Adherence to Recommended Preventive Behaviors During the COVID-19 Pandemic: The Role of Empathy and Perceived Health Threat
Bibliographic record
Abstract
BACKGROUND: Coping via empathic responding may play a role in preventive behavior engagement during the COVID-19 pandemic, and unlike trait empathy, is a potentially alterable target for changing health behavior. PURPOSE: Our goal was to examine the role of empathic responding in preventive behavior engagement during the COVID-19 pandemic, independent of trait empathy and perceived threat of COVID-19. METHODS: Participants (N = 2,841) completed a baseline survey early in the pandemic, and a follow-up survey approximately 2 weeks later (M = 13.50 days, SD = 5.61). Preventive health behaviors, including physical distancing and hygiene practices, were assessed at both timepoints. Hierarchical linear regression examined the contributions of trait empathy, perceived threat of COVID-19, and empathic responding at baseline to preventive behaviors at follow-up. RESULTS: Controlling for baseline levels of preventive behaviors and demographic covariates, trait empathy and threat of COVID-19 at baseline were each independently associated with preventive behaviors at follow-up. An interaction between perceived threat and empathic responding indicated that those perceiving high threat of COVID-19 at baseline tended to report engaging in preventive behaviors at follow-up regardless of their levels of empathic responding, whereas for those reporting low levels of perceived threat, higher levels of empathic responding were associated with higher engagement in preventive behavior. CONCLUSIONS: When perceived threat of COVID-19 was low, higher empathic responding was associated with increased engagement in preventive behaviors regardless of trait empathy, suggesting that empathic responding can serve as an actionable target for intervention to promote preventive behavior during the pandemic.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".