Top

Published in:

Open Access 01-12-2022 | Mood Disorders | Research

A study on the impact of Internet use on depression among Chinese older people under the perspective of social participation

Authors: Hua-lei Yang, Shuo Zhang, Si-meng Cheng, Zhi-yun Li, Yuan-yang Wu, Si-qing Zhang, Jia-hao Wang, Yi-wen Tao, Yi-dan Yao, Lin Xie, Wen-jing Xiao, Xiao-qing Tang, Jing Wu, Zheng Shen, Li-li Tang

Published in: BMC Geriatrics | Issue 1/2022

Abstract

Purpose

This study aimed to evaluate the role of social participation in the relationship between internet use and depressive symptoms among Chinese older adults and investigate how the internet use interact with social participation to reduce the risk of depressive symptoms.

Methods

Based on the survey from the China Health and Retirement Longitudinal Study (CHARLS) in 2018, we identified 4645 subjects and used the Ordinary Least Square method (OLS) and Propensity Score Matching method (PSM) to identify the association between Internet use and depression of older people, and further test how social participation played a role in the relationship.

Results

The level of depression of older people was significantly reduced in those who using internet in China, and the effect was still robust under different identification methods. The mental health was improved when using internet because of the increase of social participation and social capital. Further, The positive effect was stronger especially in those who were female, living in rural areas, has low education attainments and were 70–79 years old.

Conclusions

The popularity of internet use has a positive effect on the depressive symptoms of Chinese older adults. Effective measures were encouraged to improve the friendliness of internet for older people and promote the popularization of the Internet and older group, achieving the spiritual well-being of them in the Internet society.

Specifically, in the survey, respondents reported whether they had participated in the following social activities in the past month: (a) visiting and communicating with friends; (b) playing mahjong, chess and cards, going to community activity rooms and other recreational activities; (c) provide help to relatives, friends or neighbors who do not live with you; (d) dancing, fitness and qigong exercises; (e) participate in community organization activities; (f) volunteer activities or charitable activities; (g) take care of patients or persons with disabilities who do not live with you; (h) go to school or attend training courses.

Standardization method: individual value minus mean and then divided by standard deviation.

Almedom AM. Social capital and mental health: an interdisciplinary review of primary evidence. Soc Sci Med. 2005;61(5):943–64. https://doi.org/10.1016/j.socscimed.2004.12.025.CrossRefPubMed

Alves de Rezende CH, Coelho LM, Oliveira LM, Penha Silva N. Dependence of the geriatric depression scores on age, nutritional status, and haematologic variables in elderly institutionalized patients. J Nutr Health Aging. 2009;13:617–21.

Bauernschuster S, Falck O, Woessmann L. Surfing alone? The internet and social capital: evidence from an unforeseeable technological mistake. J Public Econ. 2014;117(sep.):73–89. https://doi.org/10.1016/j.jpubeco.2014.05.007.

Borda M, Grishchenko N, Kowalczyk-Rólczyńska P. Impact of digital inequality on the COVID-19 pandemic: Evidence from European Union countries. Sustainability. 2022;14(5):2850.CrossRef

Bots S, Tijhuis M, Giampaoli S, Kromhout D, Nissinen A. Lifestyle- and diet-related factors in late-life depression: a 5-year follow-up of elderly European men: the FINE study. Int J Geriatr Psychiatry. 2008;23(5):478–84.CrossRef

Cassidy K, Kotynia-English R, Acres J, et al. Association between lifestyle factors and mental health measures among community-dwelling older women. Aust N Z J Psychiatry. 2004;38:940–7.CrossRef

Chen G, Li S. How can government make people happy? --- an empirical study of the impact of government quality on residents' happiness. J Manag World. 2012;08:55–67. https://doi.org/10.19744/j.cnki.11-1235/f.2012.08.006.

