Chu Meijie, Ma Honghao, Lee Chun-Yang, Zhao Zeyu, Chen Tianmu, Zhang Shuoxun, Chiang Yi-Chen
State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
School of International Business, Xiamen University Tan Kah Kee College, Zhangzhou, China.
Heliyon. 2023 May 11;9(5):e16176. doi: 10.1016/j.heliyon.2023.e16176. eCollection 2023 May.
Positive social relationships are critical for better subjective well-being across ages. Future research will benefit from examining how to improve life satisfaction by utilizing social groups in new, ever-changing social and technological contexts. This study aimed to evaluate the effect of online and offline social network group clusters on life satisfaction across different age groups.
Data were derived from the Chinese Social Survey (CSS) (2019), which is a nationally representative survey. We adopted a K-mode cluster analysis algorithm to categorize participants into four clusters according to their online and offline social network groups. ANOVA and chi-square analysis were used to understand the associations among age groups, social network group clusters, and life satisfaction. Multiple linear regression was applied to identify the association between social network group clusters and life satisfaction across age groups.
Younger and older adults had higher life satisfaction than middle-aged adults. Individuals who joined diverse social network groups had the highest life satisfaction, followed by those who joined personal and working social groups, while those who joined restricted social groups had the lowest life satisfaction (F = 81.19, p < 0.001). According to the results of multiple linear regression, individuals who belonged to diverse social groups had higher life satisfaction than those who belonged to restricted social groups among adults aged 18-59 years, except students (p < 0.05). Individuals who joined personal and working social groups had higher life satisfaction than those who joined restricted social groups among adults aged 18-29 and 45-59 years (β = 2.15, p < 0.01; β = 1.45, p < 0.01).
Interventions to promote participation in diverse social network groups among adults aged 18-59 years, except for students, are highly recommended to improve life satisfaction. Health practitioners could provide interventions to encourage young and middle-aged adults to join both personal and working social groups.
积极的社会关系对于各年龄段提高主观幸福感至关重要。未来的研究将受益于探讨如何在不断变化的新社会和技术背景下，通过利用社会群体来提高生活满意度。本研究旨在评估线上和线下社交网络群体聚类对不同年龄组生活满意度的影响。
数据来源于具有全国代表性的《中国社会调查》（CSS）（2019年）。我们采用K-模式聚类分析算法，根据参与者的线上和线下社交网络群体将其分为四类。采用方差分析和卡方分析来了解年龄组、社交网络群体聚类和生活满意度之间的关联。应用多元线性回归来确定社交网络群体聚类与各年龄组生活满意度之间的关联。
年轻人和老年人的生活满意度高于中年人。加入多样化社交网络群体的个体生活满意度最高，其次是加入个人和工作社交群体的个体，而加入受限社交群体的个体生活满意度最低（F = 81.19，p < 0.001）。根据多元线性回归结果，在18 - 59岁的成年人中，除学生外，属于多样化社会群体的个体比属于受限社会群体的个体生活满意度更高（p < 0.05）。在18 - 29岁和45 - 59岁的成年人中，加入个人和工作社交群体的个体比加入受限社交群体的个体生活满意度更高（β = 2.15，p < 0.01；β = 1.45，p < 0.01）。
强烈建议对18 - 59岁的成年人（学生除外）进行干预，以促进他们参与多样化的社交网络群体，从而提高生活满意度。健康从业者可以提供干预措施，鼓励年轻人和中年人加入个人和工作社交群体。
