Effect of kiwifruit consumption on sleep quality in adults with sleep problems.
Bibliographic record
Abstract
Numerous studies have revealed that kiwifruit contains many medicinally useful compounds, among which antioxidants and serotonin may be beneficial in the treatment of the sleep disorders. The aim of this study was to evaluate the effects of kiwifruit on sleep patterns, including sleep onset, duration, and quality. In this study, we applied a free-living, self-controlled diet design. Twenty-four subjects (2 males, 22 females) 20 to 55 years of age consumed 2 kiwifruits 1 hour before bedtime nightly for 4 weeks. The Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), a 3-day sleep diary, and the Actigraph sleep/activity logger watch were used to assess the subjective and objective parameters of sleep quality, including time to bed, time of sleep onset, waking time after sleep onset, time of getting up, total sleep time, and self-reported sleep quality and sleep onset latency, waking time after sleep onset, total sleep time, and sleep efficiency before and after the intervention. After 4 weeks of kiwifruit consumption, the subjective CPSQI score, waking time after sleep onset, and sleep onset latency were significantly decreased (42.4%, 28.9%, and 35.4%, respectively). Total sleep time and sleep efficiency were significantly increased (13.4% and 5.41%, respectively). Kiwifruit consumption may improve sleep onset, duration, and efficiency in adults with self-reported sleep disturbances. Further investigation of the sleep-promoting properties of kiwifruit may be warranted.
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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".