Abstract Objective Explore the utility of characterizing symptom presentations using a novel statistical approach that estimates intrapersonal concussion-like symptom networks and parameters. Method Participants were N = 353 young adults ages 18–35 (84.7% female; 77.1% White; 25.8% with a lifetime concussion) who completed the Post-Concussion Symptom Scale thrice daily for 30 days. Network parameters (i.e., edge weights and bridge strength) were compiled per participant for within-person analyses, and in aggregate for between-person analyses, comparing groups with and without a lifetime concussion history. Example graphical networks were generated for within- and between-person results, although network analysis is an emerging area of research with limited guidelines for interpreting effect size and significance. Results Within-person analyses highlighted the substantial variability in concussion-like symptom presentations, with no single central symptom or edge weight emerging as especially common. The symptoms Irritability and Nervousness were among the most frequently central symptoms in both groups, though the concussion history group had a greater representation of sleep-related impairments being central symptoms. In between-person analyses, symptoms related to sleep and affect were the most common network parameters in the concussion history group versus predominantly physical symptoms in the control group. Conclusions The variability in symptom presentations demonstrates the utility of within-person network models to match individuals to rehabilitation plans that best reflect their ongoing symptom experience over time. Future research should replicate this statistical approach in acutely injured, treatment-seeking individuals following concussion to determine if patterns of sleep impairments are truly specific to post-concussion presentations.
Ingram et al. (2026) studied this question.