Sleep duration and affective reactivity to stressors and positive events in daily life.
Bibliographic record
Abstract
OBJECTIVE: Experimental evidence suggests that inadequate sleep disrupts next-day affective processing and evokes greater stress reactivity. However, less research has focused on whether sleep predicts next-day affective reactivity to naturally occurring stressors and positive events in daily life, as well as the reversed direction of association (i.e., affective reactivity to daily events as predictors of subsequent sleep). The purpose of this study was to evaluate the within-person, bidirectional associations between nightly sleep duration and day-to-day fluctuations in affect related to stressors and positive events. METHOD: Adults ages 33-84 (N = 1,982, 57% female) in the U.S. National Study of Daily Experiences II reported sociodemographics and chronic conditions at baseline, then completed telephone interviews for 8 consecutive days about their sleep duration, daily stressors, positive events, and affect. RESULTS: Prior-night sleep duration moderated the link between current-day events and positive affect, but not negative affect. Specifically, nights of shorter-than-usual sleep duration predicted more pronounced decreases in positive affect in response to daily stressors, as well as smaller increases in positive affect in response to daily positive events. Results for the reversed direction of association showed no evidence for affective reactivity to daily events as predictors of subsequent sleep duration. People with more chronic conditions were more reactive to positive events, particularly after nights of longer sleep. CONCLUSION: Affective reactivity to daily stressors and positive events vary based upon sleep duration, such that sleep loss may amplify loss of positive affect on days with stressors, as well as reduce positive affective responsiveness to positive events. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".