<p>Experienced Demand Does Not Affect Subsequent Sleep and the Cortisol Awakening Response</p>
Bibliographic record
Abstract
Purpose: Stress is associated with subjective and objective sleep disturbances; however, it is not known whether stress disrupts sleep and relevant physiological markers of stress immediately after it is experienced. The present study examined whether demand, in the form of cognitive tasks, disrupted sleep and the cortisol awakening response (CAR), depending on whether it was experienced or just anticipated. Participants and Methods: Subjective and objective sleep was measured in 22 healthy adults on three nights (Nights 0– 2) in a sleep laboratory using sleep diaries and polysomnography. Saliva samples were obtained at awakening, +15, +30, +45 and +60 minutes on each subsequent day (Day 1– 3) and CAR measurement indices were derived: awakening cortisol levels, the mean increase in cortisol levels (MnInc) and total cortisol secretion (AUC G ). On Night 1, participants were informed that they were required to complete a series of demanding cognitive tasks within the sleep laboratory during the following day. Participants completed the tasks as expected or unexpectedly performed sedentary activities. Results: Compared to the no-demand group, the demand group displayed significantly higher levels of state anxiety immediately completing the first task. There were no subsequent differences between the demand and no-demand groups in Night 2 subjective sleep continuity, objective sleep continuity or architecture, or on any Day 3 CAR measure. Conclusion: These results indicate that sleep and the CAR are not differentially affected depending on whether or not an anticipated stressor is then experienced. This provides further evidence to indicate that the CAR is a marker of anticipation and not recovery. In order to disrupt sleep, a stressor may need to be personally relevant or of a prolonged duration or intensity. Keywords: stress, cortisol, polysomnography, sleep, anticipation
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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) | 0.003 | 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".