Association between Beverage Consumption and Sleep Quality in Adolescents
Bibliographic record
Abstract
The objective of this study was to verify if the consumption of different beverages (such as water, 100% pure fruit juice, and sugar-sweetened beverages (SSBs)) is associated with adolescents’ sleep quality. French-speaking adolescents were recruited in person and online throughout the province of Québec (Canada) from the end of March to early July 2023. Beverage consumption and sleep quality were measured using French versions of validated questionnaires specifically designed for adolescents. A total of 218 adolescents (14–17 years; 55.5% female) completed the online survey. Among caffeinated SSBs, energy drink (rs = −0.16; p = 0.0197) and sugar-sweetened coffee (rs = −0.33; p < 0.0001) intake was correlated with adolescents’ sleep quality. Energy drink consumption (β = −0.0048; p = 0.0005) and being male (β = 0.6033; p < 0.0001) were associated with adolescents’ sleep quality. There was an interaction between sugar-sweetened coffee intake and biological sex that was associated with adolescents’ sleep quality (p = 0.0053). Sugar-sweetened coffee consumption was correlated with adolescent girls’ abilities to go to bed (rs = −0.21; p = 0.0203) and fall asleep (rs = −0.28; p = 0.0020), while in boys, it was only significantly correlated with their abilities to go to bed (rs = −0.27; p = 0.0069). Public health interventions aimed at adolescent boys should primarily target lowering energy drink consumption, while those aimed at girls should prioritize sugar-sweetened coffee intake to possibly improve their sleep quality.
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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 | 0.000 | 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".