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Sleep and affect in adolescents: Bidirectional daily associations over 28-day ecological momentary assessment.

Lin ShenJoshua F WileyBei Bei
Published in: Journal of sleep research (2021)
We examined bidirectional, temporal associations between daily sleep and affect under naturally restricted (school) and unrestricted (vacation) sleep opportunities, while incorporating valence (positive/negative) and arousal (high/low) dimensions of affect. Sleep and affect were measured over 2 weeks of school and 2 weeks of vacation in 205 adolescents (54.1% females, Mage  = 16.9 years), providing 5,231 days of data. Total sleep time and sleep efficiency were measured using actigraphy and sleep diary. High- and low-arousal positive and negative affect were self-reported each afternoon. Between- and within-person sleep-affect associations were tested using cross-lagged, multilevel models. Lagged outcome, day of the week, study day and socio-demographics were controlled. Bidirectional associations between self-report sleep and affect were found between-persons: longer self-report total sleep time associated with lower high- and low-arousal negative affect. Higher high-arousal positive affect associated with longer actigraphy total sleep time between-persons, but predicted shorter same-night actigraphy total sleep time within-persons. Results did not differ between school and vacation. Significant within-person random effects demonstrate individual differences in daily sleep-affect associations. Associations differed based on sleep measurement and affect dimensions, highlighting the complex sleep-affect relationship. Strong between-person associations between self-report sleep and affect suggest improving either sleep or mood may benefit the other; alternatively, addressing a common cause may lead to changes in both sleep and affect. Although overall high-arousal positive affect was protective of sleep duration, on a day-to-day basis, higher-than-usual high-arousal positive affect may reduce sleep duration on nights it is experienced. Further research needs to identify causes of individual differences in sleep-affect associations.
Keyphrases
  • physical activity
  • sleep quality
  • mental health
  • young adults
  • depressive symptoms
  • machine learning
  • bipolar disorder
  • risk assessment
  • artificial intelligence
  • climate change
  • human health