Hevey David
School of Psychology, Trinity College Dublin, Dublin, Ireland.
Health Psychol Behav Med. 2018 Sep 25;6(1):301-328. doi: 10.1080/21642850.2018.1521283.
The present paper presents a brief overview on network analysis as a statistical approach for health psychology researchers. Networks comprise graphical representations of the relationships (edges) between variables (nodes). Network analysis provides the capacity to estimate complex patterns of relationships and the network structure can be analysed to reveal core features of the network. This paper provides an overview of networks, how they can be visualised and analysed, and presents a simple example of how to conduct network analysis in using data on the Theory Planned Behaviour (TPB). : Participants ( = 200) completed a TPB survey on regular exercise. The survey comprised items on attitudes, normative beliefs, perceived behavioural control, and intentions. Data were analysed to examine the network structure of the variables. The EBICglasso was applied to the partial correlation matrix. : The network structure reveals the variation in relationships between the items. The network split into three distinct communities of items. The affective attitude item was the central node in the network. However, replication of the network in larger samples to produce more stable and robust estimates of network indices is required. : The reported network reveals that the affective attitudinal variable was the most important node in the network and therefore interventions could prioritise targeting changing the emotional responses to exercise. Network analysis offers the potential for insight into structural relations among core psychological processes to inform the health psychology science and practice.
本文为健康心理学研究人员提供了一种作为统计方法的网络分析概述。网络由变量(节点)之间关系(边)的图形表示组成。网络分析能够估计复杂的关系模式,并且可以对网络结构进行分析以揭示网络的核心特征。本文概述了网络、它们如何可视化和分析,并给出了一个使用计划行为理论(TPB)数据在[具体软件或平台]中进行网络分析的简单示例。:参与者(n = 200)完成了一项关于定期锻炼的TPB调查。该调查包括关于态度、规范信念、感知行为控制和意图的项目。对数据进行分析以检查变量的网络结构。将EBICglasso应用于偏相关矩阵。:网络结构揭示了项目之间关系的变化。网络分为三个不同的项目群落。情感态度项目是网络中的中心节点。然而,需要在更大样本中复制该网络以对网络指标产生更稳定和可靠的估计。:所报告的网络表明情感态度变量是网络中最重要的节点,因此干预措施可以优先针对改变对锻炼的情绪反应。网络分析为洞察核心心理过程之间的结构关系提供了潜力,从而为健康心理学科学和实践提供信息。