Are Children Like Werewolves? Full Moon and Its Association with Sleep and Activity Behaviors in an International Sample of Children
Bibliographic record
Abstract
In order to verify if the full moon is associated with sleep and activity behaviors, we used a 12-country study providing 33,710 24-h accelerometer recordings of sleep and activity. The present observational, cross-sectional study included 5812 children ages 9-11 years from study sites that represented all inhabited continents and wide ranges of human development (Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, United Kingdom, and United States). Three moon phases were used in this analysis: full moon (±4 days; reference), half moon (±5-9 days), and new moon (±10-14 days) from nearest full moon. Nocturnal sleep duration, moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LPA), and total sedentary time (SED) were monitored over seven consecutive days using a waist-worn accelerometer worn 24 h a day. Only sleep duration was found to significantly differ between moon phases (~5 min/night shorter during full moon compared to new moon). Differences in MVPA, LPA, and SED between moon phases were negligible and non-significant (<2 min/day difference). There was no difference in the associations between study sites. In conclusion, sleep duration was 1% shorter at full moon compared to new moon, while activity behaviors were not significantly associated with the lunar cycle in this global sample of children. Whether this seemingly minimal difference is clinically meaningful is questionable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".