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Screen time and depression risk: A meta-analysis of cohort studies
BACKGROUND: The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. METH...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815119/ https://www.ncbi.nlm.nih.gov/pubmed/36620668 http://dx.doi.org/10.3389/fpsyt.2022.1058572 |
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author | Li, Liqing Zhang, Qi Zhu, Liyong Zeng, Guohua Huang, Hongwei Zhuge, Jian Kuang, Xiaorui Yang, Sule Yang, Di Chen, Zhensheng Gan, Yong Lu, Zuxun Wu, Chunmei |
author_facet | Li, Liqing Zhang, Qi Zhu, Liyong Zeng, Guohua Huang, Hongwei Zhuge, Jian Kuang, Xiaorui Yang, Sule Yang, Di Chen, Zhensheng Gan, Yong Lu, Zuxun Wu, Chunmei |
author_sort | Li, Liqing |
collection | PubMed |
description | BACKGROUND: The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. METHODS: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I(2) statistic. Potential publication bias was evaluated using a funnel plot and Begg’s and Egger’s tests. RESULTS: The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05–1.14), with significant heterogeneity (I(2) = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found. CONCLUSION: This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant’s age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression. |
format | Online Article Text |
id | pubmed-9815119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98151192023-01-06 Screen time and depression risk: A meta-analysis of cohort studies Li, Liqing Zhang, Qi Zhu, Liyong Zeng, Guohua Huang, Hongwei Zhuge, Jian Kuang, Xiaorui Yang, Sule Yang, Di Chen, Zhensheng Gan, Yong Lu, Zuxun Wu, Chunmei Front Psychiatry Psychiatry BACKGROUND: The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. METHODS: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I(2) statistic. Potential publication bias was evaluated using a funnel plot and Begg’s and Egger’s tests. RESULTS: The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05–1.14), with significant heterogeneity (I(2) = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found. CONCLUSION: This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant’s age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression. Frontiers Media S.A. 2022-12-22 /pmc/articles/PMC9815119/ /pubmed/36620668 http://dx.doi.org/10.3389/fpsyt.2022.1058572 Text en Copyright © 2022 Li, Zhang, Zhu, Zeng, Huang, Zhuge, Kuang, Yang, Yang, Chen, Gan, Lu and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Li, Liqing Zhang, Qi Zhu, Liyong Zeng, Guohua Huang, Hongwei Zhuge, Jian Kuang, Xiaorui Yang, Sule Yang, Di Chen, Zhensheng Gan, Yong Lu, Zuxun Wu, Chunmei Screen time and depression risk: A meta-analysis of cohort studies |
title | Screen time and depression risk: A meta-analysis of cohort studies |
title_full | Screen time and depression risk: A meta-analysis of cohort studies |
title_fullStr | Screen time and depression risk: A meta-analysis of cohort studies |
title_full_unstemmed | Screen time and depression risk: A meta-analysis of cohort studies |
title_short | Screen time and depression risk: A meta-analysis of cohort studies |
title_sort | screen time and depression risk: a meta-analysis of cohort studies |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815119/ https://www.ncbi.nlm.nih.gov/pubmed/36620668 http://dx.doi.org/10.3389/fpsyt.2022.1058572 |
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