Liu Chang, Rotaru Kristian, Ren Lei, Chamberlain Samuel R, Christensen Erynn, Brierley Mary-Ellen, Richardson Karyn, Lee Rico S C, Segrave Rebecca, Grant Jon E, Kayayan Edouard, Hughes Sam, Fontenelle Leonardo F, Lowe Amelia, Suo Chao, Freichel René, Wiers Reinout W, Yücel Murat, Albertella Lucy
BrainPark, Turner Institute for Brain and Mental Health, Monash University, Australia.
BrainPark, Turner Institute for Brain and Mental Health, Monash University, Australia; and Monash Business School, Monash University, Australia.
BJPsych Open. 2024 May 9;10(3):e104. doi: 10.1192/bjo.2024.59.
Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI.
The current study is the first to use network analysis to (a) examine the unique association among impulsivity, compulsivity and PUI symptoms, and (b) identify the most influential drivers in relation to the PUI symptom community.
We estimated a Gaussian graphical model consisting of five facets of impulsivity, compulsivity and individual PUI symptoms among 370 Australian adults (51.1% female, mean age = 29.8, s.d. = 11.1). Network structure and bridge expected influence were examined to elucidate differential associations among impulsivity, compulsivity and PUI symptoms, as well as identify influential nodes bridging impulsivity, compulsivity and PUI symptoms.
Results revealed that four facets of impulsivity (i.e. negative urgency, positive urgency, lack of premeditation and lack of perseverance) and compulsivity were related to different PUI symptoms. Further, compulsivity and negative urgency were the most influential nodes in relation to the PUI symptom community due to their highest bridge expected influence.
The current findings delineate distinct relationships across impulsivity, compulsivity and PUI, which offer insights into potential mechanistic pathways and targets for future interventions in this space. To realise this potential, future studies are needed to replicate the identified network structure in different populations and determine the directionality of the relationships among impulsivity, compulsivity and PUI symptoms.
冲动性和强迫性均已被确定为网络使用问题（PUI）的风险因素。然而，关于冲动性、强迫性与个体PUI症状之间的关系，我们知之甚少，这限制了对PUI潜在机制的更精确理解。
本研究首次使用网络分析来（a）检验冲动性、强迫性与PUI症状之间的独特关联，以及（b）确定与PUI症状群落相关的最具影响力的驱动因素。
我们估计了一个高斯图形模型，该模型由370名澳大利亚成年人（51.1%为女性，平均年龄 = 29.8，标准差 = 11.1）的冲动性、强迫性和个体PUI症状的五个方面组成。研究了网络结构和桥梁预期影响，以阐明冲动性、强迫性与PUI症状之间的差异关联，并识别连接冲动性、强迫性与PUI症状的有影响力的节点。
结果显示，冲动性的四个方面（即消极紧迫性、积极紧迫性、缺乏预谋和缺乏毅力）以及强迫性与不同的PUI症状相关。此外，由于强迫性和消极紧迫性具有最高的桥梁预期影响，它们是与PUI症状群落相关的最具影响力的节点。
当前研究描绘了冲动性、强迫性与PUI之间的不同关系，为该领域未来干预的潜在机制途径和目标提供了见解。为了实现这一潜力，未来需要开展研究，在不同人群中复制所确定的网络结构，并确定冲动性、强迫性与PUI症状之间关系的方向性。
