We Will Not be Ignored: Assessing PrEP Uptake Inequities Reported by People Living with Disabilities Within a National Sample of Two-Spirit People, Gay, Bisexual and Transgender Men, and Queer and Non-Binary (2S/GBTQ+) people in Canada
Bibliographic record
Abstract
Background: No studies have examined PrEP access among people living with disabilities within Two-Spirit, Gay, Bisexual and Trans men, Queer and Non-Binary communities (2S/GBTQ+) in Canada, despite inequities and structural barriers to health. We investigated PrEP access barriers experienced by 2S/GBTQ+ people living with disabilities with increased likelihood for HIV acquisition, and associations with disability subgroup. Method: Participants self-completed an online, community-based survey, including demographic, disability, and PrEP access barrier questions. Participants were recruited through 2S/GBTQ+-oriented sex-seeking apps, social media, and community-based organizations. Using bootstrapped multivariate logistic regression analyses (1000 iterations), we estimated differences in experiencing PrEP access barriers by disability subgroups presented as adjusted odds ratios (aOR) with 95% confidence intervals (95%CI). Results: Of 1299 PrEP-naïve participants, most identified as cisgender men (88.26%), gay (78.06%) and non-Latino white (77.23%). 803 people (61.82%) reported living with at least one disability. Disabilities were grouped into visual (n=172; 21.42%), hearing (n=40; 4.98%), mobility (n=102; 12.70%), memory (n=284; 35.37%), emotional (n=564; 70.24%) or other disabilities (n=306; 38.11%). While participants living with disability and those not living with disability both reported high rates of any PrEP access barriers (95.39% vs. 95.85%; aOR=0.89; 95%CI [0.37-1.80]), patterns varied by disability subgroup and barrier. Participants with mobility disabilities were more likely to report cost barriers to PrEP (42.42% vs. 28.78%; aOR=2.08; 95%CI [1.12-3.80]) and have concerns about PrEP effectiveness (10.61% vs. 2.73%; aOR=4.08; 95%CI [1.22-9.54]). Participants with memory disabilities were also more likely to report testing requirements as a barrier (23.16% vs. 14.29%; aOR=1.58, 95%CI [1.02-2.42]). Conclusion: PrEP-naïve 2S/GBTQ+ people living with disabilities have unique needs and experiences accessing PrEP that may relate to the nature of their disability/ies. To ensure equitable PrEP implementation, further investigation of PrEP access needs for people with disabilities is warranted to inform policy and health service delivery.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".