0718 Interaction Between Sleep-Wake Pathology and Excessive Daytime Sleepiness in School-Based Cohort: Insights from Longitudinal Survey Data Set

Abstract Introduction Excessive daytime sleepiness (EDS) in adolescents is estimated to affect 4–20% of the population and may signal underlying sleep-wake pathology or hypersomnolence disorders. School-based screening programs provide a unique opportunity to identify and address these concerns early. Previous analyses of the Wake Up and Learn pilot cohort demonstrated improvements in sleep behaviors over time using the Children’s Sleep Habits Questionnaire (CSHQ). However, the interaction between CSHQ-derived pathology and Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD) scores remains Methods We performed an exploratory factor analysis to identify the factors within the CSHQ that indicate presence of sleep or circadian pathology on the CSHQ in those with and without identified pathologic scores. We then evaluated the relationship of these factors with the presence or absence of EDS based on responses to ESS-CHAD. Using the factors identified on the exploratory factor analysis, an evaluation of the individual and combination of factors was evaluated to determine the relationship to sleepiness. Results The interaction between factors that lead to pathologic sleepiness vary by individual. While CSHQ scores demonstrated significant improvement over time, ESS scores showed minimal variability, suggesting resistance to behavioral interventions and highlighting potential underlying medical etiologies. Further analysis will be presented to characterize these interactions and identify high-risk phenotypes. Conclusion Understanding the individual factors driving pathology on the ESS-CHAD provides greater clarity on how to identify individual pathology and anticipate future care needs. Findings from this pilot cohort will inform school-based screening strategies and support recommendations for early identification and management of hypersomnolence disorders. Support (if any)

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0717
Primary Topic
Sleep and related disorders
Type
article
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article

0718 Interaction Between Sleep-Wake Pathology and Excessive Daytime Sleepiness in School-Based Cohort: Insights from Longitudinal Survey Data Set

Anne Morse, Erin Van Enkevort, Alicia Johns, Kristina Blessing
SLEEP
Sleep and related disorders
article

0718 Interaction Between Sleep-Wake Pathology and Excessive Daytime Sleepiness in School-Based Cohort: Insights from Longitudinal Survey Data Set

Anne Morse, Erin Van Enkevort, Alicia Johns, Kristina Blessing
article en

Abstract

Abstract Introduction Excessive daytime sleepiness (EDS) in adolescents is estimated to affect 4–20% of the population and may signal underlying sleep-wake pathology or hypersomnolence disorders. School-based screening programs provide a unique opportunity to identify and address these concerns early. Previous analyses of the Wake Up and Learn pilot cohort demonstrated improvements in sleep behaviors over time using the Children’s Sleep Habits Questionnaire (CSHQ). However, the interaction between CSHQ-derived pathology and Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD) scores remains Methods We performed an exploratory factor analysis to identify the factors within the CSHQ that indicate presence of sleep or circadian pathology on the CSHQ in those with and without identified pathologic scores. We then evaluated the relationship of these factors with the presence or absence of EDS based on responses to ESS-CHAD. Using the factors identified on the exploratory factor analysis, an evaluation of the individual and combination of factors was evaluated to determine the relationship to sleepiness. Results The interaction between factors that lead to pathologic sleepiness vary by individual. While CSHQ scores demonstrated significant improvement over time, ESS scores showed minimal variability, suggesting resistance to behavioral interventions and highlighting potential underlying medical etiologies. Further analysis will be presented to characterize these interactions and identify high-risk phenotypes. Conclusion Understanding the individual factors driving pathology on the ESS-CHAD provides greater clarity on how to identify individual pathology and anticipate future care needs. Findings from this pilot cohort will inform school-based screening strategies and support recommendations for early identification and management of hypersomnolence disorders. Support (if any)

SLEEPVol. 49(Supplement_1)
Geisinger Medical Center (US)
Quality Education
Openalex Percentile: Top 7%
Sleep and related disorders
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