Seasonal influenza vaccination in older people: A systematic review and meta-analysis of the determining factors
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Despite influenza vaccination programs in various jurisdictions, seasonal influenza vaccine (SIV) uptake remains suboptimal among older people (≥65years old), an important subpopulation for influenza vaccination. We sought to summarize determinants of SIV uptake (any vaccine receipt) and vaccination adherence (receipt of vaccine in two or more seasons in sequence) among older people. METHODS: We searched for population-based studies conducted in community-dwelling older people (irrespective of their health status) from 2000-2019. Two reviewers independently selected publications for inclusion. One reviewer extracted data from the included studies; a second checked the extracted data for errors. Disagreements were resolved by discussion and consensus, or a third reviewer. We were interested in the determinants of SIV uptake and vaccination adherence. Where appropriate, we pooled adjusted results using the inverse variance, random-effects method and reported the odds ratios (OR) and their 95% confidence intervals (CI). RESULTS: Out of 11,570 citations screened, we included 34 cross-sectional studies. The following were associated with increased SIV uptake: being older (OR 1.52, 95%CI 1.38-1.67 [21 studies]), white (1.30, 1.14-1.49 [10 studies]), married (1.23, 1.17-1.28 [9 studies]), non-smoker (1.28, 1.11-1.47 [7 studies]), of a higher social class (1.20, 1.06-1.36 [2 studies]), having a higher education (1.12, 1.04-1.21 [14 studies]), having a higher household income (1.11, 1.05-1.18 [8 studies]), having a chronic illness (1.53, 1.44-1.63 [16 studies]), having poor self-assessed health (1.23, 1.02-1.40 [9 studies]), having a family doctor (2.94, 1.79-4.76 [2 studies]), and having health insurance (1.58, 1.13-2.21 [6 studies]). The influence of these factors varied across geographical regions. Being older (1.26, 1.11-1.44 [2 studies]) was also associated with increased vaccination adherence. CONCLUSIONS: Several factors may determine SIV uptake and vaccination adherence among older people. More studies are needed to provide a stronger evidence base for planning more effective influenza vaccination programs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".