Role of Trusted Sources and Behavioral Beliefs in Promoting Mitigation Behaviors During the COVID-19 Pandemic: Survey Study
Bibliographic record
Abstract
BACKGROUND: During the ongoing COVID-19 pandemic and in preparation for future public health crises, it is important to understand the relationship between individuals' health beliefs, including their trust in various sources of health information, and their engagement in mitigation behaviors. OBJECTIVE: We sought to identify relationships between trust in various sources of health information and the behavioral beliefs related to vaccination and mask wearing as well as to understand how behavioral beliefs related to vaccination differ by willingness to be vaccinated. METHODS: We conducted an online survey of 1034 adults in the United States and assessed their trust in federal, local, and media sources of health information; their beliefs about vaccination; and their masking intention and vaccination willingness. RESULTS: Using regression, masking intention was predicted by trust in the World Health Organization (P<.05) and participants' state public health offices (P<.05), while vaccine willingness was predicted by trust in participants' own health care providers (P<.05) and pharmaceutical companies (P<.001). Compared to individuals with low willingness to be vaccinated, individuals with high willingness indicated greater endorsement of beliefs that vaccines would support a return to normalcy, are safe, and are a social responsibility (P<.001 for all). CONCLUSIONS: Results can be used to inform ongoing public health messaging campaigns to manage the COVID-19 pandemic and increase readiness for the next pandemic. Additionally, results support the need to bolster the public's trust in health care agencies as well as to enhance trust and respect in health care providers to increase people's adoption of mitigation behaviors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".