COVID-19 Booster Vaccination Bellwethers: Factors Predictive of Older Adults’ Adoption of the Second Booster COVID-19 Vaccine in Israel: A Longitudinal Study
Bibliographic record
Abstract
Israel became the first country to offer the second COVID-19 booster vaccination. The study tested for the first time, the predictive role of booster-related sense of control (SOC_B), trust and vaccination hesitancy (VH) on adoption of the second-booster among older adults, 7 months later. Four hundred Israelis (≥60 years-old), eligible for the first booster, responded online, two weeks into the first booster campaign. They completed demographics, self-reports, and first booster vaccination status (early-adopters or not). Second booster vaccination status was collected for 280 eligible responders: early- and late-adopters, vaccinated four and 75 days into the second booster campaign, respectively, versus non-adopters. Multinomial logistic regression was conducted with pseudo R 2 = .385. Higher SOC_B, and first booster early-adoption were predictive of second booster early-vs.-non-adoption, 1.934 [1.148–3.257], 4.861 [1.847–12.791]; and late-vs.-non-adoption, 2.031 [1.294–3.188], 2.092 [0.979–4.472]. Higher trust was only predictive of late-vs.-non-adoption (1.981 [1.03–3.81]), whereas VH was non-predictive. We suggest that older-adult bellwethers, second booster early-adopters, could be predicted by higher SOC_B, and first booster early-adoption, 7 months earlier.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".