Determinants of SARS-CoV-2 vaccine willingness among people incarcerated in 3 Canadian federal prisons: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Maximizing uptake of SARS-CoV-2 vaccines among people in prison is essential in mitigating future outbreaks. We aimed to determine factors associated with willingness to receive SARS-CoV-2 vaccination before vaccine availability. METHODS: We chose 3 Canadian federal prisons based on their low uptake of influenza vaccines in 2019-2020. Participants completed a self-administered questionnaire on knowledge, attitude and beliefs toward vaccines. The primary outcome was participant willingness to receive a SARS-CoV-2 vaccine, measured using a 5-point Likert scale to the question, "If a safe and effective COVID-19 vaccine becomes available in prison, how likely are you to get vaccinated?" We calculated the association of independent variables (age, ethnicity, chronic health conditions, 2019-2020 influenza vaccine uptake and prison security level), identified a priori, with vaccine willingness using logistic regression and crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: We recruited 240 participants from Mar. 31 to Apr. 19, 2021 (median age 46 years; 19.2% female, 25.8% Indigenous). Of these, 178 (74.2%) were very willing to receive a SARS-CoV-2 vaccine. Participants who received the 2019-2020 influenza vaccine (adjusted OR 5.20, 95% CI 2.43-12.00) had higher odds of vaccine willingness than those who did not; those who self-identified as Indigenous (adjusted OR 0.27, 95% CI 0.11-0.60) and in medium- or maximum-security prisons (adjusted OR 0.36, 95% CI 0.12-0.92) had lower odds of vaccine willingness than those who identified as white or those in minimum-security prisons, respectively. INTERPRETATION: Most participants were very willing to receive vaccination against SARS-CoV-2 before vaccine roll-out. Vaccine promotion campaigns should target groups with low vaccine willingness (i.e., those who have declined influenza vaccine, identify as Indigenous or reside in high-security prisons).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".