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Record W2945841606 · doi:10.1186/s12889-019-6744-y

HIV leadership programming attendance is associated with PrEP and PEP awareness among young, gay, bisexual, and other men who have sex with men in Vancouver, Canada

2019· article· en· W2945841606 on OpenAlexafffundabout
Kalysha Closson, Sarah Chown, Heather L. Armstrong, Lu Wang, Nicanor Bacani, Darren Ho, Jody Jollimore, Gbolahan Olarewaju, David Moore, Eric Abella Roth, Robert S. Hogg, Nathan J. Lachowsky

Bibliographic record

VenueBMC Public Health · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsSimon Fraser UniversityUniversity of VictoriaCommunity Based Research CentreAIDS VancouverPHS Community Services SocietyUniversity of British Columbia
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsMedicineMen who have sex with menAttendanceSexual orientationPre-exposure prophylaxisFamily medicinePublic healthTreatment as preventionReproductive healthBiostatisticsYoung adultGerontologyDemographyHuman immunodeficiency virus (HIV)SyphilisPsychologyPopulationViral loadEnvironmental healthNursingSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Young gay, bisexual, and other men who have sex with men (YGBM) may have reduced engagement and knowledge of HIV care and biomedical HIV prevention strategies, such as pre-exposure prophylaxis (PrEP), post-exposure prophylaxis (PEP), and Treatment as Prevention (TasP), compared with adult GBM. We sought to understand differences in HIV prevention awareness, health care access, and service utilization between youth (16-29 years) and adult (≥30 year) GBM, as well as factors associated with attendance in HIV leadership programming among YGBM living in the publicly funded PrEP setting of Vancouver, Canada. METHODS: Sexually-active GBM were recruited using respondent-driven sampling (RDS) from February 2012 to February 2015. Participants completed an in-person computer-assisted self-interview every 6 months, up to February 2017, with questions on sociodemographic factors, awareness of biomedical HIV prevention strategies, and an HIV treatment optimism-skepticism scale. Participants were asked if they had ever attended either of two HIV-leadership programs designed for YGBM. Both programs involve multiple GBM-led education and social networking sessions operated by community-based organizations in Vancouver. Multivariable Glimmix confounder models assessed differences between youth and adult GBM. Among younger men, bivariate analyses examined factors associated with HIV-leadership program attendance. RESULTS: Of 698 GBM who enrolled in the longitudinal study, 36.8% were less than 30 years old at the first study visit. After controlling for gender identification, sexual orientation, HIV status, and income in the past 6 months, younger GBM (n = 257/698) had lower awareness of biomedical HIV prevention strategies and less HIV treatment optimism compared with older GBM (n = 441/698). Among younger GBM who attended HIV-leadership programs (n = 50), greater awareness of biomedical HIV prevention strategies and higher HIV treatment optimism were reported, compared with non-attendees. CONCLUSION: Younger GBM, who are disproportionately affected by the HIV epidemic, are less aware of new prevention technologies than older GBM, but attending peer-based HIV-leadership programs ameliorates age-disparities in HIV-prevention knowledge and treatment optimism.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.081
GPT teacher head0.346
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2019
Admission routes3
Has abstractyes

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