This study examined the ability of the Ru-SATED scale to detect elevated insomnia symptoms, and explored whether signal detection varied by sex or age.

U.S. adults ages 19-99 (N=3284; Mage=42.7±16.7; 45% male) completed online versions of the Ru-SATED and Insomnia Severity Index (ISI) measures, measuring sleep health and insomnia symptom severity, respectively. Receiver operating characteristic (ROC) analyses, examining criterion-related validity, were performed to identify the optimal Ru-SATED score to identify elevated insomnia symptoms based on an ISI total score ≥10. The area under the curve, sensitivity, specificity, and accuracy were calculated to evaluate the model’s performance at different values. Exploratory subgroup analyses evaluated performance across age and sex.

ROC analyses identified a Ru-SATED score of ≤8 had the strongest signal detection performance for detecting elevated insomnia symptoms. However, exploratory analyses suggested a lower score of ≤7 for young adults and a higher score of ≤9 for female participants.

Ru-SATED scores contain an insomnia-related signal, consistent with a conceptual overlap between multidimensional sleep health and insomnia symptoms. These findings provide evidence of the scale’s criterion-related validity and support its potential utility in population-based sleep-health research.

The Ru-SATED assesses domains that conceptually overlap with insomnia symptoms, yet little is known about how well sleep-health scores capture insomnia symptoms. This study evaluated the criterion-related validity of the Ru-SATED scale by examining its ability to detect elevated insomnia symptom burden (ISI ≥10) in a large U.S. adult sample and explored whether performance varied by age or sex.

Ru-SATED scores demonstrated meaningful signal detection performance for identifying individuals with elevated insomnia symptoms, supporting the scale’s criterion-related validity and highlighting conceptual links between sleep health and insomnia symptoms. Exploratory subgroup analyses suggested demographic variability in performance, underscoring the need for special attention in unique populations. These findings support the use of Ru-SATED in population-based sleep-health research and clarify how sleep-health dimensions relate to insomnia symptoms.