Reasons for COVID-19 vaccine refusal among people incarcerated in Canadian federal prisons
Bibliographic record
Abstract
BACKGROUND: Vaccine uptake rates have been historically low in correctional settings. To better understand vaccine hesitancy in these high-risk settings, we explored reasons for COVID-19 vaccine refusal among people in federal prisons. METHODS: Three maximum security all-male federal prisons in British Columbia, Alberta, and Ontario (Canada) were chosen, representing prisons with the highest proportions of COVID-19 vaccine refusal. Using a qualitative descriptive design and purposive sampling, individual semi-structured interviews were conducted with incarcerated people who had previously refused at least one COVID-19 vaccine until data saturation was achieved. An inductive-deductive thematic analysis of audio-recorded interview transcripts was conducted using the Conceptual Model of Vaccine Hesitancy. RESULTS: Between May 19-July 8, 2021, 14 participants were interviewed (median age: 30 years; n = 7 Indigenous, n = 4 visible minority, n = 3 White). Individual-, interpersonal-, and system-level factors were identified. Three were particularly relevant to the correctional setting: 1) Risk perception: participants perceived that they were at lower risk of COVID-19 due to restricted visits and interactions; 2) Health care services in prison: participants reported feeling "punished" and stigmatized due to strict COVID-19 restrictions, and failed to identify personal benefits of vaccination due to the lack of incentives; 3) Universal distrust: participants expressed distrust in prison employees, including health care providers. INTERPRETATION: Reasons for vaccine refusal among people in prison are multifaceted. Educational interventions could seek to address COVID-19 risk misconceptions in prison settings. However, impact may be limited if trust is not fostered and if incentives are not considered in vaccine promotion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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".