Steven Holfinger, Sharon Schutte-Rodin, Dulip Ratnasoma, Ambrose A Chiang, Kelly Baron, Maryann Deak, Evin Jerkins, Julie Baughn, Kevin Gipson, Reut Gruber, Jennifer N Miller, Shalini Paruthi, Sachin Shaw, Fariha Abbasi-Feinberg, Eric Olsen, Anuja Bandyopadhyay
{"title":"2020-2022年新型睡眠跟踪和睡眠测试技术出版物的发展趋势。","authors":"Steven Holfinger, Sharon Schutte-Rodin, Dulip Ratnasoma, Ambrose A Chiang, Kelly Baron, Maryann Deak, Evin Jerkins, Julie Baughn, Kevin Gipson, Reut Gruber, Jennifer N Miller, Shalini Paruthi, Sachin Shaw, Fariha Abbasi-Feinberg, Eric Olsen, Anuja Bandyopadhyay","doi":"10.5664/jcsm.11562","DOIUrl":null,"url":null,"abstract":"<p><strong>Study objectives: </strong>To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.</p><p><strong>Methods: </strong>Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.</p><p><strong>Results: </strong>96 of 3849 articles were included. Most studies were adult performance evaluation (validation) studies, often comparing a novel technology to polysomnography. Sleep tracker publications tended to be USA-based, non-industry funded, performance studies on healthy adults using non-FDA (Food and Drug Administration) cleared technologies. Sleep apnea testing technologies were more frequently industry-funded and FDA-cleared. All studied technologies utilized software with an algorithm and/or artificial intelligence. Few studies used randomized control designs, or accounted for recruitment/attrition biases associated with participants' age, race/ethnicity, or comorbid health conditions.</p><p><strong>Conclusions: </strong>Evidence-based publications have not kept pace with the proliferation and landscape of' consumer and clinical sleep technologies. Due to the variance in technologies used within sleep research, careful review of the software used within studies is recommended. Future publications may fill identified gaps by including underrepresented populations, maintaining independence from industry, and through rigorous study design.</p>","PeriodicalId":50233,"journal":{"name":"Journal of Clinical Sleep Medicine","volume":" ","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evolving trends in novel sleep tracking and sleep testing technology publications between 2020-2022.\",\"authors\":\"Steven Holfinger, Sharon Schutte-Rodin, Dulip Ratnasoma, Ambrose A Chiang, Kelly Baron, Maryann Deak, Evin Jerkins, Julie Baughn, Kevin Gipson, Reut Gruber, Jennifer N Miller, Shalini Paruthi, Sachin Shaw, Fariha Abbasi-Feinberg, Eric Olsen, Anuja Bandyopadhyay\",\"doi\":\"10.5664/jcsm.11562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Study objectives: </strong>To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.</p><p><strong>Methods: </strong>Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.</p><p><strong>Results: </strong>96 of 3849 articles were included. Most studies were adult performance evaluation (validation) studies, often comparing a novel technology to polysomnography. Sleep tracker publications tended to be USA-based, non-industry funded, performance studies on healthy adults using non-FDA (Food and Drug Administration) cleared technologies. Sleep apnea testing technologies were more frequently industry-funded and FDA-cleared. All studied technologies utilized software with an algorithm and/or artificial intelligence. Few studies used randomized control designs, or accounted for recruitment/attrition biases associated with participants' age, race/ethnicity, or comorbid health conditions.</p><p><strong>Conclusions: </strong>Evidence-based publications have not kept pace with the proliferation and landscape of' consumer and clinical sleep technologies. Due to the variance in technologies used within sleep research, careful review of the software used within studies is recommended. Future publications may fill identified gaps by including underrepresented populations, maintaining independence from industry, and through rigorous study design.</p>\",\"PeriodicalId\":50233,\"journal\":{\"name\":\"Journal of Clinical Sleep Medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Sleep Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.5664/jcsm.11562\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Sleep Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5664/jcsm.11562","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Evolving trends in novel sleep tracking and sleep testing technology publications between 2020-2022.
Study objectives: To update sleep medicine providers regarding (1) published research on the uses and performance of novel sleep tracking and testing technologies (2) the use of artificial intelligence to acquire and process sleep data and (3) research trends and gaps regarding the development and/or evaluation of these technologies.
Methods: Medline and Embase electronic databases were searched for studies utilizing screening and diagnostic sleep technologies, published between 2020 and 2022 in journals focusing on human sleep. Studies' quality was determined based on the Study Design criteria of The Oxford Centre for Evidence-Based Medicine Levels of Evidence.
Results: 96 of 3849 articles were included. Most studies were adult performance evaluation (validation) studies, often comparing a novel technology to polysomnography. Sleep tracker publications tended to be USA-based, non-industry funded, performance studies on healthy adults using non-FDA (Food and Drug Administration) cleared technologies. Sleep apnea testing technologies were more frequently industry-funded and FDA-cleared. All studied technologies utilized software with an algorithm and/or artificial intelligence. Few studies used randomized control designs, or accounted for recruitment/attrition biases associated with participants' age, race/ethnicity, or comorbid health conditions.
Conclusions: Evidence-based publications have not kept pace with the proliferation and landscape of' consumer and clinical sleep technologies. Due to the variance in technologies used within sleep research, careful review of the software used within studies is recommended. Future publications may fill identified gaps by including underrepresented populations, maintaining independence from industry, and through rigorous study design.
期刊介绍:
Journal of Clinical Sleep Medicine focuses on clinical sleep medicine. Its emphasis is publication of papers with direct applicability and/or relevance to the clinical practice of sleep medicine. This includes clinical trials, clinical reviews, clinical commentary and debate, medical economic/practice perspectives, case series and novel/interesting case reports. In addition, the journal will publish proceedings from conferences, workshops and symposia sponsored by the American Academy of Sleep Medicine or other organizations related to improving the practice of sleep medicine.