Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health
<b>Purpose</b>: Previous studies focusing on the relationship between adolescents’ screen time and mental health have uncovered contradictory results. By focusing on smartphone use content (SUC), this study uses specification curve analysis to explore the different effects of SUCs on men...
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MDPI AG
2023-04-01
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Series: | Children |
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Online Access: | https://www.mdpi.com/2227-9067/10/5/770 |
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author | Shunsen Huang Xiaoxiong Lai Yajun Li Yang Cui Yun Wang |
author_facet | Shunsen Huang Xiaoxiong Lai Yajun Li Yang Cui Yun Wang |
author_sort | Shunsen Huang |
collection | DOAJ |
description | <b>Purpose</b>: Previous studies focusing on the relationship between adolescents’ screen time and mental health have uncovered contradictory results. By focusing on smartphone use content (SUC), this study uses specification curve analysis to explore the different effects of SUCs on mental health-based on longitudinal data. <b>Methods</b>: A total of 2552 adolescents were surveyed in the first (July 2020) and second year (April 2021). A total of 2049 eligible participants (average age = 14.39 ± 2.27, female = 1062) are included in the analysis. Participants reported 20 types of content used by them during smartphone use and their mental health (depression, anxiety, and somatization). Specification curve analysis was used to examine the longitudinal relationship between SUCs and their mental health. <b>Results</b>: Smartphone use for listening to music (median β = 0.18, <i>p</i> < 0.001, NSRPD = 25/27, <i>p</i> < 0.05), chatting online (median β = 0.15, <i>p</i> < 0.001, NSRPD = 24/27, <i>p</i> < 0.05), watching TV (median β = 0.14, <i>p</i> < 0.001, NSRPD = 24/27, <i>p</i> < 0.05), and playing games (median β = 0.09, <i>p</i> < 0.001, NSRPD = 19/27, <i>p</i> < 0.05) produce high to medium negative effects on subsequent mental health. Only using smartphones for online courses exerts no effect on their subsequent mental health (median β = 0.01, <i>p</i> > 0.05, NSRPD = 0/27, <i>p</i> > 0.05). The left 15 types of smartphone content showed unstable effects on future mental health. Depending on the types of content used, these effects ranged from high, medium, and small to none. The relatively descending order of effect on mental health is listening to music, chatting online, watching TV, playing games, and types of content (e.g., browsing social media, making payments, reading online novels) with high but unstable effects, types of content with medium (e.g., browsing news and posting/sharing) but unstable effects, types of content (e.g., using the camera, obtaining life information, and making calls) with small but unstable effects, such as finishing homework and taking online courses. <b>Conclusions</b>: This study enlightens researchers and policymakers to update their understanding of adolescents’ technology use, especially to adopt a differentiated attitude towards different media use content. As nutritionists often do, a “nutritionally balanced” digital diet for young people should be recommended to the public, rather than just suggesting limits on the amount of time they can spend using digital media. |
first_indexed | 2024-03-11T03:50:34Z |
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language | English |
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publishDate | 2023-04-01 |
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spelling | doaj.art-4976ad6a6b954225b63c525f7dcea74c2023-11-18T00:54:39ZengMDPI AGChildren2227-90672023-04-0110577010.3390/children10050770Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental HealthShunsen Huang0Xiaoxiong Lai1Yajun Li2Yang Cui3Yun Wang4State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing 100875, ChinaGuangming Institute of Education Sciences, Shenzhen 518107, ChinaState Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, Beijing 100875, China<b>Purpose</b>: Previous studies focusing on the relationship between adolescents’ screen time and mental health have uncovered contradictory results. By focusing on smartphone use content (SUC), this study uses specification curve analysis to explore the different effects of SUCs on mental health-based on longitudinal data. <b>Methods</b>: A total of 2552 adolescents were surveyed in the first (July 2020) and second year (April 2021). A total of 2049 eligible participants (average age = 14.39 ± 2.27, female = 1062) are included in the analysis. Participants reported 20 types of content used by them during smartphone use and their mental health (depression, anxiety, and somatization). Specification curve analysis was used to examine the longitudinal relationship between SUCs and their mental health. <b>Results</b>: Smartphone use for listening to music (median β = 0.18, <i>p</i> < 0.001, NSRPD = 25/27, <i>p</i> < 0.05), chatting online (median β = 0.15, <i>p</i> < 0.001, NSRPD = 24/27, <i>p</i> < 0.05), watching TV (median β = 0.14, <i>p</i> < 0.001, NSRPD = 24/27, <i>p</i> < 0.05), and playing games (median β = 0.09, <i>p</i> < 0.001, NSRPD = 19/27, <i>p</i> < 0.05) produce high to medium negative effects on subsequent mental health. Only using smartphones for online courses exerts no effect on their subsequent mental health (median β = 0.01, <i>p</i> > 0.05, NSRPD = 0/27, <i>p</i> > 0.05). The left 15 types of smartphone content showed unstable effects on future mental health. Depending on the types of content used, these effects ranged from high, medium, and small to none. The relatively descending order of effect on mental health is listening to music, chatting online, watching TV, playing games, and types of content (e.g., browsing social media, making payments, reading online novels) with high but unstable effects, types of content with medium (e.g., browsing news and posting/sharing) but unstable effects, types of content (e.g., using the camera, obtaining life information, and making calls) with small but unstable effects, such as finishing homework and taking online courses. <b>Conclusions</b>: This study enlightens researchers and policymakers to update their understanding of adolescents’ technology use, especially to adopt a differentiated attitude towards different media use content. As nutritionists often do, a “nutritionally balanced” digital diet for young people should be recommended to the public, rather than just suggesting limits on the amount of time they can spend using digital media.https://www.mdpi.com/2227-9067/10/5/770smartphone use contentadolescent mental healthspecification curve analysisdepressionanxietysomatization |
spellingShingle | Shunsen Huang Xiaoxiong Lai Yajun Li Yang Cui Yun Wang Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health Children smartphone use content adolescent mental health specification curve analysis depression anxiety somatization |
title | Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health |
title_full | Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health |
title_fullStr | Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health |
title_full_unstemmed | Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health |
title_short | Beyond Screen Time: The Different Longitudinal Relations between Adolescents’ Smartphone Use Content and Their Mental Health |
title_sort | beyond screen time the different longitudinal relations between adolescents smartphone use content and their mental health |
topic | smartphone use content adolescent mental health specification curve analysis depression anxiety somatization |
url | https://www.mdpi.com/2227-9067/10/5/770 |
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