Purposefulness and daily life in a pandemic: Predicting daily affect and physical symptoms during the first weeks of the COVID-19 response
Bibliographic record
Abstract
OBJECTIVE: Sense of purpose has been associated with greater health and well-being, even in daily contexts. However, it is unclear whether effects would hold in daily life during COVID-19, when people may have difficulty seeing a path towards their life goals. DESIGN: The current study investigated whether purposefulness predicted daily positive affect, negative affect, and physical symptoms. Participants (n = 831) reported on these variables during the first weeks of the COVID-19 response in North America. MAIN OUTCOME MEASURES: Participants completed daily surveys asking them for daily positive events, stressors, positive affect, negative affect, physical symptoms, and purposefulness. RESULTS: Purposefulness at between- and within-person levels predicted less negative affect and physical symptoms, but more positive affect at the daily level. Between-person purposefulness interacted with positive events when predicting negative and positive affect, suggesting that purposeful people may be less reactive to positive events. However, between-person purposefulness also interacted with daily stressors, insofar that stressors predicted greater declines in positive affect for purposeful people. CONCLUSION: Being a purposeful person holds positive implications for daily health and well-being, even during the pandemic context. However, purposefulness may hold some consequences unique to the COVID-19 context, which merit attention in future research.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".