What Demographic, Social, and Contextual Factors Influence the Intention to Use COVID-19 Vaccines: A Scoping Review
Why this work is in the frame
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Bibliographic record
Abstract
Background: During the COVID-19 crisis, an apparent growth in vaccine hesitancy has been noticed due to different factors and reasons. Therefore, this scoping review was performed to determine the prevalence of intention to use COVID-19 vaccines among adults aged 18–60, and to identify the demographic, social, and contextual factors that influence the intention to use COVID-19 vaccines. Methods: This scoping review was conducted by using the methodological framework for scoping review outlined by Arksey and O’Malley. A search strategy was carried out on four electronic databases: PubMed, Scopus, CINAHL, and PsycINFO. All peer-reviewed articles published between November 2019 and December 2020 were reviewed. Data were extracted to identify the prevalence of, and factors that influence, the intention to use COVID-19 vaccines. Results: A total of 48 relevant articles were identified for inclusion in the review. Outcomes presented fell into seven themes: demographics, social factors, vaccination beliefs and attitudes, vaccine-related perceptions, health-related perceptions, perceived barriers, and vaccine recommendations. Age, gender, education level, race/ethnicity, vaccine safety and effectiveness, influenza vaccination history, and self-protection from COVID-19 were the most prominent factors associated with intention to use COVID-19 vaccines. Furthermore, the majority of studies (n = 34/48) reported a relatively high prevalence of intention to get vaccinated against COVID-19, with a range from 60% to 93%. Conclusion: This scoping review enables the creation of demographic, social, and contextual constructs associated with intention to vaccinate among the adult population. These factors are likely to play a major role in any targeted vaccination programs, particularly COVID-19 vaccination. Thus, our review suggests focusing on the development of strategies to promote the intention to get vaccinated against COVID-19 and to overcome vaccine hesitancy and refusal. These strategies could include transparent communication, social media engagement, and the initiation of education programs.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it