The Effectiveness of a Sleep Optimization Program on Insomnia, Anxiety, Perceived Stress, and Emotion Dysregulation Among Football Players With Sleep Complaints
Bibliographic record
Abstract
Research has shown that elite athletes frequently experience both insufficient and poor-quality sleep. In the present study, we examined the effectiveness of a sleep optimization intervention comprised of mindfulness and sleep hygiene on insomnia severity, symptoms of anxiety, stress, and emotion dysregulation among football players with sleep complaints. Sixty male football players with sleep complaints (mean age = 29.31, SD = 3.8) were randomly assigned to the active control condition (wellness program) or the sleep optimization intervention program (mindfulness plus sleep hygiene). All participants filled out questionnaires on insomnia severity, anxiety, perceived stress, and emotion dysregulation. Three data assessments were made: one at the start of the intervention (baseline), one at the end of the intervention 8 weeks later (posttest), and one 4 weeks after the posttest (follow-up). The severity of insomnia, anxiety, stress, and emotion dysregulation decreased over time in the sleep optimization group from baseline to posttest and at the follow-up. According to the present results, a sleep optimization intervention reduced insomnia, anxiety, stress symptoms, and emotion dysregulation in football players with sleep complaints.
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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) | 0.001 | 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".