0084 Consumer Sleep Technologies (CSTs) for Use in Real-World Sleep Research Environments: A Survey of Experts

Abstract

Abstract Introduction Consumer sleep technologies (CSTs) have been designed for the everyday consumer rather than as a reliable scientific tool, but are becoming sufficiently accurate for use in the research landscape. Despite the growing conversation about the viability of CSTs for research, manufacturers may not be interested in increasing scientific accuracy in their devices unless doing so is expected to result in greater consumer sales. To establish concensus opinion about important device features and economic demand for CSTs for sleep research, professional opinions from sleep medicine experts were elicited to identify what metrics and device features for measuring sleep outside the laboratory are most desirable to the scientific community. This is the first known attempt to establish consensus opinion or economic valuation for scientifically-desirable CST device features and metrics using expert elicitation within the sleep science community. Methods Sleep and/or circadian researchers with experience collecting data in real-world environments were recruited from international academic, government, clinical, and industry research backgrounds using social media and nonprobability sampling techniques. The anonymous survey was hosted through the online tool Qualtrics between April to July 2021. Exposure to survey recruitment techniques were tracked through Twitter Analytics and Qualtrics. Respondents were asked to rank sleep metrics and consumer sleep technology features to estimate their average level of importance (low, medium, or high). A hypothetical purchase task estimated economic valuation for devices with different features by price. Results Survey respondents were 46 real-world sleep research experts with, on average, 11 (range: 1-27; mode: 10) years of experience conducting human research related to sleep in real-world environments. Sixty-six percent (66%) preferred wrist-worn devices and 52% indicated that sleep onset/offset could be determined from a period of inactivity ≤20 minutes. Eighty-three percent (83%) collected data related to napping. Forty-four percent (44%) preferred a continuous observation window between 4-14 days long. Respondents ranked battery life as the most important factor limiting the observation window. Total sleep time was ranked as the most important measure of sleep followed by objective sleep quality while sleep architecture/depth and diagnostic information were ranked as least important. Economic value was greater for hypothetical devices with longer battery life. Conclusion Real-world sleep experts prefer wrist-worn devices that can reliably estimate sleep and short naps. Battery life is important. Based on responses to both rank order questions and the hypothetical purchase task, estimating sleep depth is less important to researchers than measures of sleep duration and quality. These data set a precedent for future studies to determine the scientific relevance of metrics or how scientific endorsement of a product impacts the potential market value of a CST device. Support (If Any) NA