Xian Li1, Orfeu M Buxton2, Soomi Lee3, Anne-Marie Chang4, Lawrence M Berger5, Lauren Hale6. 1. Program in Public Health, Department of Family, Population and Preventive Medicine, Stony Brook University, USA. Electronic address: stellalixian@hotmail.com. 2. Department of Biobehavioral Health, Pennsylvania State University, USA; Division of Sleep Medicine, Harvard Medical School, USA; Sleep Health Institute, Departments of Medicine and Neurology, Brigham and Women's Hospital, USA; Department of Social and Behavioral Sciences, Harvard Chan School of Public Health, USA. 3. School of Aging Studies, University of South Florida, USA. 4. Department of Biobehavioral Health, Pennsylvania State University, USA; College of Nursing, Pennsylvania State University, University Park, PA, USA. 5. Institute for Research on Poverty and School of Social Work, University of Wisconsin-Madison, USA. 6. Program in Public Health, Department of Family, Population and Preventive Medicine, Stony Brook University, USA.
Abstract
OBJECTIVE: This study examined the associations between four types of screen-based activities and depressive symptoms among adolescents. We further investigated whether sleep characteristics (ie, insomnia symptoms and sleep duration) mediate these associations. METHODS: Data come from 2865 U.S. adolescents (mean age = 15.53, SD = 0.73, 51.8% male) in the age 15 follow-up of the Fragile Families and Child Wellbeing Study. Adolescents completed surveys regarding sleep duration and insomnia symptoms, typical daily duration of four screen activities (social messaging, web surfing, TV/movie watching, and gaming), and depressive symptoms. We constructed a multiple mediation model to elucidate the associations between age 15 screen time, sleep and depressive symptoms, while adjusting for age 9 depressive symptoms. RESULTS: Structural Equation Modeling analyses revealed that the association between screen time and depressive symptoms is partially or fully mediated by sleep. For social messaging, web surfing and TV/movie watching, the three sleep variables fully mediated the positive association between screen time and depressive symptoms. For gaming, the three sleep variables acted as partial mediators in the model, accounting for 38.5% of the association between gaming and depressive symptoms. CONCLUSIONS: Our results highlight both screen-based activities and sleep behaviors as potential intervention targets to reduce depressive symptoms among adolescents.
OBJECTIVE: This study examined the associations between four types of screen-based activities and depressive symptoms among adolescents. We further investigated whether sleep characteristics (ie, insomnia symptoms and sleep duration) mediate these associations. METHODS: Data come from 2865 U.S. adolescents (mean age = 15.53, SD = 0.73, 51.8% male) in the age 15 follow-up of the Fragile Families and Child Wellbeing Study. Adolescents completed surveys regarding sleep duration and insomnia symptoms, typical daily duration of four screen activities (social messaging, web surfing, TV/movie watching, and gaming), and depressive symptoms. We constructed a multiple mediation model to elucidate the associations between age 15 screen time, sleep and depressive symptoms, while adjusting for age 9 depressive symptoms. RESULTS: Structural Equation Modeling analyses revealed that the association between screen time and depressive symptoms is partially or fully mediated by sleep. For social messaging, web surfing and TV/movie watching, the three sleep variables fully mediated the positive association between screen time and depressive symptoms. For gaming, the three sleep variables acted as partial mediators in the model, accounting for 38.5% of the association between gaming and depressive symptoms. CONCLUSIONS: Our results highlight both screen-based activities and sleep behaviors as potential intervention targets to reduce depressive symptoms among adolescents.
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