Using Best-Worst Scaling to investigate younger adult Canadians’ preferences for COVID-19 vaccination and public health measures: An observational study
Bibliographic record
Abstract
Containing the COVID-19 pandemic is dependent on compliance with public health recommendations and mandates which is lower in younger compared to older adults. Furthermore, younger adults have demonstrated lower uptake of COVID-19 vaccines. The aim of this study was to assess preferences for COVID-19 related preventive health measures and vaccination and to explore their association with COVID-19 vaccine acceptability. Canadians aged 18-39 years were invited to participate in a web-based survey in August 2021. We used the Best-Worst-Scaling (BWS) methodology to collect and analyze preference data and multivariable binary logistic regression to estimate associations with vaccine acceptability. Based on 266 complete responses, we found strong preferences for physical distancing and wearing face masks, as compared to general hygiene and respiratory etiquette. High vaccine accessibility independent of the location, receiving successive doses of the same vaccine brand and higher vaccine uptake of people in younger adults' social circle were highly preferred. Higher preferences for mandates requiring proof of vaccination and altruistic motives focused on protecting others by getting vaccinated were associated with vaccine acceptability. As the COVID-19 pandemic waxes and wanes, studies using larger, nationally representative samples are needed to replicate and validate these results to assess preferences for health behaviors corresponding to the latest recommendations. The use of this methodology could provide public health authorities with a unique opportunity to develop targeted, preference-based messaging that aligns with the latest guidelines to effectively encourage compliance and COVID-19 vaccine uptake.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".