Effects of Constructive Worry, Imagery Distraction, and Gratitude Interventions on Sleep Quality: A Pilot Trial
Bibliographic record
Abstract
Background: There is mounting empirical evidence that poor sleep compromises well‐being. Our study focused on university students who have persistent problems sleeping because their minds are racing with stimulating thoughts and worries. We evaluated three self‐help interventions (constructive worry, imagery distraction, and a gratitude intervention) which were disseminated by e‐mail. Methods: Forty‐one participants (32 females) were randomly assigned to an intervention. Daily measures of sleep and pre‐sleep worry and arousal were collected online during a baseline week followed by an intervention week. Results: Each intervention reduced worry and pre‐sleep arousal, and improved sleep compared to baseline. One intervention did not differ from the others. Participants rated the interventions as moderately helpful. Conclusions: E‐mailed self‐help versions of constructive worry, imagery distraction, or a gratitude intervention helped university students quiet their minds and sleep better. This mode of delivery is feasible for broad distribution and at universities without access to sleep clinicians.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".