Turning toward or away from God: COVID-19 and changes in religious devotion
Bibliographic record
Abstract
Major stressors can influence religiosity, making some people more religious, while making others less religious. In response to the COVID-19 pandemic, we conducted a mixed-method study with a nationally representative sample of religiously affiliated American adults (N = 685) to assess group differences between those who decreased, stayed the same, or increased in their religious devotion. In quantitative analyses we evaluated differences on sociodemographic variables, religious behaviors, individual differences, prosocial emotions, well-being, and COVID-19 attitudes and behaviors. Of most note, those who changed (i.e., increased or decreased) in religious devotion were more likely than those with no change in devotion to experience high levels of stress and threat related to COVID-19, but only those who increased in religious devotion had the highest dispositional prosocial emotions (i.e., gratitude and awe). Further, those who changed in religious devotion were more likely to report searching for meaning than those with no change, but only those who increased were more likely to report actual presence of meaning. Qualitative analyses revealed that those who increased in religious devotion reported increasing personal worship, the need for a higher power, and uncertainty in life as reasons for their increase in religious devotion; those who decreased reported being unable to communally worship, a lack of commitment or priority, and challenges making it hard to believe in God as reasons for their decrease in religious devotion. The findings help identify how COVID-19 has affected religious devotion, and how religion might be used as a coping mechanism during a major life stressor.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".