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Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey

BACKGROUND: Although social networking services (SNSs) have become popular among young people, problematic SNS use has also increased. However, little is known about SNS addiction and its association with SNS use patterns and mental health status. OBJECTIVE: This study aims to test the mediating rol...

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Autores principales: Wang, Tingxuan, Wong, Janet Y H, Wang, Man Ping, Li, Amanda Chiu Yin, Kim, Sang Suk, Lee, Jung Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701716/
https://www.ncbi.nlm.nih.gov/pubmed/34889760
http://dx.doi.org/10.2196/26733
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author Wang, Tingxuan
Wong, Janet Y H
Wang, Man Ping
Li, Amanda Chiu Yin
Kim, Sang Suk
Lee, Jung Jae
author_facet Wang, Tingxuan
Wong, Janet Y H
Wang, Man Ping
Li, Amanda Chiu Yin
Kim, Sang Suk
Lee, Jung Jae
author_sort Wang, Tingxuan
collection PubMed
description BACKGROUND: Although social networking services (SNSs) have become popular among young people, problematic SNS use has also increased. However, little is known about SNS addiction and its association with SNS use patterns and mental health status. OBJECTIVE: This study aims to test the mediating role of SNS addiction between SNS use patterns and mental health status among Chinese university students in Hong Kong (HK). METHODS: An online cross-sectional survey was conducted using a convenience sampling method. In total, 533 university students (323 [66.9%] female, mean age [SD]=20.87 [2.68] years) were recruited from February to March 2019. Multiple linear regression was used to assess the association between SNS use and SNS addiction. Structural equation modeling (SEM) was performed to examine the pathways and associations among SNS use, SNS addiction, psychosocial status, and mental health status (including anxiety and depressive symptoms). RESULTS: A longer time spent on SNSs per day (>3 h), a longer time spent on each SNS access (≥31 min), a higher frequency of SNS access (≤every 30 min), a longer duration of SNS use before sleeping (≥61 min), and a shorter duration from waking to first SNS use (≤5 min) were significantly associated with a higher level of SNS addiction (adjusted beta [aβ]=6.03, 95% CI 4.66-7.40; aβ=4.99, 95% CI 3.14-6.83; aβ=5.89, 95% CI 4.14-7.64; aβ=5.92, 95% CI 4.19-7.65; and aβ=3.27, 95% CI 1.73-4.82, respectively). SEM showed a significant mediating effect of SNS addiction in the relationship between SNS use and psychosocial status, and mental health status, including an indirect effect (β=0.63, 95% CI 0.37-0.93) and the total effect (β=0.44, 95% CI 0.19-0.72), while the direct effect was insignificant (β=–0.19, 95% CI –0.49 to 0.08). CONCLUSIONS: SNS use patterns were associated with SNS addiction, and SNS addiction mediated the associations between SNS use, psychosocial status, and mental health status of Chinese university students in HK. The findings suggest that screening for and addressing excessive SNS use are needed to prevent SNS addiction and mental distress among young people.
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spelling pubmed-87017162022-01-10 Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey Wang, Tingxuan Wong, Janet Y H Wang, Man Ping Li, Amanda Chiu Yin Kim, Sang Suk Lee, Jung Jae J Med Internet Res Original Paper BACKGROUND: Although social networking services (SNSs) have become popular among young people, problematic SNS use has also increased. However, little is known about SNS addiction and its association with SNS use patterns and mental health status. OBJECTIVE: This study aims to test the mediating role of SNS addiction between SNS use patterns and mental health status among Chinese university students in Hong Kong (HK). METHODS: An online cross-sectional survey was conducted using a convenience sampling method. In total, 533 university students (323 [66.9%] female, mean age [SD]=20.87 [2.68] years) were recruited from February to March 2019. Multiple linear regression was used to assess the association between SNS use and SNS addiction. Structural equation modeling (SEM) was performed to examine the pathways and associations among SNS use, SNS addiction, psychosocial status, and mental health status (including anxiety and depressive symptoms). RESULTS: A longer time spent on SNSs per day (>3 h), a longer time spent on each SNS access (≥31 min), a higher frequency of SNS access (≤every 30 min), a longer duration of SNS use before sleeping (≥61 min), and a shorter duration from waking to first SNS use (≤5 min) were significantly associated with a higher level of SNS addiction (adjusted beta [aβ]=6.03, 95% CI 4.66-7.40; aβ=4.99, 95% CI 3.14-6.83; aβ=5.89, 95% CI 4.14-7.64; aβ=5.92, 95% CI 4.19-7.65; and aβ=3.27, 95% CI 1.73-4.82, respectively). SEM showed a significant mediating effect of SNS addiction in the relationship between SNS use and psychosocial status, and mental health status, including an indirect effect (β=0.63, 95% CI 0.37-0.93) and the total effect (β=0.44, 95% CI 0.19-0.72), while the direct effect was insignificant (β=–0.19, 95% CI –0.49 to 0.08). CONCLUSIONS: SNS use patterns were associated with SNS addiction, and SNS addiction mediated the associations between SNS use, psychosocial status, and mental health status of Chinese university students in HK. The findings suggest that screening for and addressing excessive SNS use are needed to prevent SNS addiction and mental distress among young people. JMIR Publications 2021-12-08 /pmc/articles/PMC8701716/ /pubmed/34889760 http://dx.doi.org/10.2196/26733 Text en ©Tingxuan Wang, Janet Y H Wong, Man Ping Wang, Amanda Chiu Yin Li, Sang Suk Kim, Jung Jae Lee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.12.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Wang, Tingxuan
Wong, Janet Y H
Wang, Man Ping
Li, Amanda Chiu Yin
Kim, Sang Suk
Lee, Jung Jae
Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title_full Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title_fullStr Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title_full_unstemmed Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title_short Effects of Social Networking Service (SNS) Addiction on Mental Health Status in Chinese University Students: Structural Equation Modeling Approach Using a Cross-sectional Online Survey
title_sort effects of social networking service (sns) addiction on mental health status in chinese university students: structural equation modeling approach using a cross-sectional online survey
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701716/
https://www.ncbi.nlm.nih.gov/pubmed/34889760
http://dx.doi.org/10.2196/26733
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