Chen QH, Lin H, Lv ZW. Does village democracy increase happiness? Evidence from rural China. China Econ Q. 2014;13(02):723–44. https://doi.org/10.13821/j.cnki.ceq.2014.02.005.

China Internet Network Information Center. The 46th China statistical report on internet development. 2020; http://www.cac.gov.cn/2020-09/29/c_1602939918747816.htm.

10.

Choi E, Han KM, Chang J, Lee YJ, Ham BJ. Social participation and depressive symptoms in community-dwelling older adults: emotional social support as a mediator. J Psychiatr Res. 2021;137:589–96. https://doi.org/10.1016/j.jpsychires.2020.10.043.

11.

Choi M, Kong S, Jung D. Computer and internet interventions for loneliness and depression in older adults: a meta-analysis. Healthcare Inform Res. 2012;18(3):191–8. https://doi.org/10.4258/hir.2012.18.3.191.CrossRef

12.

Choi NG, Dinitto DM. Internet use among older adults: association with health needs, psychological capital, and social capital. J Med Internet Res. 2013;15(5).

13.

Coll-Planas L, Gómez GDV, Bonilla P, Masat T, Monteserin R. Promoting social capital to alleviate loneliness and improve health among older people in Spain. Health Soc Care Community. 2017;25(1):145. https://doi.org/10.1111/hsc.12284.CrossRefPubMed

14.

Cotten SR, Ford G, Ford S, Hale TM. Internet use and depression among retired older adults in the United States:a longitudinal analysis. J Gerontol Ser B Psychol Sci Soc Sci. 2014;69(5):763–71. https://doi.org/10.1093/geronb/gbu018.CrossRef

15.

Croezen S, Avendano M, Burdorf A, van Lenthe FJ. Social participation and depression in old age: a fixed-effects analysis in 10 European countries. Am J Epidemiol. 2015;182(2):168–76. https://doi.org/10.1093/aje/kwv015.CrossRefPubMedPubMedCentral

16.

Dolan P, Peasgood T, White M. Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. J Econ Psychol. 2008;29(1):94–122.CrossRef

17.

Dorn D, Fischer JAV, Kirchgassner J, Sousa-Poza A. Is it culture or democracy? The impact of democracy and culture on happiness. Soc Indic Res. 2007;82(3):505–26.CrossRef

18.

Du P, Wang B. How does internet use affect life satisfaction of the Chinese elderly? Popul Res. 2020;44(04):3–17.

19.

Glanville JL, Story WT. Social capital and self-rated health: clarifying the role of trust. Soc Sci Res. 2018;71:98–108.CrossRef

20.

Guo QJ, Bai X, Feng N. Social participation and depressive symptoms among Chinese older adults: do rural-urban differences exist? J Affect Disord. 2018; 239:124–30. https://doi.org/10.1016/j.jad.2018.06.036.

21.

Hage E, Wortmann H, van Offenbeek M, Boonstra A. The dual impact of online communication on older Adults’Social connectivity. Inf Technol People. 2016;29(1):31–50. https://doi.org/10.1108/ITP-09-2014-0216.CrossRef

22.

Hakkarainen R, Partonen T, Haukka J, et al. Food and nutrient intake in relation to mental wellbeing. Nutr J. 2004;3:14. https://doi.org/10.1186/1475-2891-3-14.

23.

Hao G, Bishwajit G, Tang S, Nie C, Ji L, Huang R. Social participation and perceived depression among elderly population in South Africa. Clin Interv Aging. 2017;12:971–6. https://doi.org/10.2147/CIA.S137993.CrossRefPubMedPubMedCentral

24.

Hayes M, van Stolk-Cooke K, Muench F. Understanding Facebook use and the psychological affects of use across generations. Comput Hum Behav. 2015;49:507–11 https://www.sciencedirect.com/science/article/pii/S0747563215002307?via%3Dihub.

25.

