0239 Excessive Daytime Sleepiness, Reduced Sleep Duration on Weekend and Social Jetlag are associated with Caffeine Consumption in Teenagers
Bibliographic record
Abstract
Caffeine consumption is increasing in adolescents, particularly due to the gaining popularity of energy drinks. Yet, much more research is needed to better understand the motivation underlying these consumption habits and the impact of caffeine on sleep and daytime functioning in teenagers. The purpose of this study is to examine the association between sleep habits, daytime sleepiness and energy drinks and coffee consumption in adolescents. 674 adolescents (280 boys, 394 girls, 14 to 17 years old) completed a questionnaire on sleep habits and caffeine consumption. First, Pearson’s correlations between energy drinks and coffee consumption were calculated with total sleep time (TST) on school nights (SN) and weekend nights (WN), social jetlag (SJ), and excessive daytime sleepiness (EDS). A multiple linear regression model was performed to examine the unique contribution of each variable that was significantly associated with caffeine consumption in teenagers. Since age could also be associated with this habits, this variable was added to the model. Results showed that energy drinks and coffee consumption was associated with EDS (r=.34;p<.001), TST on SN (r=-.145;p<.001) and WN (r=-.087;p<.05), and SJ (r=.18;p<.001). Multiple linear regression modeling demonstrated that 14,8% of the variance in the consumption habits can be explained by the model (p<.001). EDS was the largest predictor ( β =.29,p<.001), followed by SJ ( β =.18,p<.001) and TST on WN ( β =-.13,p<.01). Age and TST on SN were not significant predictors of caffeine consumption. These results confirm that although EDS is associated with energy drinks and coffee consumption in adolescents, sleep timing and duration on weekend also seem to be associated with this habit. Our results could suggest that caffeine is used to compensate for daytime sleepiness partly due to an increased social jetlag. It could also suggest that teenagers who consume high level of caffeine have more trouble sleeping on weekends. However, it is also possible that teenagers are deliberately using caffeine as a way to increase social and personal time during weekend. This needs to be investigated. None.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.004 | 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".