Bibliographic record
Abstract
Rates of sexually transmitted infections (STI) have increased among gay, bisexual, and men who have sex with other men (GBM) in Canada, particularly gonorrhea and syphilis. If left untreated, these bacterial STI can cause serious sequalae among GBM such infertility and prostatitis as well as increase the risk of HIV transmission. Based on the theory of risk compensation, pre-exposure prophylaxis (PrEP) has been hypothesized as the primary contributing factor to the recent growth in bacterial STI incidence. However, findings are conflicting due to the methodological challenges of assessing how PrEP use facilitate behavioral changes for other prevention strategies such as condom use, subsequently increasing bacterial STI risk. Thus, this dissertation examined whether a) time-varying PrEP uptake affected cumulative bacterial STI incidence, b) condomless anal sex mediated the relation between PrEP uptake and bacterial STI, and c) characteristics of sexual partnerships were associated with elevated bacterial STI incidence among GBM in the era of PrEP. To answer address these research aims, this dissertation used data from the iCruise study, an online longitudinal study of GBM in Ontario, Canada. I used methods in causal inference to construct marginal structural models to evaluate the effect of PrEP uptake on rates of bacterial STI incidence and mediation models to quantify the indirect effect through condomless anal sex. In the final aim, I broaden the scope of possible mechanisms contributing to increased STI risk and adopt a descriptive epidemiology approach to generate hypotheses regarding the potential impact of partnership characteristics on STI incidence. Overall, this dissertation did not find sufficient evidence of risk compensation among iCruise participants. It demonstrates that a different mechanism (or a set of mechanisms) may better explain the observed increases in STI incidence among GBM and those on PrEP.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".