Canadian results from the European Men-who-have- sex-with-men Internet survey (EMIS-2017)
Bibliographic record
Abstract
Background: In 2017, the international European Men-who-have-sex-with-men Internet Survey (EMIS-2017) collected data from 50 countries, including Canada for the first time. Objective: To provide an overview of the Canadian EMIS-2017 data to describe the sexually transmitted and other bloodborne infection (STBBI) related needs of gay, bisexual and other men who have sex with men (gbMSM). Methods: The EMIS-2017 questionnaire was an updated version of EMIS-2010. It included self-reported sociodemographic data, experience of discrimination, mental health and substance use, knowledge of preexposure prophylaxis (PrEP) for HIV, sexual practices and history of STBBI testing and diagnosis. Analysis was largely descriptive. Results: Of the 6,059 respondents from Canada, 5,165 participants met the inclusion criteria for this analysis. The majority of participants were born in Canada (79.3%); and over half of the respondents (56.7%) were under the age of 39. In terms of discrimination related to their attraction to other men, participants reported high levels of intimidation (31.9%), verbal abuse (22.1%) and physical violence (1.5%) in the previous year. Regarding mental health, 23.9% had a moderate to severe depression/anxiety score. Almost two-thirds (64.1%) indicated substance use and one-fifth (21.5%) reported chemsex (or the use of stimulant drugs to make sex more intense or last longer). Only 8.4% of participants reported use of PrEP for HIV; however, 51.7% reported being likely to use PrEP if it was available and affordable. Sexual practices, such as condom use, varied by PrEP use with 91.3% of men using PrEP reporting condomless anal intercourse (CAI) compared with 71.5% of men not on PrEP. In terms of STBBI testing, 1.5% reported being diagnosed with hepatitis C and 9.0% reported an HIV diagnosis. Of those with an HIV diagnosis, most were on treatment (99.1%) and had an undetectable viral load (96.7%). Conclusion: gbMSM in Canada experienced stigma, discrimination and mental health problems; substance use was high as were high-risk sexual practices, such as CAI, among some groups of men. There was a gap between the proportion of men who were interested in PrEP and those who actually used it; and comprehensive STBBI testing was low.These findings can inform public health action and provide a baseline to examine the impact of current and new interventions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".