LONGITUDINAL CHANGES IN DAILY STRESS REACTIVITY AND FUNCTIONAL HEALTH ACROSS 20 YEARS OF ADULTHOOD
Bibliographic record
Abstract
Abstract The daily within-person association between stress exposure and negative affect (i.e., stress reactivity) has been shown to be predictive of a number of adverse health outcomes (e.g., inflammation, chronic conditions). These findings typically rely on a single burst of daily assessments. Little is known about the influence of long-term changes in daily stress reactivity across adulthood and its association with changes in health outcomes. The present study examined whether longitudinal changes in daily within-person associations between stress and affect over 20 years predicted long-term changes in functional health. We used measurement burst data from the National Study of Daily Experiences subsample (N=2,880) embedded within the MIDUS longitudinal study. Three measurement bursts were separated by ten years, with each containing daily measures of stress and affect across eight consecutive days, yielding 33,942 days of data across 20 years of adulthood. Functional health was measured by basic and instrumental activities of daily living (BADL; IADL) at three measurement waves spanning 20 years. Multilevel structural equation models were fit to simultaneously model short-term within-person associations between stress and affect (i.e., stress reactivity) at Level 1; long-term changes in stress reactivity at Level 2; and the association between changes in stress reactivity and changes in functional health at Level 3. Changes in stress reactivity predicted changes in both BADLs and IADLs across 20 years (estimate=0.518, SE=0.153, p=.016; and estimate=0.656, SE=0.200, p<.001, respectively). Individuals who increased more in their stress reactivity across the 20 year period also showed greater increases in their functional health limitations.
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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 | 0.004 |
| 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 | 0.001 | 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".