Multidimensional Internet Use, Social Participation, and Depression Among Middle-Aged and Elderly Chinese Individuals: Nationwide Cross-Sectional Study

被引:37
作者
Du, Xiwang [1 ]
Liao, Jiazhi [2 ]
Ye, Qing [2 ]
Wu, Hong [3 ,4 ]
机构
[1] Taikang Tongji Wuhan Hosp, Wuhan, Peoples R China
[2] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Wuhan, Peoples R China
[3] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Med & Hlth Management, Wuhan, Peoples R China
[4] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Med & Hlth Management, 13 Hangkong Rd, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
internet use; depression; social participation; middle-aged and elderly Chinese; RIDL; OLDER-ADULTS; MENTAL-HEALTH; TECHNOLOGY; SYMPTOMS; INFLAMMATION; LONELINESS; SUPPORT; PEOPLE; IMPACT;
D O I
10.2196/44514
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: There is growing evidence that the internet has beneficial effects on the mental health of middle-aged and older people (>= 45 years), but the evidence is inconclusive, and the underlying mechanisms are less known. Objective: This study aims to explore the relationship between multidimensional (devices, frequency, and purpose) internet use and depression in middle-aged and elderly Chinese, as well as the mediating effect of social participation. Moreover, this study will explore the moderating effect of the regional informatization development level (RIDL) on the relationships between individual internet use, social participation, and depression. Methods: Data on 17,676 participants aged 45 years or older were obtained from the China Health and Retirement Longitudinal Study (CHARLS) 2018 data set. The 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) was used to identify the presence of depression. Logistic regression was used to explore the relationship between each dimension of internet use and depression. Multiple linear regression was used to explore the mediating effect of social participation and the moderating effect of the RIDL. Results: The results showed that 28.33% (5008/17,676) of the total population had depression. In terms of regional subgroups, respondents living in the western region exhibited the highest proportion of depression (2041/5884, 34.69%). Internet use was negatively associated with depression (odds ratio 0.613, 95% CI 0.542-0.692; P<.001). Various dimensions of internet use positively contributed to individual social participation and reduced individual depression (devices: beta=-.170, 95% CI -0.209 to -0.127; frequency: beta=-.065, 95% CI -0.081 to -0.047; and purpose: beta=-.043, 95% CI -0.053 to -0.031). In addition, the RIDL weakened the relationship between individual-level internet use and social participation (internet use: F-74.12,F-9.82=7.55, P<.001; devices: F-51.65/9.88=5.23, P=.005; frequency: F-66.74/10.08=6.62, P=.001; and purpose: F-66.52/9.78=6.80, P=.001), and negatively moderated the relationship between the frequency of internet use and depression (frequency: F-662.67/188.79=3.51,P=.03). Conclusions: This study found that different dimensions of internet use are associated with lower levels of depression. Social participation partially mediates the association between multidimensional internet use and depression in the eastern, central, and western regions, respectively. Additionally, the RIDL helps individuals further their internet use and social participation, reducing the impact of depression. However, this effect weakens sequentially from the western region to the central region and then to the eastern region.
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页数:19
相关论文
共 88 条
[51]   Reforming mental health in China and India [J].
Liu, Shiwei ;
Page, Andrew .
LANCET, 2016, 388 (10042) :314-316
[52]   Prevalence of depressive disorders and treatment in China: a cross-sectional epidemiological study [J].
Lu, Jin ;
Xu, Xiufeng ;
Huang, Yueqin ;
Li, Tao ;
Ma, Chao ;
Xu, Guangming ;
Yin, Huifang ;
Xu, Xiangdong ;
Ma, Yanjuan ;
Wang, Limin ;
Huang, Zhengjing ;
Yan, Yongping ;
Wang, Bo ;
Xiao, Shuiyuan ;
Zhou, Liang ;
Li, Lingjiang ;
Zhang, Yan ;
Chen, Hongguang ;
Zhang, TingTing ;
Yan, Jie ;
Ding, Hua ;
Yu, Yaqin ;
Kou, Changgui ;
Shen, Zonglin ;
Jiang, Linling ;
Wang, Zhizhong ;
Sun, Xian ;
Xu, Yifeng ;
He, Yanling ;
Guo, Wanjun ;
Jiang, Lijun ;
Li, Shengyan ;
Pan, Wen ;
Wu, Yue ;
Li, Guohua ;
Jia, Fujun ;
Shi, Jianfei ;
Shen, Zhongxia ;
Zhang, Ning .
LANCET PSYCHIATRY, 2021, 8 (11) :981-990
[53]   Depression [J].
Malhi, Gin S. ;
Mann, J. John .
LANCET, 2018, 392 (10161) :2299-2312
[54]  
Matthews K., 2015, Understanding digital engagement in later life
[55]   Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study [J].
Mc Dowell, Cillian P. ;
Carlin, Angela ;
Capranica, Laura ;
Dillon, Christina ;
Harrington, Janas M. ;
Lakerveld, Jeroen ;
Loyen, Anne ;
Ling, Fiona Chun Man ;
Brug, Johannes ;
MacDonncha, Ciaran ;
Herring, Matthew P. .
BMC PUBLIC HEALTH, 2018, 18
[56]   Clinical Usefulness of Therapeutic Neuromodulation for Major Depression A Systematic Meta-Review of Recent Meta-Analyses [J].
McGirr, Alexander ;
Berlim, Marcelo T. .
PSYCHIATRIC CLINICS OF NORTH AMERICA, 2018, 41 (03) :485-+
[57]   The role of inflammation in depression: from evolutionary imperative to modern treatment target [J].
Miller, Andrew H. ;
Raison, Charles L. .
NATURE REVIEWS IMMUNOLOGY, 2016, 16 (01) :22-34
[58]  
National Bureau of Statistics of China, About us
[59]  
Nie NormanH., 2002, IT SOC, V1, P1, DOI DOI 10.1002/9780470774298.CH7
[60]   Health literacy as a social vaccine in the COVID-19 pandemic [J].
Okan, Orkan ;
Messer, Melanie ;
Levin-Zamir, Diane ;
Paakkari, Leena ;
Sorensen, Kristine .
HEALTH PROMOTION INTERNATIONAL, 2023, 38 (04)