Bibliographic record
Abstract
We read with great interest the article published by Zhu et al.[1]. The authors have addressed an important question regarding sexual behaviour in the context of advances in HIV treatment. In their article, the authors report that prior to the availability of HAART, the odds of subsequent engagement in sex with at least two partners, among MSM, decreased after seroconversion. Seroconversion after the widespread availability of HAART was associated with further reduced odds in engaging in these sexual behaviours. These findings challenge the current discussions regarding the association between HIV treatment advances and sexual behaviour. The study drew on data from 4616 MSM collected between 1984 and 2008, comparing men who seroconverted prior to the availability of HAART and after. Given the design of their study, it is still unclear whether the findings are associated with availability of antiretroviral therapy or the temporal trends in sexual behaviour in the United States over this time period [2]. In 2012, the Food and Drug Administration (FDA) approved emtricitabine/tenofovir for reducing the risk of HIV transmission through sexual activity. Since then, discussions have emerged regarding whether widespread use of emtricitabine/tenofovir as preexposure prophylaxis (PrEP) contributes to riskier sexual behaviour among populations already at a high risk of acquiring HIV, a concept termed ‘risk compensation’ [3]. On the basis of this concept, people taking PrEP or HIV treatment would perceive a reduced risk of acquiring or transmitting HIV and thus will engage in riskier sexual behaviour; however, the authors have shown that for HIV treatment, this reasoning is not applicable in the cohort studied. Qualitative research exploring the complexities of risk-taking has begun to describe the diverse ways in which PrEP influences sexual-wellbeing from the perspective of MSM [4]. From the limited research that exists, the perceived impacts of PrEP on sexual behaviour vary and may in fact fluctuate over the course of one's life. Hence, it would be valuable to re-examine the cohort described by Zhu et al.[1] for changes in sexual behaviour in the current context of treatment as prevention [5] and PrEP availability. Although limitations of the study constrain the conclusions that can be drawn to MSM, if the authors have access to data from the cohort after 2012, it would be worthwhile to examine and comment on whether sexual behaviours among this cohort have changed since the availability of PrEP. Furthering our understanding of how treatment as prevention and PrEP alter sexual behaviour could aid in directing HIV policy and future research. Acknowledgements Conflicts of interest There are no conflicts of interest.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.747 | 0.489 |
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".