Intention to receive a COVID-19 vaccine by HIV status among a population-based sample of women and gender diverse individuals in British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT Introduction COVID-19 vaccination is recommended for people living with HIV (PLWH), among whom social inequities and co-morbidities may drive risks of COVID-19 infection and outcome severity. Among a provincial (British Columbia) sample, we determined the prevalence of COVID-19 vaccine intention by HIV status and assessed socio-demographic, vaccine hesitancy, and psychological predictors of vaccine intention. Methods Individuals (25-69y) recruited from province-wide research cohorts completed an online survey examining COVID-19 impacts (August/2020-March/2021). Among women and gender diverse participants, we compared intention to receive a recommended COVID-19 vaccine (Very likely/Likely vs Neutral/Unlikely/Very Unlikely) by self-reported HIV status. Logistic regression models assessed the independent effect of HIV status and other factors on vaccine intention. Results Of 5,588 participants, 69 (1.2%) were PLWH, of whom 79.7% were on antiretroviral therapy. Intention to vaccinate was significantly lower among PLWH compared to participants not living with HIV (65.2% vs 79.6%; OR: 0.44; 95%CI: 0.32-0.60). However, this association was attenuated after adjustment for social disparities (aOR:0.85; 95%CI: 0.48-1.55). Among PLWH, those with greater vaccine confidence, positive attitudes towards the COVID-19 vaccine, and more strongly influenced by direct and indirect social norms to vaccinate had significantly higher odds of vaccine intention. Discussion Tailored messaging is needed to build vaccine confidence, address questions about vaccine benefits, and support informed vaccination decision-making to promote COVID-19 vaccine uptake among women and gender diverse PLWH.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 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".