Cognitive predictors of vaccine hesitancy and COVID-19 mitigation behaviors in a population representative sample
Bibliographic record
Abstract
Abstract With the continued threat of COVID-19, predictors of vaccination hesitancy and mitigation behaviors are critical to identify. Prior studies have found that cognitive factors are associated with some COVID-19 mitigation behaviors, but few studies employ representative samples and to our knowledge no prior studies have examined cognitive predictors of vaccine hesitancy. The purpose of the present study, conducted among a large national sample of Canadian adults, was to examine associations between cognitive variables (executive function, delay discounting, and temporal orientation) and COVID-19 mitigation behaviors (vaccination, mask wearing, social distancing, and hand hygiene). Findings revealed that individuals with few executive function deficits, limited delay discounting and who adopted a generally future-orientation mindset were more likely to be double-vaccinated and to report performing COVID-19 mitigation behaviors with high consistency. The most reliable findings were for delay discounting and future orientation, with executive function deficits predicting mask wearing and hand hygiene behaviors but not distancing and vaccination. These findings identify candidate mediators and moderators for health communication messages targeting COVID-19 mitigation behaviors and vaccine hesitancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".