The Resilience of Attitude Toward Vaccination: Web-Based Randomized Controlled Trial on the Processing of Misinformation
Bibliographic record
Abstract
Background Before the COVID-19 pandemic, it was already recognized that internet-based misinformation and disinformation could influence individuals to refuse or delay vaccination for themselves, their families, or their children. Reinformation, which refers to hyperpartisan and ideologically biased content, can propagate polarizing messages on vaccines, thereby contributing to vaccine hesitancy even if it is not outright disinformation. Objective This study aimed to evaluate the impact of reinformation on vaccine hesitancy. Specifically, the goal was to investigate how misinformation presented in the style and layout of a news article could influence the perceived tentativeness (credibility) of COVID-19 vaccine information and confidence in COVID-19 vaccination. Methods We conducted a web-based randomized controlled trial by recruiting English-speaking Canadians aged 18 years and older from across Canada through the Qualtrics (Silver Lake) paid opt-in panel system. Participants were randomly assigned to 1 of 4 distinct versions of a news article on COVID-19 vaccines, each featuring variations in writing style and presentation layout. After reading the news article, participants self-assessed the tentativeness of the information provided, their confidence in COVID-19 vaccines, and their attitude toward vaccination in general. Results The survey included 537 participants, with 12 excluded for not meeting the task completion time. The final sample comprised 525 participants distributed about equally across the 4 news article versions. Chi-square analyses revealed a statistically significant association between general attitude toward vaccination and the perceived tentativeness of the information about COVID-19 vaccines included in the news article (χ21=37.8, P<.001). The effect size was small to moderate, with Cramer V=0.27. An interaction was found between vaccine attitude and writing style (χ21=6.2, P=.01), with a small effect size, Cramer V=0.11. In addition, a Pearson correlation revealed a significant moderate to strong correlation between perceived tentativeness and confidence in COVID-19 vaccination, r(523)=0.48, P<.001. The coefficient of determination (r2) was 0.23, indicating that 23% of the variance in perceived tentativeness was explained by confidence in COVID-19 vaccines. In comparing participants exposed to a journalistic-style news article with those exposed to an ideologically biased article, Cohen d was calculated to be 0.38, indicating a small to medium effect size for the difference in the perceived tentativeness between these groups. Conclusions Exposure to a news article conveying misinformation may not be sufficient to change an individual’s level of vaccine hesitancy. The study reveals that the predominant factor in shaping individuals’ perceptions of COVID-19 vaccines is their attitude toward vaccination in general. This attitude also moderates the influence of writing style on perceived tentativeness; the stronger one’s opposition to vaccines, the less pronounced the impact of writing style on perceived tentativeness. International Registered Report Identifier (IRRID) RR2-10.2196/41012
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".