Ontarians’ Perceptions of Public Health Communications and Misinformation During the COVID-19 Pandemic: Survey Study
Bibliographic record
Abstract
BACKGROUND: Clear, accurate, and transparent risk communication is critical to providing policy makers and the public with directions to effectively implement public health strategies during a health emergency. OBJECTIVE: We aimed to explore the public's preferred sources of obtaining COVID-19 information, perceptions on the prevalence and drivers of misinformation during the pandemic, and suggestions to optimize health communications during future public health emergencies. METHODS: We administered a web-based survey that included Likert scale, multiple choice and open-ended response questions to residents of Ontario, Canada. We aimed to recruit a sample that reflected population diversity with respect to age and gender. Data were collected between June 10, 2020, and December 31, 2020, and were analyzed using descriptive statistics; open-ended data were analyzed using content analysis. Subgroup analyses to explore perceptions by age and gender were conducted using ordinal regression. RESULTS: A total of 1823 individuals participated in the survey (n=990, 54% women; n=703, 39% men; n=982, 54% aged 18-40 years; n=518, 28% aged 41-60 years; and n=215, 12% aged ≥61 years). Participants most commonly obtained COVID-19 information from local television news (n=1118, 61%) followed by social media (n=938, 51%), national or international television news (n=888, 49%), and friends and family (n=835, 46%). Approximately 55% (n=1010) of the participants believed they had encountered COVID-19-related misinformation; 70% (n=1284) of the participants reported high levels of trust in health authority websites and health care providers; 66% (n=1211) reported high levels of trust in health ministers or public health organizations. Sources perceived to be less trustworthy included friends and family, talk radio, social media, as well as blogs and opinion websites. Men were more likely to report encountering misinformation and to trust friends or family (odds ratio [OR] 1.49, 95% CI 1.24-1.79) and blogs or opinion websites (OR 1.24, 95% CI 1.03-1.50), compared to women. Compared to those aged 18-40 years, participants aged ≥41years were more likely to trust all assessed information sources, with the exception of web-based media sources, and less likely to report encountering misinformation. Of those surveyed, 58% (n=1053) had challenges identifying or appraising COVID-19 information. CONCLUSIONS: Over half of our participants perceived that they had encountered COVID-19 misinformation, and 58% had challenges identifying or appraising COVID-19 information. Gender and age differences in perceptions of misinformation and trust in information sources were observed. Future research to confirm the validity of these perceptions and to explore information-seeking patterns by population subgroups may provide useful insights on how to optimize health communication during public health emergencies.
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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 | 0.025 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".