A-13 Characterizing the Network Structure of Post-Concussion Symptoms

Abstract Objective: Assessment of post-concussion symptoms (PCS) has become a standard part of athletics at secondary, post-secondary, and professional levels. Network theory suggests that disorders can be viewed as a set of interacting symptoms that amplify, reinforce, and maintain one another. Examining the network structure of PCS may provide new insights into symptom comorbidity to inform targeted treatment and rehabilitation. We used network analysis to examine the topology of the Post-Concussion Symptom Scale (PCSS) in high school athletes with recent sport-related concussion (SRC). Method: High school athletes (n = 3292) with suspected SRC completed the PCSS. PCSS items were entered into network analysis, where nodes represented symptoms and edges represented association between symptoms. Centrality indices were calculated to determine relative importance of each symptom in the network. Results: Edge weights, node strength, and expected influence were stable and interpretable. The network consisted of positive and negative edges. The strongest edges linked nodes within symptom domain (e.g., strong positive associations among affective symptoms). “Difficulty concentrating” was the most central and influential symptom in the network. Conclusions: The present study examined the architecture of PCS using network analysis. While strong connections were found among symptoms within similar domains, all symptoms appeared to be interconnected. “Difficulty concentrating” emerged as an influential symptom in the network. Thus, this symptom is expected to affect the activation, persistence, and remission of other PCS. Interventions targeting difficulties with concentration may help alleviate other symptoms. Future research should examine the trajectory of PCS to advance clinical understanding of persisting symptoms after concussion.