850. Reasons for not Using PrEP and Actions that May Facilitate PrEP Uptake in Ontario and British Columbia, Canada
Bibliographic record
Abstract
Abstract Background HIV Pre-exposure prophylaxis (PrEP) is an underutilized intervention to prevent HIV infection in Canada. Known barriers to PrEP uptake include lack of awareness, low HIV risk perception, side effects, PrEP not being publicly funded (which is the case in Ontario) and stigma. We aimed to identify barriers to PrEP use and actions that may facilitate PrEP uptake in Ontario and British Columbia. Methods Gay, bisexual and other men who have sex with men 19 years or older living in Ontario and British Columbia, Canada, answered a survey between July 2019 and August 2020. Participants who met Canadian PrEP guideline criteria for PrEP and not already using PrEP indicated which barriers were relevant to them and which actions would make them more likely to start PrEP. We used descriptive statistics and tested differences between Ontario and British Columbia using Chi-square tests for proportions and t-tests or Wilcoxon rank-sum tests for continuous variables. Results Of 1527 survey responses, 260 (184 in Ontario and 76 in British Columbia) who were never PrEP users and met criteria for PrEP were included. In Ontario, the most common barriers were affordability (43%) and concern about side effects (42%). In British Columbia, the most common reasons were concern about side effects (41%) and not feeling at high enough risk (36%). In Ontario, the actions that would most likely encourage the respondent to start PrEP were short waiting time (63%), the healthcare provider informing about their HIV risk being higher than perceived (62%) and a written step-by-step guide (60%). In British Columbia, the actions that would most likely encourage the respondent to start PrEP were short waiting time (68%), people speaking publicly about PrEP (68%) and their healthcare provider counselling about: their HIV risk being higher than perceived (64%), side effects of PrEP (64%) and about how PrEP works (62%). Table. Top reasons for not using PrEP and top actions that might influence the decision to start PrEP stratified by province. (n= 184 in Ontario, n= 76 in British Columbia). Conclusion Concern about side effects and not feeling at high enough risk were common barriers. Short waiting times may increase PrEP uptake. In Ontario, the findings suggested lack of affordability. In British Columbia, actions involving healthcare providers were valued. Disclosures Kevin Woodward, MD FRCPC, Gilead (Independent Contractor) Darrell Tan, MD PhD, Abbvie (Grant/Research Support)Gilead (Grant/Research Support)GlaxoSmithKline (Scientific Research Study Investigator)ViiV Healthcare (Grant/Research Support)
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".