{"id":15185,"date":"2026-04-28T05:06:45","date_gmt":"2026-04-28T12:06:45","guid":{"rendered":"https:\/\/www.sleep.ai\/?post_type=news_media&#038;p=15185"},"modified":"2026-04-28T05:06:45","modified_gmt":"2026-04-28T12:06:45","slug":"sleep-ai-publishes-jmir-insomnia-variability-study","status":"publish","type":"news_media","link":"https:\/\/www.sleep.ai\/de\/news\/sleep-ai-publishes-jmir-insomnia-variability-study\/","title":{"rendered":"New Study: Insomnia\u2019s Impact Comes From Unpredictability, Not Sleep Duration"},"content":{"rendered":"<h2><i><span style=\"font-weight: 400;\">Using Sleep.ai\u2019s contactless monitoring, researchers identify nightly variability as a hallmark of insomnia &amp; opens new pathways to manage the condition<\/span><\/i><\/h2>\n<p><b>CARLSBAD, CA \u2014 April 28, 2026 <\/b><span style=\"font-weight: 400;\">\u2014 <\/span><a href=\"http:\/\/sleep.ai\"><span style=\"font-weight: 400;\">Sleep.ai<\/span><\/a><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">the world&#8217;s leading validated sleep intelligence platform, today <\/span><span style=\"font-weight: 400;\">announced findings from a peer-reviewed study led by Washington State University, in collaboration with the University of Washington, exploring sleep patterns in people with chronic insomnia. It is the longest known objective, real-world characterization of objective sleep in chronic insomnia.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Published in <\/span><a href=\"https:\/\/formative.jmir.org\/2026\/1\/e73969\"><i><span style=\"font-weight: 400;\">JMIR Formative Research<\/span><\/i><\/a><span style=\"font-weight: 400;\">, the study tracked 112 adults &#8211; 83 with chronic insomnia and 29 without insomnia &#8211; across eight consecutive weeks of nightly, at-home sleep monitoring using Sleep.ai\u2019s contactless, radio-frequency sleep measurement technology. The results come amid rising interest in tracking sleep over time as a predictor of health outcomes.<\/span><\/p>\n<p><b>Key Findings<\/b><\/p>\n<p><span style=\"font-weight: 400;\">People with chronic insomnia got about the same total amount of sleep each night as those without insomnia (6.57 vs. 6.60 hours). The real difference was in the unpredictability of their sleep. Compared to a control group without insomnia, chronic insomnia patients experienced night-to-night variability in sleep efficiency, time taken to fall asleep, and overnight wakefulness.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This suggests that inconsistent sleep-wake patterns, not simply shorter sleep, may be the debilitating feature of chronic insomnia. Understanding these ups and downs could change how insomnia is diagnosed, measured, and treated. Standard approaches that look only at average sleep and which use questionnaires may miss this important variability.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The long-term measurement of objective sleep data in participants\u2019 own home was made possible by Sleep.ai\u2019s sleep measurement technology. With its unique non-contact (radiofrequency) and PSG-validated sleep measurement technology, the SleepScore Max device leverages patented ResMed technology built on 12 years of research with best-in-class performance validated in <\/span><a href=\"https:\/\/www.sleep.ai\/science-publications\/\"><span style=\"font-weight: 400;\">multiple published performance evaluation studies<\/span><\/a><span style=\"font-weight: 400;\"> to date.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cThis study validates that meaningful sleep insights require more than a single night\u2019s snapshot,\u201d said Elie Gottlieb, PhD, Head of Applied Science, Sleep.ai, and study co-author. \u201cBy tracking sleep objectively and contactlessly in people\u2019s own homes, we can move beyond lab-based limits and give consumers and clinicians tools to understand sleep as it truly happens, night after night \u2013 all without a wearable or touching the body.\u201d<\/span><\/p>\n<p><b>What This Means for Sleep Care<\/b><\/p>\n<p><span style=\"font-weight: 400;\">The study sheds new light on why insomnia feels so unpredictable and disruptive. For people living with the condition, it\u2019s not just about an inability to fall asleep or stay asleep; it&#8217;s the constant night-to-night swings that make rest feel unreliable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For doctors, these findings show the limits of traditional tools like sleep diaries or one-night lab studies, which can miss the bigger picture. And for researchers and companies developing new treatments, tracking how sleep varies from night to night may be more useful than looking only at average sleep hours.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cFor years, insomnia research focused on averages, which often made differences seem small,\u201d said Devon A. Hansen, PhD, lead author at Washington State University. \u201cThis study shows the real story: people with chronic insomnia live with unpredictable sleep night after night. Being able to track this objectively in people\u2019s own homes over two months opens up new possibilities for both research and care.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cAs a sleep doctor and researcher, I know how hard it can be to truly capture patients\u2019 sleep experiences using traditional methods,\u201d said Nathaniel F. Watson, MD, MSc, University of Washington. \u201cThis study shows that contactless, at-home sleep technology can fill that gap. Recognizing nightly variability as a core feature of insomnia could change how we screen, diagnose, and ultimately treat the condition.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For more information on this research, <\/span><a href=\"https:\/\/www.sleep.ai\/insomnia-night-to-night-variability-study\/\"><span style=\"font-weight: 400;\">click here<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<p><b>About Sleep.ai<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Sleep.ai is a global sleep intelligence company delivering science-backed solutions to improve sleep and long-term health across consumer, wellness, and healthcare applications. Powered by nearly one billion hours of sleep data, over 100 publications and conference abstracts, and more than 250 scientific studies, the company combines advanced analytics and behavioral science to support prevention, performance, and health insight.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sleep.ai offers consumer sleep coaching programs, including reimbursable preventive solutions such as Dein Schlaf in Germany, as well as enterprise-grade APIs, SDKs, and R&amp;D services. Trusted by leading brands including Dyson, L&#8217;Or\u00e9al, Therabody, Purple, Thorne, and IFF, Sleep.ai enables partners across health, wellness, and life sciences to embed validated sleep intelligence into their products and services.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Using Sleep.ai\u2019s contactless monitoring, researchers identify nightly variability as a hallmark of insomnia &amp; opens new pathways to manage the condition CARLSBAD, CA \u2014 April 28, 2026 \u2014 Sleep.ai, the world&#8217;s leading validated sleep intelligence&#8230;<\/p>\n","protected":false},"featured_media":0,"template":"","news_media_categories":[1904],"class_list":["post-15185","news_media","type-news_media","status-publish","hentry","news_media_categories-press-releases"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Sleep.ai publishes 8-week JMIR study on chronic insomnia<\/title>\n<meta name=\"description\" content=\"Sleep.ai, Washington State University, and UW publish a peer-reviewed JMIR study on what defines chronic insomnia. 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