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Record W2937306301 · doi:10.1093/sleep/zsz067.238

0239 Excessive Daytime Sleepiness, Reduced Sleep Duration on Weekend and Social Jetlag are associated with Caffeine Consumption in Teenagers

2019· article· en· W2937306301 on OpenAlexaff
Kim Isabelle-Nolet, Frédérick Michaud, Pascale Gaudreault, Roxanne Godin, Isabelle Green‐Demers, Geneviève Forest

Bibliographic record

VenueSLEEP · 2019
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsCaffeineSleep deprivationMedicineDemographyExcessive daytime sleepinessConsumption (sociology)PsychologyInternal medicineCircadian rhythmSleep disorderPsychiatryInsomnia

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.012
GPT teacher head0.257
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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