NONLINEAR ASSOCIATIONS OF DAILY STRESS REACTIVITY WITH HEALTH AND WELL-BEING
Bibliographic record
Abstract
Abstract Research has repeatedly demonstrated that greater affective reactivity to daily stressors is associated with detrimental health outcomes (e.g. inflammation, mortality). However, most research has only considered linear effects, which precludes an examination of whether moderate levels of stress reactivity may be beneficial. Using daily diary data from the National Study of Daily Experiences (N=2,018) we fit multilevel SEMs to simultaneously model daily within-person associations between stress and negative affect (i.e., stress reactivity), and individual differences in the linear and quadratic associations between stress reactivity and life satisfaction, psychological distress, and chronic conditions. Significant quadratic effects were found for each of the three outcomes (estimates=-20.23; 11.49; 20.81, ps<.001, respectively), indicating a U-shaped pattern where both low and high levels of stress reactivity were associated with poorer health, whereas moderate levels of daily stress reactivity predicted better health outcomes. The results suggest that some affective response to daily stressors can be beneficial.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".