Work

Network models of symptoms following mild traumatic brain injury: A systematic review and meta-analysis

Year: 2026

Type: review

Study designs: Systematic Review, Meta-Analysis

Abstract: OBJECTIVE: Network modeling of post-concussion symptoms following mild traumatic brain injury (mTBI) has emerged as a promising tool for understanding how cognitive, emotional, and somatic symptoms co-occur and interact. However, the generalizability of networks developed in individual studies remains unclear. This study aimed to develop the first-ever meta-analytic pooled between-persons network structure of post-concussion symptoms and systematically examine the between-study heterogeneity of these symptom networks. METHODS: Using the Meta-Analytic Gaussian Network Aggregation (MAGNA) framework, a single pooled network model was developed by aggregating data from 6 distinct samples, comprising a total of 5,776 participants. Additionally, this study quantitatively assessed the degree of heterogeneity across these studies. RESULTS: Strong symptom clusters between cognitive, emotional, and somatic symptoms were identified. Concentration difficulty and slowed thinking were the most central symptoms in the pooled MAGNA network. Large between-study heterogeneity was observed. CONCLUSIONS: Findings from this meta-analysis highlight cognitive symptoms as most important for defining the network structure after mTBI at a group level, potentially perpetuating and/or being perpetuated by symptoms in other domains. The large heterogeneity observed between studies underscores the need for an idiographic (person-specific) approach to studying post-concussion symptom networks to inform precision rehabilitation.

Source: Journal of the International Neuropsychological Society

DOI: 10.1017/s1355617726101854

Authors: Shuyuan Shi, Aaron J. Fisher, Amanda R. Rabinowitz, Noah D. Silverberg