Background. Day-to-day changes in sleep-wake patterns are important to quantify because
they can result in circadian disruption, a risk factor for health outcomes. Traditionally, sleep
regularity has been assessed by comparing each day to the average sleep-wake pattern, using
metrics such as standard deviation (StDev) and Interdaily Stability (IS). Recently, metrics have
been proposed to instead capture variability between consecutive days: the Sleep Regularity
Index (SRI) and the Composite Phase Deviation (CPD). Here, we systematically compared
these metrics across a range of sources of day-to-day variability, including naps, awakenings,
and missing data.
Methods. Sleep-wake patterns were synthetically generated over 2-28 days with a weekdayweekend structure. Daily sleep variability was introduced by randomly drawing daily midsleeps
and/or sleep durations from a normal distribution with standard deviation ranging from 0-
120min. Average estimates and 95% confidence intervals (CIs) were calculated for each metric
under the following scenarios: (1) ‘scrambling’ the order of days, (2) fragmented sleep (i.e. naps,
wake after sleep onset (WASO), and all-nighters), (3) varying number of days, and (4) randomly
vs. non-randomly (i.e. very early/late sleep more likely to be missing) missing data.
Results. (1) Scrambling did not affect IS and StDev values but did affect SRI and CPD values,
showing that the metrics measure sleep regularity on different time scales: global vs. circadian.
(2) SRI and IS behaved similarly for naps and WASO but differed for all-nighters: SRI values
increased (more regular) when all-nighters exceeded 50% of nights, whereas IS yielded
monotonically lower (less regular) scores. (3) When based on £ 7 days, StDev and IS
overestimated how regular patterns were by up to 40% whereas SRI and CPD were more
stable, yet with wider CIs requiring up to 40% larger samples. (4) All metrics were highly
sensitive to non-randomly missing data but remarkably stable for up to 50% randomly missing
data.
Conclusions. All examined metrics have been used for quantifying sleep regularity, yet they
measure different aspects and should be seen as complementary rather than redundant.
Studies should consider including more than one metric and examining mechanistic links
between circadian disruption and sleep regularity
