Comparison of Sleep Regularity Index (SRI) scores calculated by open-source packages and implications for outcomes research: rationale and design of the RIRI statement (Reporting Items for Regularity Indices)

Abstract The day-to-day regularity of sleep–wake timing refers to time-varying patterns of behavioral cycles, which co-occur with temporally associated environmental exposures and circadian rhythms. Introduced in 2017, the Sleep Regularity Index (SRI) has enabled rigorous study of the health and performance implications of the day-to-day regularity of sleep–wake timing. Since its introduction, multiple open-source calculators have been published to facilitate SRI scoring from timestamped sleep–wake data; however, the comparability of these calculators had not previously been evaluated. Here, we sought to (1) estimate SRI usage and method of calculation in peer-reviewed studies published since its establishment; (2) compare SRI scores calculated by two widely used SRI calculators, sleepreg and GGIR; (3) compare results from prospective assessments of the relationship between sleepreg SRI scores versus GGIR SRI scores and previously examined health outcomes. We found that amidst increasing use of the SRI, non-disclosure and heterogeneity in the method of SRI calculation are common. Additionally, among more than 70 000 adults with accelerometer-derived sleep–wake data, SRI scores calculated by two widely used open-source packages differed markedly, both in absolute and relative values. Applied to prospective clinical outcome models for all-cause mortality, incident type 2 diabetes, and incident atrial fibrillation or atrial flutter, the method of calculation alone meaningfully changed results and interpretations. In light of these findings, we developed and introduced a 14-item RIRI statement (Reporting Items for Regularity Indices) to standardize reporting and promote reproducibility in research involving the SRI or complementary regularity indices.