Preferences for COVID-19 Vaccines: Systematic Literature Review of Discrete Choice Experiments
Bibliographic record
Abstract
BACKGROUND: Vaccination can be viewed as comprising the most important defensive barriers to protect susceptible groups from infection. However, vaccine hesitancy for COVID-19 is widespread worldwide. OBJECTIVE: We aimed to systematically review studies eliciting the COVID-19 vaccine preference using discrete choice experiments. METHODS: A literature search was conducted in PubMed, Embase, Web of Science, Scopus, and CINAHL Plus platforms in April 2023. Search terms included discrete choice experiments, COVID-19, and vaccines and related synonyms. Descriptive statistics were used to summarize the study characteristics. Subgroup analyses were performed by factors such as high-income countries and low- and middle-income countries and study period (before, during, and after the pandemic wave). Quality appraisal was performed using the 5-item Purpose, Respondents, Explanation, Findings, and Significance checklist. RESULTS: The search yield a total of 623 records, and 47 studies with 53 data points were finally included. Attributes were grouped into 4 categories: outcome, process, cost, and others. The vaccine effectiveness (21/53, 40%) and safety (7/53, 13%) were the most frequently reported and important attributes. Subgroup analyses showed that vaccine effectiveness was the most important attribute, although the preference varied by subgroups. Compared to high-income countries (3/29, 10%), a higher proportion of low- and middle-income countries (4/24, 17%) prioritized safety. As the pandemic progressed, the duration of protection (2/24, 8%) during the pandemic wave and COVID-19 mortality risk (5/25, 20%) after the pandemic wave emerged as 2 of the most important attributes. CONCLUSIONS: Our review revealed the critical role of vaccine effectiveness and safety in COVID-19 vaccine preference. However, it should be noticed that preference heterogeneity was observed across subpopulations and may change over time. TRIAL REGISTRATION: PROSPERO CRD42023422720; https://tinyurl.com/2etf7ny7.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".