Haynes JC, Farrell M, Singleton N, et al. Alcohol consumption as a risk factor for anxiety and depression: results from the longitudinal follow-up of the National Psychiatric Morbidity Survey. Br J Psychiatry. 2005;187:544–51.CrossRef

26.

Hikichi H, Tsuboya T, Aida J, Matsuyama Y, Kondo K, Subramanian SV, et al. Social capital and cognitive decline in the aftermath of a natural disaster: a natural experiment from the 2011 great East Japan earthquake and tsunami. Lancet Planet Health. 2017;1:e105-13. https://doi.org/10.1016/S2542-5196(17)30041-4.CrossRefPubMedPubMedCentral

27.

Jin YA, Liu WL, Zhao MH, Wang DH, Hu WB. Short video APP use and the life of mid-age and older adults: an exploratory study based on a social survey. Population Research. 2021;45(03):31–45.

28.

Kraut R, Burke M. Internet use and psychological well-being: effects of activity and audience. Commun ACM. 2015;58(12):94–100. https://doi.org/10.1145/2739043.CrossRef

29.

Kraut R, Patterson M, Lundmark V, Kiesler S, Scherlis W. Internet paradox: a social technology that reduces social involvement and psychological well-being? Am Psychol. 1998;53(9):1017–31. https://doi.org/10.1037//0003-066X.53.9.1017.CrossRefPubMed

30.

Lapid MI, Rummans TA. Evaluation and management of geriatric depression in primary care. Mayo Clin Proc. 2003;78:1423–9.CrossRef

31.

LaRose R, Mastro D, Eastin MS. Understanding internet usage: a social-cognitive approach to uses and gratifications. Social ence Comput Rev. 2001;19:395–413. https://doi.org/10.1177/089443930101900401.CrossRef

32.

Lei X, Sun X, Strauss JS, Zhang P, Zhao Y. Depressive symptoms and SES among the mid-aged and elderly in China: evidence from the China health and retirement longitudinal study national baseline. Soc Sci Med. 2014;120:224–32. https://doi.org/10.1016/j.socscimed.2014.09.028.CrossRefPubMedPubMedCentral

33.

Li D, Zhang DL, Shao JJ, Qi XD, Tian L. A meta-analysis of the prevalence of depressive symptoms in Chinese older adults. Arch Gerontol Geriatr. 2014;58(1):1–9. https://doi.org/10.1016/j.archger.2013.07.016.CrossRefPubMed

34.

Liao S, Zhou Y, Liu Y, Wang R. Variety, frequency, and type of internet use and its association with risk of depression in middle- and older-aged Chinese: a cross-sectional study. J Affect Disord. 2020;273:280–90 https://doi.org/10.1016/j.jad.2020.04.022.

35.

Lipton RI. The effect of moderate alcohol use on the relationship between stress and depression. Am J Public Health. 1994;84:1913–7.CrossRef

36.

Liu H, Fang B, Chan J, Lou VW. Continued social participation protects against depressive symptoms across the retirement transition: longitudinal evidence from three waves of the China health and retirement longitudinal survey. Geriatr Gerontol Int. 2019;19(10):972–76. https://doi.org/10.1111/ggi.13752.

37.

Liu Q, Pan HM, Wu YY. Migration status, internet use, and social participation among middle-aged and older adults in China: consequences for depression. Int J Environ Res Public Health. 2020;17(16):6007. https://doi.org/10.3390/ijerph17166007.CrossRefPubMedCentral

38.

Lopresti AL, Hood SD, Drummond PD. A review of lifestyle factors that contribute to important pathways associated with major depression: diet, sleep and exercise. J Affect Disord. 2013;148(1):12–27.CrossRef

39.

Lu YP, Wang JP. Digital or information welfare: the effect of internet use on individual subjective well-being in China. Econ Perspect. 2020;02:59–73.

40.

