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  • Title: Multilevel modeling of chronotype and weekdays versus weekends to predict nonrestorative sleep.
    Author: Tutek J, Molzof HE, Lichstein KL.
    Journal: Chronobiol Int; 2017; 34(10):1401-1412. PubMed ID: 29064299.
    Abstract:
    Nonrestorative sleep, a form of subjective sleep disturbance that has been largely neglected in the literature, is newly accessible to researchers via the validated restorative sleep questionnaire (RSQ). The daily version of the RSQ allows for analysis of within-subjects variation in restorative sleep across repeated samplings, and such day-to-day regularity in sleep variables has been highlighted as an important new direction for research. The present study used a sophisticated statistical approach, multilevel modeling, to examine the contributions of circadian chronotype, calendar day of questionnaire completion (weekends versus weekdays), and their interaction in explaining both interindividual and intraindividual variance in restorative sleep. Analyses were conducted using an archival dataset of college undergraduates who continuously completed daily RSQs over a 14-day sampling period. In the final multilevel model, possessing an evening type predicted lower restorative sleep between subjects, while sampling on weekdays predicted lower restorative sleep within subjects. Furthermore, a cross-level interaction was observed, such that the difference in restorative sleep on weekends versus weekdays was more pronounced among those with greater evening circadian preference. All of the effects were maintained after accounting for the significant influence of gender (women had less restorative sleep than men). These results are theoretically consistent with findings that evening types display stronger disparities in sleep schedules across free and workdays (i.e., social jet lag), and attest to the usefulness of multilevel models for statistically investigating how stable traits interact with factors that vary day to day (e.g., work or school schedules) in influencing sleep outcomes.
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