Characteristics and Influencing Factors of HIV Related Behaviors in Men Who Have Sex with Men
Bibliographic record
Abstract
[Objective] To find out characteristics of human immunodeficiency virus(HIV) infection related behaviours among men who have sex with men(MSM) in Shanghai and related influencing factors.[Methods]A total of 121 MSM were recruited through internet and interviewed face to face using questionnaires designed by Sino-Canada Global Research.[Results]The interviewees were at the average age of(27.99±5.933) years;74.4% of them received college or above education;62.9% earned more than 3000 yuan per month;86.0% were single.The average age at first sex with men was(22.14±5.32) years;the average number of sexual partners within the past six months was 3.27±2.77.The interviewees who had long-term relations accounted for 56.14%,but only 36.84% were loyal to the relations;16 interviewees had sexual behaviours with female partners within the past six months,among which 62.8% were unprotected;45.45% interviewees had unprotected sexual behaviours with male partners,and their percentage of unprotected sexual behaviours in long-term relations was significantly higher than that with irregular sexual partners(χ2=4.32,P0.05) and occasional sexual partner(χ2=10.13,P0.01);77.7% intervieweesbelieved they wereattherisk of HIV infection.The factors influencing unprotected sexualbehaviours were education level,number of sexual partners within the past six months and self-evaluation of HIV infection[.Conclusion]The MSM who have less education and more sexual partners are more likely to have unprotected sexual behaviours,and those with self-evaluation of HIV infection tend to have a history of unprotected sexualbehaviours.Enhanced health interventionsare therefore imperative to bedelivered to these MSM.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".