Lyu S, Sun J. Internet use and self-rated health among Chinese older adults: the mediating role of social capital. Geriatr Gerontol Int. 2021;21:34–8. https://doi.org/10.1111/ggi.14090.CrossRefPubMed

41.

Mamplekou E, Bountziouka V, Psaltopoulou T, et al. Urban environment, physical inactivity and unhealthy dietary habits correlate to depression among elderly living in eastern Mediterranean islands: the MEDIS (MEDiterranean ISlands elderly) study. J Nutr Health Aging. 2010;14(6):449–55.CrossRef

42.

Miller WC, Anton HA, Townson A. Measurement properties of the CES-D scale among individuals with spinal cord injury. Spinal Cord. 2008;46(4):287–92. https://doi.org/10.1038/sj.sc.3102127.CrossRefPubMed

43.

National Bureau of statistics. Main data of the seventh National Census; 2021. http://www.stats.gov.cn/tjsj/zxfb/202105/t20210510_1817176.html

44.

Neves BB, Franz RL, Munteanu C, Baecker R. Inf Commun Soc. 2018;21(11–12):1681–99. https://doi.org/10.1080/1369118X.2017.1348534.

45.

Nie P, Sousa-Poza A, Nimrod G. Internet use and subjective well-being in China. Soc Indic Res. 2017;132(1):489–516. https://doi.org/10.1007/s11205-015-1227-8.CrossRef

46.

Pénard T, Poussing N. Internet use and social capital: the strength of virtual ties. J Econ Issue. 2010;3:569–95.CrossRef

47.

Peng XZ, Lv MY, Lu MH. Does internet use make older people happier?:empirical research from CGSS. Nanjing J Soc Sci. 2019;10:57–68.

48.

Radloff LS. The CES-D scale: a self report depression scale for research in the general. Appl Psych Meas. 1977;1:385–401.CrossRef

49.

Segel-Karpas D, Ayalon L, Lachman ME. Loneliness and depressive symptoms: the moderating role of the transition into retirement. Aging Ment Health. 2016;22:135–40. https://doi.org/10.1080/13607863.2016.1226770.CrossRefPubMed

50.

Shaw LH, Gant LM. In defense of the internet:the relationship between internet communication and depression, loneliness, self-esteem, and perceived social support. CyberPsychol Behav. 2002;5(2):157–71. https://doi.org/10.1089/109493102753770552.CrossRefPubMed

51.

Shen K, Zhang B, Feng Q. Association between tea consumption and depressive symptom among Chinese older adults. BMC Geriatr. 2019;19:1–8.CrossRef

52.

Sims T, Reed AE, Carr DC. Information and communication technology use is related to higher well-being among the oldest-old. J Gerontol Ser B Psychol Sci Soc Sci. 2017;72(5):761–70 https://www.ncbi. nlm.nih.gov/pubmed/27702839.

53.

Song Y, Qian C, Pickard S. Age-related digital divide during the COVID-19 pandemic in China. Int J Environ Res Public Health. 2021;18(21):11285.CrossRef

54.

Stadelmann SI, Vatter A. Does satisfaction with democracy really increase happiness? Direct democracy and individual satisfaction in Switzerland. Polit Behav. 2012;34(3):535–59.CrossRef

55.

Wang R, Chen Z, Zhou Y, Shen L, Zhang Z, Wu X. Melancholy or mahjong? Diversity, frequency, type, and rural-urban divide of social participation and depression in middle- and old-aged Chinese: a fixed-effects analysis. Soc Sci Med. 2019a;238:112518. https://doi.org/10.1016/j.socscimed.2019.112518.

56.

Wang Y, Zhang H, Feng T, Wang H. Does internet use affect levels of depression among older adults in China? A propensity score matching approach. BMC Public Health. 2019b;19(1). https://doi.org/10.1186/s12889-019-7832-8.

57.

Welsch H. Environment and happiness: valuation of air pollution using life satisfaction data. Ecol Econ. 2006;58(4):801–13.CrossRef

58.

