, J.M. Violanti

Abstract: Sleep quality has a large impact on daily performance and general health. Among the different methods of ob-jectively measuring sleep quality, actigraphy continues to be very popular. It can take continuous activity measurements over several days in order to determine sleep-wake cycles and calculate sleep variables, including the three standard sleep variables used in determining sleep quality: total sleep time, sleep efficiency, and wake-after-sleep onset, in which study analyses use the mean of these variables. In the case of wake-after-sleep onset, which calculates the amount of time be-tween falling asleep and waking up, the average does not characterize wake-after-sleep times as it does not account for the total number of awakenings or the frequencies of wake-after-sleep times. Instead, we recommend using the entire distribu-tion of wake-after-sleep onset times, which we will call waiting time distribution, which better characterizes wake-after-sleep onset than the average value. Sleep quality for each participant was determined by their total sleep time and sleep ef-ficiency. Non-parametric statistics were utilized to determine differences in waiting time distributions between partici-pants with good and poor quality of sleep. Discriminant analysis was performed to show that a distribution of waiting times discriminates better between qualities of sleep than the average wake-after-sleep onset time does. Waiting time dis-tributions were also fit to standard probability distributions for utility and ease of understanding. Analyses show that th