Too little, too much, and “just right”: Exploring the “goldilocks zone” of daily stress reactivity.
Bibliographic record
Abstract
= 12.12, age range: 35-86; 57% female) completed telephone interviews detailing their stressors and affect on eight consecutive evenings. A series of multilevel structural equation models estimated within-person associations between daily stressors and negative affect (i.e., stress reactivity), and between-person linear and quadratic effects of stress reactivity on mental and physical health outcomes (i.e., life satisfaction, psychological distress, and number of chronic conditions). Findings reveal a significant quadratic effect for each outcome, indicating a U-shaped pattern (inverse U for positively valenced life satisfaction), such that low and high levels of stress reactivity were associated with poorer health and well-being, whereas moderate levels of daily stress reactivity predicted better health outcomes. These findings suggest that individuals who display either very low- or very high-stress reactivity may benefit from interventions that target their emotion regulation skills and coping resources. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".