Determinants of Vaccine Hesitancy among Home Health Care Service Recipients in Saudi Arabia
Bibliographic record
Abstract
Background: Vaccine hesitancy has been identified by the World Health Organization (WHO) as a major worldwide health threat. Home Health Care (HHC) service recipients represent a vulnerable group and were prioritized to receive coronavirus disease (COVID-19) vaccination during the national vaccine campaigns in Saudi Arabia. We aimed to investigate the most frequent reasons for vaccine hesitancy among home health care recipients in Saudi Arabia. Methods: This cross-sectional survey was conducted among home health care (HHC) service recipients in Saudi Arabia from February 2022 to September 2022. The behavioral and social drivers (BeSD) model developed by the WHO was used to understand the factors affecting vaccination decision making in our cohort. Results: Of the 426 HHC service recipients enrolled in the study, a third were hesitant to complete the COVID-19 vaccination series. The most prevalent reported reason for COVID-19 vaccine refusal was concerns about the vaccine side effects (41.6%). Factors independently associated with COVID-19 vaccination hesitancy were: having chronic conditions (odds ratio [OR] = 2.59; 95% confidence interval [CI] = 1.33–5.05, p = 0.005), previous COVID-19 diagnosis (OR = 0.48; 95% CI: 0.28–0.82, p = 0.008), ease of getting the COVID-19 vaccine by themselves (OR = 0.49; 95% CI: 0.28–0.89, p = 0.018), belief in the importance of COVID-19 vaccine in protecting their health (OR = 0.60; 95% CI: 0.38–0.96, p = 0.032), and confidence in the safety of COVID-19 vaccination (OR = 0.38; 95% CI: 0.21–0.69, p = 0.001). Conclusion: Only one-third of the study participants were hesitant to complete the series of COVID-19 vaccination. Understanding the factors underpinning vaccine hesitancy among this group would help healthcare workers and policymakers in developing personalized health awareness campaigns aimed at improving vaccine acceptance levels.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".