Circadian phase delay induced by phototherapeutic devices.
Bibliographic record
Abstract
INTRODUCTION: The Canadian Forces has initiated a multiple study project to optimize circadian phase changes using appropriately timed phototherapy and/or ingestion of melatonin for those personnel on long-range deployments and shift workers. The work reported here compared four phototherapeutic devices for efficacy in effecting circadian phase delays. METHODS: In a partially counterbalanced treatment order, 14 subjects (7 men and 7 women), ages 18-51 yr, participated in 5 weekly experimental sessions of phototherapy with 4 different phototherapy devices (light tower, light visor, Litebook, LED spectacles) and a no-phototherapy control. Phototherapy was applied from 24:00 to 02:00 on night. (1) Dim light melatonin onset (DLMO) was assessed on night 1 and night. (2) Subjects were tested for psychomotor performance (serial reaction time, logical reasoning, and serial subtraction tasks) and completed the Stanford Sleepiness Scale on night 1 at 19:00, 23:00, 01:00, 02:00, and 03:00. After phototherapy, subjects completed a phototherapy side-effects questionnaire. RESULTS: All phototherapy devices produced melatonin suppression and significant phase delays. Sleepiness was significantly decreased with the light tower, the light visor, and the Litebook. Task performance was only slightly improved with phototherapy. The LED spectacles and light visor caused greater subjective performance impairment, more difficulty viewing the computer monitor and reading printed text than the light tower or the Litebook. The light visor, the Litebook, and the LED spectacles caused more eye discomfort than the light tower. CONCLUSIONS: The light tower was the best device, producing melatonin suppression and circadian phase change while relatively free of side effects.
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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) | 0.003 | 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".