Wearing Blue-Blockers in the Morning Could Improve Sleep of Workers on a Permanent Night Schedule: A Pilot Study
Bibliographic record
Abstract
Night shiftworkers often complain of disturbed sleep during the day. This could be partly caused by morning sunlight exposure during the commute home, which tends to maintain the circadian clock on a daytime rhythm. The circadian clock is most sensitive to the blue portion of the visible spectrum, so our aim was to determine if blocking short wavelengths of light below 540 nm could improve daytime sleep quality and nighttime vigilance of night shiftworkers. Eight permanent night shiftworkers (32-56 yrs of age) of Quebec City's Canada Post distribution center were evaluated during summertime, and twenty others (24-55 yrs of age) during fall and winter. Timing, efficacy, and fragmentation of daytime sleep were analyzed over four weeks by a wrist activity monitor, and subjective vigilance was additionally assessed at the end of the night shift in the fall-winter group. The first two weeks served as baseline and the remaining two as experimental weeks when workers had to wear blue-blockers glasses, either just before leaving the workplace at the end of their shift (summer group) or 2 h before the end of the night shift (fall-winter group). They all had to wear the glasses when outside during the day until 16:00 h. When wearing the glasses, workers slept, on average +/-SD, 32+/-29 and 34+/-60 more min/day, increased their sleep efficacy by 1.95+/-2.17% and 4.56+/-6.1%, and lowered their sleep fragmentation by 1.74+/-1.36% and 4.22+/-9.16% in the summer and fall-winter group, respectively. Subjective vigilance also generally improved on Fridays in the fall-winter group. Blue-blockers seem to improve daytime sleep of permanent night-shift workers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".