United Nations Department of Economic and Social Affairs, Population Division. World Population Prospects 2022: Summary of Results. Available online:https://www.un.org/development/desa/pd/content/World-Population-Prospects-2022.

Rong J, Cheng P, Li D, et al. Global, regional, and National Temporal trends in prevalence for depressive disorders in older adults, 1990–2019: an age-period-cohort analysis based on the global burden of disease study 2019 [J]. Ageing Res Rev. 2024;100:102443. https://doi.org/10.1016/j.arr.2024.102443.


Google Scholar
 

Wu Y, Cornally N, O’Donovan A, et al. Prevalence and factors associated with depression and depressive symptoms among Chinese older persons: an integrative review [J]. Int J Ment Health Nurs. 2025;34(1):e13484. https://doi.org/10.1111/inm.13484.


Google Scholar
 

Surkalim DL, Luo M, Eres R, et al. The prevalence of loneliness across 113 countries: systematic review and meta-analysis [J]. BMJ. 2022;376:e067068. https://doi.org/10.1136/bmj-2021-067068.


Google Scholar
 

Li W, Liu E, Balezentis T, et al. Association between socioeconomic welfare and depression among older adults: evidence from the China health and retirement longitudinal study [J]. Soc Sci Med. 2021;275:113814. https://doi.org/10.1016/j.socscimed.2021.113814.


Google Scholar
 

Cai H, Jin Y, Liu R, et al. Global prevalence of depression in older adults: A systematic review and meta-analysis of epidemiological surveys [J]. Asian J Psychiatr. 2023;80:103417. https://doi.org/10.1016/j.ajp.2022.103417.


Google Scholar
 

McHugh Power JE, Steptoe A, Kee F, et al. Loneliness and social engagement in older adults: A bivariate dual change score analysis [J]. Psychol Aging. 2019;34(1):152–62. https://doi.org/10.1037/pag0000287.


Google Scholar
 

Houben N, Janssen EPCJ, Hendriks MRC, et al. Physical health status of older adults with severe mental illness: the PHiSMI-E cohort study [J]. Int J Ment Health Nurs. 2019;28(2):457–67. https://doi.org/10.1111/inm.12547.


Google Scholar
 

Holst H, Ozolins L-L, Enros J, et al. Life situation of older people living with severe mental illness – A scoping review [J]. Int J Ment Health Nurs. 2024;33(4):739–49. https://doi.org/10.1111/inm.13288.


Google Scholar
 

GSMA. The State of Mobile Internet Connectivity. 2023.Available from: https://www.gsma.com/r/wp-content/uploads/2023/10/The-State-of-Mobile-Internet-Connectivity-Report-2023.pdf

Liang X, Xiong F, Xie F. The effect of smartphones on the self-rated health levels of the elderly [J]. BMC Public Health. 2022;22(1):508. https://doi.org/10.1186/s12889-022-12952-0.


Google Scholar
 

Fang Y, Chau AKC, Wong A, et al. Information and communicative technology use enhances psychological well-being of older adults: the roles of age, social connectedness, and frailty status [J]. Aging Ment Health. 2018;22(11):1516–24. https://doi.org/10.1080/13607863.2017.1358354.


Google Scholar
 

Wu H, Ba N, Ren S, et al. The impact of internet development on the health of Chinese residents: transmission mechanisms and empirical tests [J]. Socio-Economic Plann Sci. 2022;81:101178. https://doi.org/10.1016/j.seps.2021.101178.


Google Scholar
 

Noone C, McSharry J, Smalle M et al. Video calls for reducing social isolation and loneliness in older people: a rapid review [J]. Cochrane Database Syst Rev, 2020, 5(5): Cd013632. https://doi.org/10.1002/14651858.Cd013632

Minagawa Y, Saito Y. An analysis of the impact of cell phone use on depressive symptoms among Japanese elders [J]. Gerontology. 2014;60(6):539–47. https://doi.org/10.1159/000363059.


Google Scholar
 

Lin L, Jing XC, Lv SJ, et al. Mobile device use and the cognitive function and depressive symptoms of older adults living in residential care homes [J]. BMC Geriatr. 2020;20(1):41. https://doi.org/10.1186/s12877-020-1427-1.


Google Scholar
 

Bonoto BC, de Araújo VE, Godói IP, et al. Efficacy of mobile apps to support the care of patients with diabetes mellitus: A systematic review and Meta-Analysis of randomized controlled trials [J]. JMIR Mhealth Uhealth. 2017;5(3):e4. https://doi.org/10.2196/mhealth.6309.


Google Scholar
 

Sagong H, Yoon JY. The effects of smartphone use on life satisfaction in older adults: the mediating role of depressive symptoms [J]. Comput Inf Nurs. 2022;40(8):523–30. https://doi.org/10.1097/cin.0000000000000867.


