The Cycle of Daily Stress and Sleep: Sleep Measurement Matters
Bibliographic record
Abstract
BACKGROUND: Disturbed sleep can be a cause and a consequence of elevated stress. Yet intensive longitudinal studies have revealed that sleep assessed via diaries and actigraphy is inconsistently associated with daily stress. PURPOSE: We expanded this research by examining daily associations between sleep and stress using a threefold approach to assess sleep: sleep diaries, actigraphy, and ambulatory single-channel electroencephalography (EEG). METHODS: Participants were 80 adults (mean age = 32.65 years, 63% female) who completed 7 days of stressor and sleep assessments. Multilevel models were used to examine bidirectional associations between occurrence and severity of daily stress with diary-, actigraphy-, and EEG-determined sleep parameters (e.g., total sleep time [TST], sleep efficiency, and sleep onset latency, and wake after sleep onset [WASO]). RESULTS: Participants reported at least one stressor 37% of days. Days with a stressor were associated with a 14.4-min reduction in actigraphy-determined TST (β = -0.24, p = 0.030), but not with other actigraphy, diary, or EEG sleep measures. Nights with greater sleep diary-determined WASO were associated with greater next-day stressor severity (β = 0.01, p = 0.026); no other diary, actigraphy, or EEG sleep measures were associated with next-day stressor occurrence or severity. CONCLUSIONS: Daily stress and sleep disturbances occurred in a bidirectional fashion, though specific results varied by sleep measurement technique and sleep parameter. Together, our results highlight that the type of sleep measurement matters for examining associations with daily stress. We urge future researchers to treat sleep diaries, actigraphy, and EEG as complementary-not redundant-sleep measurement approaches.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".