An examination of social rhythms in a clinical insomnia population and good sleeper comparison group
Bibliographic record
Abstract
Insomnia had generally been conceptualized as a nighttime disorder, while the daytime experience of insomnia has been largely ignored. However, there are several lines of research suggesting daytime experiences as well as daytime behaviours are equally important. For example, daily behavioural routines commonly referred to as social rhythms (e.g., exercise, attendance of school or work, recreation, engagement in social activities) have been identified as potential zeitgebers (i.e., time cues that help to regulate the biological clock). Previous research has shown that regulating behavioural zeitgebers may have promising benefits for sleep. As such, this study examined the daytime activities in a clinical insomnia population and a good sleeper comparison group. Participants (N = 69) prospectively monitored their sleep and daily activities for a two-week period, while wearing a wrist actiwatch. Those with insomnia appear to engage in activities characterized by significantly less regularity than good sleepers. However, those with insomnia were found to engage in similar levels of daily activities compared to good sleepers. Findings from this study highlight the relative importance of daytime activities on this supposed nighttime process. Accordingly, future research would benefit from testing treatment components that focus on regulating daytime activities, which would likely improve treatment outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".