Google Scholar
 

Tsai H-H, Cheng C-Y, Shieh W-Y, et al. Effects of a smartphone-based videoconferencing program for older nursing home residents on depression, loneliness, and quality of life: a quasi-experimental study [J]. BMC Geriatr. 2020;20(1). https://doi.org/10.1186/s12877-020-1426-2.

Liu H, Ma Y, Lin L, et al. Association between activities of daily living and depressive symptoms among older adults in china: evidence from the CHARLS [J]. Front Public Health. 2023;11:1249208. https://doi.org/10.3389/fpubh.2023.1249208.


Google Scholar
 

Chen H, Mui AC. Factorial validity of the center for epidemiologic studies depression scale short form in older population in China [J]. Int Psychogeriatr. 2014;26(1):49–57. https://doi.org/10.1017/s1041610213001701.


Google Scholar
 

Qingbo H, Xiaohua W, Gong C. Reliability and validity of 10-item CES-D among middle aged and older adults in China [J]. China J Health Psychol. 2015. https://doi.org/10.13342/j.cnki.cjhp.2015.07.023.


Google Scholar
 

Du X, Li X, Qian P, et al. Indoor air pollution from solid fuels use, inflammation, depression and cognitive function in middle-aged and older Chinese adults [J]. J Affect Disord. 2022;319:370–6. https://doi.org/10.1016/j.jad.2022.09.103.


Google Scholar
 

Wang R, Chen Z, Zhou Y, et al. 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 [J]. Soc Sci Med. 2019;238:112518. https://doi.org/10.1016/j.socscimed.2019.112518.


Google Scholar
 

Hu X, Liu H, Liu Q, et al. Depressive symptoms and their influencing factors among older adults in china: a cross-sectional study [J]. Front Public Health. 2024;12–2024. https://doi.org/10.3389/fpubh.2024.1423391.

Bae S-M. The relationship between the type of smartphone use and smartphone dependence of Korean adolescents: National survey study [J]. Child Youth Serv Rev. 2017;81:207–11. https://doi.org/10.1016/j.childyouth.2017.08.012.


Google Scholar
 

Elhai JD, Hall BJ, Levine JC et al. Types of smartphone usage and relations with problematic smartphone behaviors: The role of content consumption vs. social smartphone use [J]. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 2017, 11(2). https://doi.org/10.5817/cp2017-2-3

Dhir A, Chen S, Nieminen M. Predicting adolescent internet addiction: the roles of demographics, technology accessibility, unwillingness to communicate and sought internet gratifications [J]. Comput Hum Behav. 2015;51:24–33. https://doi.org/10.1016/j.chb.2015.04.056.


Google Scholar
 

Li LW, Liu J, Zhang Z, et al. Late-life depression in rural china: do village infrastructure and availability of community resources matter? [J]. Int J Geriatr Psychiatry. 2015;30(7):729–36. https://doi.org/10.1002/gps.4217.


Google Scholar
 

Guo M, Li Z, Chen Y, et al. Study on the relationship between depressive symptoms and internet use in the older adults under the background of population aging-evidence based on CHARLS 2018 and 2020 [J]. BMC Public Health. 2025;25(1):1057. https://doi.org/10.1186/s12889-025-22141-4.


Google Scholar
 

Yang Y, Deng H, Yang Q, et al. Mental health and related influencing factors among rural elderly in 14 poverty state counties of Chongqing, Southwest china: a cross-sectional study [J]. Environ Health Prev Med. 2020;25(1):51. https://doi.org/10.1186/s12199-020-00887-0.


Google Scholar
 

Wang T, Zhang S, Yang Y, et al. Health-related quality of life and its factors in Chinese people with depression and anxiety: A National multi-center cross-sectional study [J]. J Affect Disord. 2025;372:241–50. https://doi.org/10.1016/j.jad.2024.12.004.


Google Scholar
 

Gao Y, Liang J, Xu Z. Digital social media expression and social adaptability of the older adult driven by artificial intelligence [J]. Front Public Health. 2024;12:1424898. https://doi.org/10.3389/fpubh.2024.1424898.


Google Scholar
 

Fan S, Yang Y. How does internet use improve mental health among Middle-Aged and elderly people in rural areas in China? A Quasi-Natural experiment based on the China health and retirement longitudinal study (CHARLS) [J]. Int J Environ Res Public Health. 2022;19(20). https://doi.org/10.3390/ijerph192013332.

He T, Huang C, Li M, et al. Social participation of the elderly in china: the roles of conventional media, digital access and social media engagement [J]. Telematics Inform. 2020;48:101347. https://doi.org/10.1016/j.tele.2020.101347.


Google Scholar
 

Zhang S, Zhang Y. The relationship between internet use and mental health among older adults in china: the mediating role of physical exercise [J]. Risk Manag Healthc Policy. 2021;14:4697–708. https://doi.org/10.2147/rmhp.S338183.


Google Scholar
 

Bertolazzi A, Quaglia V, Bongelli R. Barriers and facilitators to health technology adoption by older adults with chronic diseases: an integrative systematic review [J]. BMC Public Health. 2024;24(1):506. https://doi.org/10.1186/s12889-024-18036-5.


