Sleep Duration Is Associated with Academic Achievement of Adolescent Girls in Mathematics
Bibliographic record
Abstract
Lanyi Lin,1 Gail Somerville,2 Johanne Boursier,3 Jose Arturo Santisteban,1 Reut Gruber1,4 1Attention, Behaviour and Sleep Lab, Douglas Mental Health University Institute, Montréal, QC H4H 1R3, Canada; 2Riverside School Board, Saint-Hubert, QC J3Y 0N7, Canada; 3Heritage High School, Riverside School Board, St. Hubert, QC J3Y 3S3, Canada; 4Department of Psychiatry, Faculty of Medicine, McGill University, Montréal, QC H4H 1R3, CanadaCorrespondence: Reut GruberDouglas Mental Health University Institute, 6875 LaSalle Boulevard, Verdun, Montréal, QC H4H 1R3, CanadaTel +1 514 761 6131 ext 3476Fax +1 514 762 3858Email reut.gruber@douglas.mcgill.caPurpose: To examine the associations between objective measures of sleep during the school week and academic achievement in mathematics and languages in typically developing adolescent girls.Methods: Eighty adolescent girls aged 12– 17 years (M=14.74, SD=1.3) participated. For five consecutive weeknights, sleep was assessed in the home environment using an actigraph. Academic achievement was assessed using report card grades.Results: Girls who obtained on average less sleep than the recommended amount of 8 to 10 hrs per night had significantly lower grades in mathematics compared to girls who obtained the recommended amount (77.61 vs 86.16, respectively; ηp2=0.11). Hierarchical regression analyses adjusted for age, pubertal status, and socioeconomic status revealed that longer average sleep time was significantly associated with higher grades in mathematics (B=4.78, 95% CI [2.03,7.53]). No significant associations were found between sleep variables and grades in languages.Conclusion: Longer average weekday sleep duration is associated with academic achievement of adolescent girls in mathematics.Keywords: actigraphy, adolescence, grades, report card, gender
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".