0351 Towards Interpreting Consumer Sleep Data: Distributions of Sleep Scores. (25th May 2022)

• Record Type: Journal Article
• Authors: Raymann, Roy; Nayak, Nyayabrata; Watson, Nathaniel; Gahan, Luke; Gottlieb, Elie
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A158
• Page End: A158
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.348
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: With the rise of sleep measurement technology becoming widely available to the public, it has become apparent that traditional sleep metrics might not be best suited for a lay audience. Most consumer industry has started including a metric that would capture sleep quality, although the exact calculations of these scores remain proprietary. These novel outcome metrics require a set of reference values in order to become interpretable. Here, we provide reference values for the parameters SleepScore, BodyScore and MindScore as included in the SleepScore Labs non-contact radiofrequency sleep measurement devices. Methods: SleepScore is a sleep quality metric that includes objectively measured total sleep time (TST), sleep onset latency (SOL) and sleep stage durations, normalized for aged and sex, using reference values of Ohayon et al (2004), ranging from 0-100. BodyScore reflects the normalized amount of deep sleep, whereas MindScore reflects the normalized amount of REM, ranging from 0-100. Data from 40, 862 S+ and Max users between 18 and 98 years old were used to calculate distribution statistics. Results: The average age of users was 53±15 years old. Individual scores of SleepScore, BodyScore and MindScore ranged from 0-100 and their distribution was left-skewed. SleepScore averaged 81±11, with the first quartile (Q1) at 73, median at 81 and third quartile (Q3) at 88, and a mode of 89. BodyScore averaged 81±10 with Q1 at 73, median at 80 and Q3 at 86, and a mode of 84. MindScore averaged 78±10 with Q1 at 72, median at 79 and Q3 at 84, and a mode of 83. Despite being algorithmically normalized for age, average SleepScore increased from 70 to 88 across the age range, BodyScore increased from 71 to 89, and MindScore increased from 75 to 81. Conclusion: SleepScores, BodyScores and MindScores presented to the average consumer will mostly show them a number in the low 70 to high 80 range. This distribution was intentionally created as being left-skewed to prevent triggering anxiety that may contribute to orthosomnia. Despite the intent to create a normalized score that would not be impacted by age, the data show an increase of scores by age. Support (If Any):