Understanding COVID-19 Vaccine Confidence in People Living with HIV: A pan-Canadian Survey
Bibliographic record
Abstract
Understanding the roots of Covid-19 vaccine hesitancy in at-risk groups, such as persons living with HIV (PLWH), is of utmost importance. We developed a modified Vaccine Hesitancy Scale (VHS) questionnaire using items from the National Advisory Committee on Immunization Acceptability Matrix. To examine factors associated with receiving COVID-19 vaccine and the link between vaccine attitudes and beliefs with vaccine behavior, PLWH were recruited via social media and community-based organizations (February-May 2022). Descriptive statistics were used to summarize results. Total VHS score was generated by adding Likert scale scores and linear regression models used to compare results between participants who received or did not receive COVID-19 vaccines. Logistic regression models were used to identify factors associated with vaccine uptake. A total of 246 PLWH indicated whether they received a COVID-19 vaccine. 89% received ≥ 1 dose. Mean total VHS(SD) for persons having received ≥ 1 COVID-19 vaccine was 17.8(6.2) vs. 35.4(9.4) for participants not having received any COVID-19 vaccine. Persons who received ≥ 1 dose were significantly older than those who had not received any (48.4 ± 13.8 vs. 34.0 ± 7.7 years, p < 0.0001). The majority of participants considered COVID-19 vaccination important for their health(81.3%) and the health of others(84.4%). Multivariate logistic regression revealed the odds of taking ≥ 1dose were increased 2.4-fold [95% CI 1.6, 3.5] with each increase in age of 10 years (p < 0.0001). Sex and ethnicity were not different between groups. In conclusion, PLWH accept COVID-19 vaccines for both altruistic and individual reasons. With evolving recommendations and increasing numbers of booster vaccines, we must re-examine the needs of PLWH regularly.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| 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".