78 The associations between objective measures of sleep averages and variability with report card grades in adolescents
Bibliographic record
Abstract
Considerable research points to the importance of sleep for academic success. Short and inconsistent sleep are common in adolescents. Many adolescents present high intraindividual variability (IIV), the day-to-day variability in an individual’s sleep duration, timing, and efficiency, even within school nights. To date, only a paucity of studies has examined the associations between sleep IIV and averages with school grades in adolescents. However, these studies used subjective measures of sleep and showed mixed results. The goal of this study was to determine the extent to which averages and IIV in sleep duration, timing, and efficiency were associated with academic performance in adolescents using objective sleep measures. It was hypothesized that longer average sleep duration, higher sleep continuity, and smaller IIV would be associated with better grades. The sample consisted of 119 participants: 36 boys and 83 girls aged 12–18 years (SD = 1.35 years). Nighttime sleep was measured for five school nights using actigraphy paired with sleep logs. Academic performance was measured using report card grades. The associations between sleep and academic performance were examined using hierarchical regression analyses adjusted for potential confounds of puberty status, gender, and socioeconomic status. IIV of the sleep measures sleep duration, timing, and efficiency were calculated using individual standard deviations. The average duration of time spent asleep and the number of immobile minutes, indicating higher sleep continuity, measured by actigraphy were found to be associated with better grades in Mathematics and in French. IIV in sleep duration, timing, and efficiency were not significantly associated with report card grades. Longer average time asleep and immobile sleep time were associated with higher Math and French grades, suggesting that sleep quality and duration both contribute to students’ performance in core school subjects. Weekday IIV in sleep measures were not associated with academic performance in adolescent students. Pediatricians and other health professionals can contribute to improving youth academic success by helping them to maintain or achieve healthy sleep.
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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 | 0.002 | 0.007 |
| 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".