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Record W4414667334 · doi:10.1080/09540121.2025.2562238

Awareness, acceptance, and impact of undetectable equals untransmittable (U = U) among people living with HIV across Canada

2025· article· en· W4414667334 on OpenAlexafffundabout
Alex Tran, James R. Watson, Jason M. Lo Hog Tian, Kristin McBain, Arthur Dave Miller, Anthony R. Boni, Lynne Cioppa, Michael Murphy, Deborah Norris, Kim Samson, Danita Wahpoosewyan, Jennifer Demchuk, Catherine Pearl, Gayle Restall, Jared Star, Wangari Tharao, Adrian Betts, Jacqueline Gahagan, Darren Lauscher, Josephine Pui‐Hing Wong, Bruce W. Richman, Randy Davis, Breklyn Bertozzi, Christian Hui, Daniel Grace, Gordon Arbess, Sean B. Rourke

Bibliographic record

VenueAIDS Care · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsPublic Health OntarioToronto Public HealthCanadian Respiratory Research NetworkYukon UniversityToronto Metropolitan UniversityDurham CollegeNine Circles Community Health CentreUniversity of ManitobaYukon Health and Social ServicesMount Royal UniversityMount Saint Vincent UniversityAIDS Committee of TorontoWomen's Health In Women's HandsRegina General HospitalSaskatchewan Ministry of AgricultureUniversity of TorontoDalhousie UniversityRegina Qu'Appelle Health Region
FundersCanadian Institutes of Health ResearchPublic Health AgencyPublic Health Agency of Canada
KeywordsStigma (botany)Snowball samplingHealth careHuman immunodeficiency virus (HIV)IndigenousMultivariate analysisPublic healthQuality of life (healthcare)

Abstract

fetched live from OpenAlex

Undetectable equals Untransmittable (U = U) is a pivotal tool for HIV prevention, stigma reduction, and improving quality of life for people living with HIV. This study examined awareness, acceptance, and impact of U = U among people living with HIV across Canada, and explored differences across sociodemographic characteristics. From 2018-2024, 1,083 participants were recruited in-person and online using snowball sampling. Peer researchers conducted interviews, initially in person and later mostly online due to COVID-19. Demographic data and U = U outcomes were collected and analyzed using multivariate logistic regression. Overall, 72% of participants had heard of U = U, 67% strongly accepted it, and 51% had discussed it with a healthcare provider. Awareness and acceptance were lower among heterosexual and bisexual participants. Cis-women and participants who were unemployed were less likely to report positive impacts from U = U. Black-identifying participants were more likely to report benefits, while Indigenous participants were more likely to believe U = U could reduce stigma and shift public opinion. Older participants were less likely to discuss U = U with a healthcare provider. Findings highlight U = U's potential to reduce stigma, but gaps remain in awareness, acceptance, and provider communication. Tailored strategies are needed to engage diverse communities and support healthcare providers in confidently sharing the zero-risk message.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.276
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.314
Teacher spread0.306 · 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 teacher head, 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

Citations3
Published2025
Admission routes3
Has abstractyes

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