The psychology of pandemic policy support: unraveling the complex interplay of personal values and value congruence across 20 European countries
Bibliographic record
Abstract
OBJECTIVES: We explored the roles of personal values and value congruence-the alignment between individual and national values-in predicting public support for pandemic restrictions across 20 European countries. STUDY DESIGN: Cross-sectional study. METHODS: We analyzed multinational European survey data (N = 34,356) using Schwartz's values theory and person-environment fit theory. Multilevel polynomial regression was employed to assess the linear and curvilinear effects of personal values on policy support. Multilevel Euclidean similarity analysis and response surface analysis were conducted to evaluate the impact of value congruence and delineate nuanced congruence patterns. RESULTS: Findings revealed that extreme levels of security, conformity, stimulation, hedonism, and achievement values were associated with decreased policy support. Value congruence with security, conformity, and benevolence increased support, while congruence with stimulation, hedonism, and achievement reduced it. High congruence between personal and national social focus values significantly boosted policy support. Extreme mismatches in self-direction values amplified support. Societal power exceeding personal power also increased support. Matched levels of hedonism motivated greater support, while stimulation and achievement value (in)congruence showed little impact. CONCLUSIONS: We highlight the differential effects of personal values and value congruence on public attitudes toward pandemic restrictions. The findings underscore the importance of considering the interplay between individual and societal values when designing and implementing effective pandemic response strategies.
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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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".