Working Memory Capacity and Thinking Styles Unable to Predict COVID-19 Vaccination
Bibliographic record
Abstract
Failure to comply with vaccination mandates during the coronavirus disease 2019 (COVID-19) pandemic posed a great challenge to the Canadian health care system. Choosing not to vaccinate may reflect concerns about the costs of vaccination while discounting its public health benefits. This study investigated this decision-making is associated with limits of one’s mental capacity, specifically working memory capacity. In addition, the degree to which individuals choose to approach decisions with either experiential (intuitive) or rational (logical) thinking styles were considered. To measure these cognitive functions, participants completed the N-Back as well as the Rational Experiential Inventory-40 questionnaire. The purpose of this study was to investigate if working memory capacity and individuals’ thinking styles can predict attitudes towards COVID-19 vaccination status. However, the results of this study did not find evidence of thinking styles or working memory capacity to be statistically significant predictors of vaccination status. Instead, we found that attitudes surrounding COVID-19 vaccination, such as concerns regarding the safety of the vaccine, to be significant predictors of vaccination. The results of this study propose that executive functioning levels cannot predict vaccination.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".