Partial blue light blocking glasses at night advanced sleep phase and reduced daytime irritability, disruptive behavior and improved morning mood, but did not alter salivary melatonin secretion in Japanese male schoolchildren
Bibliographic record
Abstract
In modern society, delayed sleep patterns among schoolchildren present challenges to academic attendance and performance. The impact of nighttime light exposure, especially blue wavelength light, on sleep delay has long been acknowledged. We investigated the effects of using partial blue light blocking glasses (JINS Screen Lens Heavy [40% cut]) on salivary melatonin levels, sleep patterns, sleep circadian phase, and daytime behavior in 39 male schoolchildren aged 10-12 who regularly wear glasses for myopia. Participants alternated between blue light blocking and standard clear lens glasses, both providing vision correction, for three hours before their habitual bedtime. The study was conducted over five weeks using a crossover design with two-week glasses-wearing sessions and a one-week washout interval between conditions. While blue light blocking glasses did not influence salivary melatonin levels, they significantly advanced the sleep phase (bedtime: 22.03 ± 0.08h vs. 22.13 ± 0.09h, p = 0.040, sleep onset: 22.26 ± 0.08h vs. 22.36 ± 0.10h, p = 0.041). The effects were more pronounced in the second week and accompanied by reduced irritability and disruptive behavior during daytime. Our results suggest that wearing blue light blocking glasses before bedtime may advance the sleep phase and improve daytime behavior in schoolchildren under real-world living conditions, warranting further mechanistic investigation.
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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 | 0.000 |
| 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".