Changing patterns of sexual behaviour in the era of highly active antiretroviral therapy
Bibliographic record
Abstract
PURPOSE OF REVIEW: To describe changing patterns of sexual behaviour in the era of highly active antiretroviral therapy among gay/bisexual men in Europe, Canada, USA and Australia. RECENT FINDINGS: While there has been a substantial increase in high-risk sexual behaviour among gay men since 1996, this now appears to be levelling off in some cities. Overall the empirical evidence does not support the suggestion that taking highly active antiretroviral therapy or having an undetectable viral load leads to risky sexual behaviour among people with HIV. Nor can HIV treatment optimism alone explain the recent increase in high-risk sexual behaviour. Since 1996, an increasing number of gay men have begun to use the Internet to look for sexual partners. By serosorting on the Internet, HIV-positive men are more likely to meet online, rather than off-line, other HIV-positive men for unprotected sex. While serosorting does not present a risk of HIV transmission to an uninfected person, it does present a risk of other sexually transmitted infections and co-infection with resistant virus for HIV-positive men themselves. This review also explores emerging behaviours such as barebacking and strategic positioning as well as the role of crystal meth and Viagra. SUMMARY: The review reminds us of the complexity of human and sexual behaviour. Among gay men, sexual behaviour in the era of highly active antiretroviral therapy has been characterized by risk reduction and stabilization as well as increasing risk. These changing patterns provide a new challenge as well as new opportunities for HIV prevention.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".