Providing Online-Based Sexual Health Outreach to Gay, Bisexual, and Queer Men in Ontario, Canada: Qualitative Interviews with Multisectoral Frontline Service Providers and Managers
Bibliographic record
Abstract
The Internet is a common tool for gay, bisexual, and other men who have sex with men (MSM) to find sexual partners and sexual health information. Given persistently high human immunodeficiency virus (HIV) infection rates among MSM, it is important to examine the role of online outreach for MSM as part of HIV prevention and care. We provide an overview of the unique perspectives of online sexual health outreach, delivered through AIDS Service Organizations (ASOs) through sociosexual Internet sites and mobile applications. Data were drawn from the qualitative arm of the community-based Cruising Counts study conducted across Ontario from December 2013 to January 2014. ASO online outreach providers and managers (n = 22) were recruited to complete a 1-h in-person/telephone interview to explore in-depth their experiences with, and perspectives on, delivering online outreach services for MSM in Ontario. Thematic analyses were conducted inductively using NVivo 10. Service providers suggested a high demand for online outreach services for MSM. Strengths and advantages of online outreach over face-to-face outreach included anonymity, instant access to services, peer model, and accessing hard-to-reach populations of MSM. Barriers included consistent quality of service, collaborations between companies that own online technologies and outreach service agencies, budgetary and staff capacity issues, and uncertainty of best practices and evaluation parameters for online outreach. Findings from these interviews can inform service providers, policy makers, and researchers on how online sexual health outreach can play a greater role in HIV prevention by better acknowledging and addressing the opportunities and barriers experienced by service providers working with MSM communities online.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".