Discontinuous growth modeling of adaptation to sleep setting changes

Abstract

Introduction: Biomedical devices allow investigators to collect longterm repeated measures data to study adaptation. We examined 26 d of actigraph sleep data and tested for individual differences in sleep patterns prior to, during, and after a transition of sleeping in garrison to sleeping in a field exercise setting. In addition, we examined whether the individual difference variable of participant age (a continuous variable ranging from 19-29 yr) was related to sleep patterns. Methods: Actigraph data was obtained from 77 cadets participating in a month-long military training program. At day 17, participants transitioned from sleeping in garrison to sleeping in a field exercise setting. A discontinuous growth model tested for individual differences in 1) overall sleep time, 2) garrison sleep slope, 3) the transition, and 4) the sleep slope during the field exercise setting. Results: Individuals varied significantly in their overall sleep time, pattern of sleep in garrison, and the degree to which sleep decreased at the transition. The decline in sleep at the transition was related to participant age such that increases in age were associated with larger declines in sleep minutes. Discussion: Individuals display significant variability in sleep patterns that can be detected using discontinuous growth models. The individual difference variable of participant age explains some of this variability. Much of the variability, however, remains unexplained. Future work will benefit from using discontinuous growth models to identify and model individual difference variables such as age when examining response patterns and transitions in data collected in applied field settings.