute a significant proportion of individuals living with human immunodeficiency virus. Over the past few years, China has implemented various strategies aimed at increasing the rate of HIV testing and reducing HIV transmission among MSM. Among these, the disclosure of HIV serostatus is an effective prevention strategy. Objective: This study aimed to assess HIV serostatus disclosure and identify factors associated with awareness of sexual partners' HIV status among MSM to provide a scientific basis for promoting HIV testing and reducing HIV transmission. Methods: A cross-sectional study based on a large-scale web-based survey was conducted among MSM in Zhejiang province, China, between July and December 2023. MSM who were HIV-negative or had an unknown HIV status were recruited from the Sunshine Test, a web-based platform that uses location-based services to provide HIV prevention services. Participants were required to complete a questionnaire on demographic characteristics, sexual behavior, rush popper use, awareness of sexual partners' HIV status, and knowledge of pre-exposure prophylaxis (PrEP) and postexposure prophylaxis (PEP). A multinomial regression model was used to identify the factors associated with awareness of sexual partners' HIV status. Results: A total of 7629 MSM participated in the study, with 45.2% (n=3451) being aware, 35.4% (n=2701) being partially aware, and 19.4% (n=1477) being unaware of their sexual partner's HIV status. The multinomial logistic regression analysis revealed the following results. Compared to those who were unaware of their sexual partner's HIV status, participants who were students (adjusted odds ratio [aOR] 1.43, 95% CI 1.09-1.86), had a monthly income of more than US $1400 (aOR 1.36, 95% CI 1.03-1.80), had insertive anal sex (aOR 1.35, 95% CI 1.12-1.63), had only male sexual partners (aOR 1.53, 95% CI 1.28-1.82), had 1 sexual partner in the past 3 months (aOR 2.36, 95% CI 2.01-2.77), had used condoms for the past 3 months (aOR 1.72, 95% CI 1.33-2.22), had frequently used rush poppers in the past 3 months (aOR 2.27, 95% CI 1.81-2.86), were aware of HIV PrEP (aOR 2.04, 95% CI 1.68-2.48), were aware of HIV PEP (aOR 1.69, 95% CI 1.39-2.06), used mail reagent self-testing (aOR 1.19, 95% CI 1.04-1.36), and had previously undergone HIV testing (aOR 1.40, 95% CI 1.16-1.69) were associated with increased odds of being aware of their sexual partner's HIV status. Conclusions: Overall, 45.2% of MSM who were HIV-negative or had an unknown status were aware of their sexual partners' HIV status in China. We suggest strengthening targeted interventions through web-based platforms and gay apps to promote the disclosure of HIV serostatus and reduce HIV transmission among MSM.

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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.403
Teacher spread0.363 · 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
Published2025
Admission routes1
Has abstractyes

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