Gangwon Institute, Chuncheon, Republic of Korea.
Hallym University College of Medicine, Chuncheon Sacred Heart Hospital, 77 Sakju-ro, Chuncheon, 24253, Republic of Korea.
Sci Rep. 2024 May 22;14(1):11648. doi: 10.1038/s41598-024-62371-x.
Social Network Analysis (SNA) provides a dynamic framework for examining interactions and connections within networks, elucidating how these relationships impact behaviors and outcomes. This study targeted small residential communities in Gangwon State, South Korea, to explore network formation theories and derive strategies for enhancing health promotion services in rural communities. Conducted in 12 small residential areas, the survey led to a network categorization model distinguishing networks as formal, informal, or non-existent. Key findings demonstrated that demographic and socio-economic factors, specifically age, income, living environment, leisure activities, and education level, significantly influence network formation. Importantly, age, environmental conditions, satisfaction with public transportation, and walking frequency were closely associated with the evolution of formal networks. These results highlight the importance of early community network assessments, which must consider distinct network traits to develop effective health promotion models. Utilizing SNA early in the assessment process can improve understanding of network dynamics and optimize the effectiveness of health interventions.
社会网络分析（SNA）为研究网络内部的互动和联系提供了一个动态框架，阐明了这些关系如何影响行为和结果。本研究以韩国江原道的小型居住社区为对象，旨在探索网络形成理论，并为农村社区的健康促进服务制定策略。该研究在 12 个小型居住区域进行，调查结果得出了一个网络分类模型，将网络分为正式、非正式或不存在三种类型。研究结果表明，人口统计学和社会经济因素，特别是年龄、收入、生活环境、休闲活动和教育水平，对网络形成有重大影响。重要的是，年龄、环境条件、对公共交通的满意度和步行频率与正式网络的演变密切相关。这些结果强调了早期社区网络评估的重要性，评估必须考虑到不同的网络特征，以制定有效的健康促进模式。在评估过程中尽早使用 SNA 可以提高对网络动态的理解，并优化健康干预措施的效果。
