Self-Reported Academic Performance and Lifestyle Habits of School Children in Japan
Bibliographic record
Abstract
Background and Objective: The purpose of this study was to determine the lifestyle habits significantly associated with self-reported academic performance (AP) in children in grades 5 to 12 in Japan. Methods: A total of 2,114 completed questionnaires were analyzed. Factors examined included habits related to sleeping, eating, defecation, physical activity, and screen time, in addition to body mass index (BMI). Social jet lag (SJL) was calculated from sleeping factors and categorized into five groups according to its value: minus 1 or less (SJL 1), more than minus 1 and 0 or less (SJL 2), more than 0 and 1 or less (SJL 3), more than 1 and 2 or less (SJL 4), and more than 2 (SJL 5). The association between self-reported AP and other factors except for SJL was assessed by means of multinomial logistic regression analysis. Results: Factors significantly associated with good self-reported AP included female gender, lower grade, less sleepiness, lower BMI, intake of breakfast, less constipation, early wake-up time during the weekend, and short screen time during the weekend. The mean self-reported AP of SJL 3 was better than that of both SJL 5 and SJL 1. Conclusions: Self-reported AP was associated with gender, grade, BMI, sleep, breakfast, defecation, and screen time in children in grades 5 to 12 in Japan. It must be ensured that children take enough time to perform the indispensable human behaviors of sleeping, eating, defecation, and physical activity.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".