Ajar Diushekeeva, Claudia Picard-Deland, Santiago Hidalgo, Antonio Zadra
{"title":"Beyond screen time: Pre-sleep media use profiles and sleep outcomes in adults","authors":"Ajar Diushekeeva, Claudia Picard-Deland, Santiago Hidalgo, Antonio Zadra","doi":"10.1016/j.chbr.2026.101209","DOIUrl":null,"url":null,"abstract":"<div><div>Pre-sleep media use has been widely implicated in sleep disturbances, yet most research has focused on children, adolescents, or young adults, and has relied on coarse measures of overall screen time while offering limited insight into patterns of use. The present cross-sectional study aimed to provide a comprehensive and nuanced assessment of media use within the hour before sleep in a large and diverse adult sample, and to examine how distinct media devices, activities, and usage patterns relate to sleep outcomes. A total of 722 adults (aged 18–75+) completed an online questionnaire assessing pre-sleep media use, media-related habits, self-reported sleep quality, sleep duration, and sleep onset latency. Hierarchical ordinal logistic regressions indicated that pre-sleep media use explained a modest but meaningful proportion of variance in sleep outcomes (approximately 8% for sleep quality and duration and 15% for sleep onset latency), with media use habits more consistently associated with poorer sleep outcomes than device type or specific media activities. Latent class analysis identified four distinct pre-sleep media use profiles: Versatile Moderate Users, Social Media-Streaming Moderate Users, Traditional Low Users, and Heavy Users. Class membership was strongly associated with sleep outcomes: Traditional Low Users exhibited consistently better sleep quality, longer sleep duration, and shorter sleep onset latency, whereas Social Media-Streaming Moderate Users and Heavy Users showed poorer sleep across outcomes. These findings underscore the importance of considering not only the amount of media use before sleep, but also the configurations of media activities and habitual patterns of engagement when evaluating associations with adult sleep health.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"23 ","pages":"Article 101209"},"PeriodicalIF":5.5000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in human behavior reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451958826002836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Pre-sleep media use has been widely implicated in sleep disturbances, yet most research has focused on children, adolescents, or young adults, and has relied on coarse measures of overall screen time while offering limited insight into patterns of use. The present cross-sectional study aimed to provide a comprehensive and nuanced assessment of media use within the hour before sleep in a large and diverse adult sample, and to examine how distinct media devices, activities, and usage patterns relate to sleep outcomes. A total of 722 adults (aged 18–75+) completed an online questionnaire assessing pre-sleep media use, media-related habits, self-reported sleep quality, sleep duration, and sleep onset latency. Hierarchical ordinal logistic regressions indicated that pre-sleep media use explained a modest but meaningful proportion of variance in sleep outcomes (approximately 8% for sleep quality and duration and 15% for sleep onset latency), with media use habits more consistently associated with poorer sleep outcomes than device type or specific media activities. Latent class analysis identified four distinct pre-sleep media use profiles: Versatile Moderate Users, Social Media-Streaming Moderate Users, Traditional Low Users, and Heavy Users. Class membership was strongly associated with sleep outcomes: Traditional Low Users exhibited consistently better sleep quality, longer sleep duration, and shorter sleep onset latency, whereas Social Media-Streaming Moderate Users and Heavy Users showed poorer sleep across outcomes. These findings underscore the importance of considering not only the amount of media use before sleep, but also the configurations of media activities and habitual patterns of engagement when evaluating associations with adult sleep health.