Google Scholar
 

Ji R, Chen WC, Ding MJ. The contribution of the smartphone use to reducing depressive symptoms of Chinese older adults: the mediating effect of social participation [J]. Front Aging Neurosci. 2023;15:1132871. https://doi.org/10.3389/fnagi.2023.1132871.


Google Scholar
 

Hoffner CA, Lee S. Mobile phone Use, emotion Regulation, and Well-Being [J]. Cyberpsychol Behav Soc Netw. 2015;18(7):411–6. https://doi.org/10.1089/cyber.2014.0487.


Google Scholar
 

Hofer M, Hargittai E, Büchi M, et al. Older adults’ online information seeking and subjective Well-Being: the moderating role of internet skills [J]. Int J Communication. 2019;13:4426–43. https://doi.org/10.5167/uzh-175837.


Google Scholar
 

Sleiman KAA, Juanli L, Lei H, et al. User trust levels and adoption of mobile payment systems in china: an empirical analysis [J]. Sage Open. 2021;11(4). https://doi.org/10.1177/21582440211056599.

Friemel T. The digital divide has grown old: determinants of a digital divide among seniors [J]. New Media Soc. 2016;18:313–31. https://doi.org/10.1177/1461444814538648.


Google Scholar
 

Abrahim Sleiman KA, Juanli L, Lei HZ, et al. Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic [J]. Heliyon. 2023;9(5):e16197. https://doi.org/10.1016/j.heliyon.2023.e16197.


Google Scholar
 

Huang T, Wang G, Huang C. What promotes the mobile payment behavior of the elderly? [J]. Humanit Social Sci Commun. 2024;11(1):1501. https://doi.org/10.1057/s41599-024-04031-z.


Google Scholar
 

Rogers E, Singhal A, Quinlan M. Diffusion of Innovations [M]. 2019: 182–186.

Kebede AS, Ozolins LL, Holst H, et al. Digital engagement of older adults: scoping review [J]. J Med Internet Res. 2022;24(12):e40192. https://doi.org/10.2196/40192.


Google Scholar
 

Bhattacharjee P, Baker S, Waycott J. Older adults and their acquisition of digital skills: A review of current research evidence [J]. Proceedings of the 32nd Australian Conference on Human-Computer Interaction, 2021: 437–443. https://doi.org/10.1145/3441000.3441053

Kärnä E, Aavikko L, Rohner R, et al. A Multilevel Model of Older Adults’ Appropriation of ICT and Acquisition of Digital Literacy [J]. Int J Environ Res Public Health. 2022;19(23). https://doi.org/10.3390/ijerph192315714.

Quan-Haase A, Williams C, Kicevski M, et al. Dividing the grey divide: deconstructing Myths about older adults’ online Activities, Skills, and attitudes [J]. Am Behav Sci. 2018;62:1207–28. https://doi.org/10.1177/0002764218777572.


Google Scholar
 

Yang B, Lester D. Sex differences in purchasing textbooks online [J]. Comput Hum Behav. 2005;21(1):147–52. https://doi.org/10.1016/j.chb.2003.11.007.


Google Scholar
 

Zhou L, Peng Y, Xia Q. The impact of digital skills on the mental health of rural residents: from the perspective of happiness [J]. Front Psychol. 2025;16. https://doi.org/10.3389/fpsyg.2025.1471488.

Gu Y, Ali SH, Guo A. Comparing the role of social connectivity with friends and family in depression among older adults in china: evaluating the moderating effect of urban-rural status [J]. Front Psychiatry. 2023;14:1162982. https://doi.org/10.3389/fpsyt.2023.1162982.


Google Scholar
 

Kong H, Wang X. Exploring the influential factors and improvement strategies for digital information literacy among the elderly: an analysis based on integrated learning algorithms [J]. Digit Health. 2024;10:20552076241286635. https://doi.org/10.1177/20552076241286635.


Google Scholar
 

Wang C, Zhu Y, Ma J, et al. The association between internet use and depression among older adults in china: the mediating role of social networks [J]. Digit Health. 2023;9:20552076231207587. https://doi.org/10.1177/20552076231207587.


Google Scholar
 

Sun X, Yan W, Zhou H, et al. Internet use and need for digital health technology among the elderly: a cross-sectional survey in China [J]. BMC Public Health. 2020;20(1):1386. https://doi.org/10.1186/s12889-020-09448-0.


Google Scholar
 

Neves BB, Mead G. Digital technology and older people: towards a sociological approach to technology adoption in later life [J]. Sociology. 2021;55(5):888–905. https://doi.org/10.1177/0038038520975587.


Google Scholar
 

Li L, Jin G, Guo Y, et al. Internet access, support, usage divides, and depressive symptoms among older adults in china: A nationally representative cross-sectional study [J]. J Affect Disord. 2023;323:514–23. https://doi.org/10.1016/j.jad.2022.12.001.


Google Scholar
Â