Zhu Xiuyuan, Ni Zihan, Zhu Xiaoying, Yang Yi, Xie Shiyu, Wang Xinguo, Yang Xiaoguang
School of Elderly Care Services and Management, Nanjing University of Chinese Medicine, Nanjing, China.
Nossal Institute for Global Health, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Front Psychiatry. 2025 Apr 24;16:1569022. doi: 10.3389/fpsyt.2025.1569022. eCollection 2025.
To explore the chain-mediated roles of social networks and depressive symptoms in the relationship between internet use and cognition among older adults.
Data were sourced from the 2018 China Longitudinal Aging Social Survey (CLASS). Structural equation modeling (SEM) was employed to analyze the potential mediating roles of social networks and depressive symptoms. Internet use, Lubben Social Network Scale (LSNS), the Center for Epidemiological Studies Depression Scale (CES-D) and Cognitive Scale were selected as indicators. Additionally, propensity score matching (PSM) was applied to further validate the robustness of the results by reducing potential selection bias and ensuring a more comparable distribution of observed covariates between internet users and non-users.
Our analysis found that the use of the internet by older adults was positively correlated with their social networks (=0.090, <0.01). Both internet use and social networks exhibited negative associations with depressive symptoms in older adults respectively (=-0.244, <0.01; =-0.136, <0.01). Furthermore, both internet use (=0.177, <0.01) and social networks (=0.032, <0.01) positively predicted cognition in older adults, while depressive symptoms (=-0.090, <0.01) negatively impacted cognition. Moreover, our study showed that internet use not only directly influenced cognition of older adults but also indirectly impacted it through social networks and depressive symptoms, yielding a total mediated effect value of 0.026. Social networks and depressive symptoms accounted for 1.48% and 10.84% of the total effect respectively. Social networks and depressive symptoms served as chain mediators between internet use and cognition, constituting 0.49% of the total effect.
This chain-mediated model provided a clear depiction of how social networks and depressive symptoms mediate the impact of internet use on the cognition of older adults. Enhancements in internet literacy and optimization of age-appropriate product designs are recommended to improve cognitive functions in older populations.
探讨社交网络和抑郁症状在老年人互联网使用与认知关系中的链式中介作用。
数据来源于2018年中国老年社会追踪调查（CLASS）。采用结构方程模型（SEM）分析社交网络和抑郁症状的潜在中介作用。选取互联网使用、鲁本社会网络量表（LSNS）、流行病学研究中心抑郁量表（CES-D）和认知量表作为指标。此外，应用倾向得分匹配（PSM）来进一步验证结果的稳健性，通过减少潜在的选择偏差并确保互联网使用者和非使用者之间观察到的协变量分布更具可比性。
我们的分析发现，老年人的互联网使用与其社交网络呈正相关（=0.090，<0.01）。互联网使用和社交网络分别与老年人的抑郁症状呈负相关（=-0.244，<0.01；=-0.136，<0.01）。此外，互联网使用（=0.177，<0.01）和社交网络（=0.032，<0.01）均对老年人的认知有正向预测作用，而抑郁症状（=-0.090，<0.01）对认知有负向影响。此外，我们的研究表明，互联网使用不仅直接影响老年人的认知，还通过社交网络和抑郁症状间接影响认知，总中介效应值为0.026。社交网络和抑郁症状分别占总效应的1.48%和10.84%。社交网络和抑郁症状在互联网使用和认知之间起链式中介作用，占总效应的0.49%。
这种链式中介模型清晰地描绘了社交网络和抑郁症状如何介导互联网使用对老年人认知的影响。建议提高互联网素养并优化适合老年人的产品设计，以改善老年人群的认知功能。