Wen ZL, Zhang L, Hou JT, Liu HY. Testing and application of the mediating effects. Acta Psychol Sin. 2004;05:614–20.

59.

White H, McConnell E, Clipp E, Branch LG, Sloane R, Pieper C, et al. A randomized controlled trial of the psychosocial impact of providing internet training and access to older adults. Aging Ment Health. 2002;6:213–21. https://doi.org/10.1080/13607860220142422.CrossRefPubMed

60.

Wind TR. Social capital interventions in public health: moving towards why social capital matters for health. Br J Soc Med. 2019;73(9):793–5. https://doi.org/10.1136/jech-2018-211576.CrossRef

61.

Wong CK, Yeung DY, Ho HC, Tse KP, Lam CY. Chinese older adults’ internet use for health information. Appl Gerontol Official. 2014;33(3):316–35.CrossRef

62.

World Health Organization. Depression and other common mental disorders:Global Health estimates; 2017.

63.

Yan A, Zou Y, Mirchandani DA. How hospitals in mainland China responded to the outbreak of COVID-19 using information technology–enabled services: an analysis of hospital news webpages. J Am Med Inf Assoc. 2020;27:991–9.CrossRef

64.

Yang D. The legal regulation of internet finance : a perspective based on information tools. Soc Sci China. 2015;(4):107–26+206.

65.

Yang HL, Zhang S, Zhang SQ, et al. Internet Use and Depressive Symptoms Among Older Adults in China. Front Psychiatry. 2021;12:739085. https://doi.org/10.3389/fpsyt.2021.739085.

66.

Yuan H. Internet use and mental health problems among older people in Shanghai, China: the moderating roles of chronic diseases and household income. Aging Ment Health. 2021;25(4):657–63. https://doi.org/10.1080/13607863.2020.1711858.CrossRefPubMed

67.

Zhao JG, Liu ZQ. The impact of internet use on the health of the elderly. Chinese journal of population Science. 2020;05:126.

68.

Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China health and retirement longitudinal study (CHARLS). Int J Epidemiol. 2014;43(1):61–8. https://doi.org/10.1093/ije/dys203.CrossRefPubMed

69.

Zhu YM, Zhou YF, Long CH, Yi CZ. The relationship between internet use and health among older adults in China: the mediating role of social capital. Healthcare. 2021;9(5):559. https://doi.org/10.3390/healthcare9050559.CrossRefPubMedPubMedCentral

Title: A study on the impact of Internet use on depression among Chinese older people under the perspective of social participation
Authors: Hua-lei Yang
Shuo Zhang
Si-meng Cheng
Zhi-yun Li
Yuan-yang Wu
Si-qing Zhang
Jia-hao Wang
Yi-wen Tao
Yi-dan Yao
Lin Xie
Wen-jing Xiao
Xiao-qing Tang
Jing Wu
Zheng Shen
Li-li Tang
Publication date: 01-12-2022
Publisher: BioMed Central
Keywords: Mood Disorders
Affective Disorder
Published in: BMC Geriatrics / Issue 1/2022
Electronic ISSN: 1471-2318
DOI: https://doi.org/10.1186/s12877-022-03359-y

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2022

Trochanteric fracture pattern is associated with increased risk for nonunion independent of open or closed reduction technique

Optimising diagnosis and post-diagnostic support for people living with dementia: geriatricians’ views

Barriers and enablers for older adults participating in a home-based pragmatic exercise program delivered and monitored by Amazon Alexa: a qualitative study

Coding quality of deaths and its impact on elderly unintentional fall mortality data from 1990 to 2019: a retrospective analysis of the WHO Mortality Database

Factors associated with older persons’ perceptions of dignity and well-being over a three-year period. A retrospective national study in residential care facilities

Association between low back pain and functional disability in the elderly people: a 4-year longitudinal study after the great East Japan earthquake

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

At a glance: The STEP trials