Abstract Objective Prior literature suggests there may be gender-based differences in Post-Concussion Symptom Scale (PCSS) scores, with girls reporting more symptoms than boys at pre- and post-concussion. PCSS network analysis comparisons on gender have been conducted at pre-concussion but not post-concussion, which can determine whether gender-based differences in symptom relationships exist post-concussion. We conducted network comparisons between boys and girls from a sample of high school athletes at acute post-concussion to analyze differences in symptom relationships. Method Separate network analyses were conducted on acute post-concussion PCSS scores (within 72 hours post-suspected concussion) for boys (n = 2032) and girls (n = 1246), with nodes representing PCSS items and edges representing partial correlations between them. Expected influence was calculated to determine node importance in each network. Network Comparison Tests were used to compare network structure, global connectivity, and expected influence. Results Both networks’ expected influences and edge weights were stable and interpretable. There were no significant differences in network structure, connectivity, and expected influence between the groups. Networks consisted of positive and negative edges; strongest edges connected symptoms within similar domains (e.g., light and noise sensitivity). Conclusions Current results suggest that prior reports of gender-based differences in PCSS scores following concussion do not appear to be accounted for by differences in how PCSS items interact and influence each other. Differences may reflect actual differences in type and severity of post-concussion symptoms experienced by boys and girls or reflect differences in symptom reporting based on cultural influences. Future research could examine cultural or societal factors that influence gender-based differences in symptom reporting.

Objective:Previous studies have found differences between monolingual and bilingual athletes on ImPACT, the most widely used sport-related concussion (SRC) assessment measure. Most recently, results suggest that monolingual English-Speaking athletes outperformed bilingual English- and Spanish-speaking athletes on Visual Motor Speed and Reaction Time composites. Before further investigation of these differences can occur, measurement invariance of ImPACT must be established to ensure that differences are not attributable to measurement error. The current study aimed to 1) replicate a recently identified four-factor model using cognitive subtest scores of ImPACT on baseline assessments in monolingual English-Speaking athletes and bilingual English- and Spanish-speaking athletes and 2) to establish measurement invariance across groups.Participants and Methods:Participants included high school athletes who were administered the ImPACT as part of their standard pre-season athletic training protocol in English. Participants were excluded if they had a self-reported history of concussion, Autism, ADHD, learning disability or treatment history of epilepsy/seizures, brain surgery, meningitis, psychiatric disorders, or substance/alcohol use. The final sample included 7,948 monolingual English-speaking athletes and 7,938 bilingual English- and Spanish-speaking athletes with valid baseline assessments. Language variables were based on self-report. As the number of monolingual athletes was substantially larger than the number of bilingual athletes, monolingual athletes were randomly selected from a larger sample to match the bilingual athletes on age, sex, and sport. Confirmatory factor analysis (CFA) was used to test competing models, including one-factor, two-factor, and three-factor models to determine if a recently identified four-factor model (Visual Memory, Visual Reaction Time, Verbal Memory, Working Memory) provided the best fit of the data. Eighteen subtest scores from ImPACT were used in the CFAs. Through increasingly restrictive multigroup CFAs (MGCFA), configural, metric, scalar, and residual levels of invariance were assessed by language group.Results:CFA indicated that the four-factor model provided the best fit in the monolingual and bilingual samples compared to competing models. However, some goodness-of-fit-statistics were below recommended cutoffs, and thus, post-hoc model modifications were made on a theoretical basis and by examination of modification indices. The modified four-factor model had adequate to superior fit and met criteria for all goodness-of-fit indices and was retained as the configural model to test measurement invariance across language groups. MGCFA revealed that residual invariance, the strictest level of invariance, was achieved across groups.Conclusions:This study provides support for a modified four-factor model as estimating the latent structure of ImPACT cognitive scores in monolingual English-speaking and bilingual English- and Spanish-speaking high school athletes at baseline assessment. Results further suggest that differences between monolingual English-speaking and bilingual English- and Spanish-speaking athletes reported in prior ImPACT studies are not caused by measurement error. The reason for these differences remains unclear but are consistent with other studies suggesting monolingual advantages. Given the increase in bilingual individuals in the United States, and among high school athletics, future research should investigate other sources of error such as item bias and predictive validity to further understand if group differences reflect real differences between these athletes.

PCSS network connectivity, structure, and symptom influence do not differ between bilingual and monolingual athletes, suggesting differences do not exist in symptom interactions between groups and likely do not underly observed differences in symptom ratings. Future work should examine whether administration language influences symptom networks.

OBJECTIVE Assessment of post-concussion symptoms is implemented at secondary, post-secondary, and professional levels of athletics. 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 post-concussion symptoms may provide new insights into symptom comorbidity and may inform targeted treatment. We used network analysis to examine the topology of post-concussion symptoms using the Post-Concussion Symptom Scale (PCSS) in high school athletes with recent suspected sport-related concussion. METHOD Using a cross-sectional design, the network was estimated from Post Concussion Symptom Scale scores from 3,292 high school athletes, where nodes represented symptoms and edges represented the association between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. RESULTS The network consisted of edges within and across symptom domains. "Difficulty concentrating" and "dizziness" were the most central symptoms in the network. Although not highly central in the network, headaches were the highest rated symptom. CONCLUSIONS The interconnectedness among symptoms supports the notion that post-concussion symptoms are interrelated and mutually reinforcing. Given their central role in the network, "difficulty concentrating" and "dizziness" are expected to affect the activation and persistence of other post-concussion symptoms. Interventions targeting difficulties with concentration and dizziness may help alleviate other symptoms. Our findings could inform the development of targeted treatment with the aim of reducing overall symptom burden. Future research should examine the trajectory of post-concussion symptom networks to advance the clinical understanding of post-concussive recovery.

Increased NPS severity at baseline predicts more rapid decline in EF over four years. Findings highlight the prognostic value of NPS on cognitive decline and underscore the importance of targeting NPS at early disease stages. Future research will examine influence of individual NPS on rate of cognitive decline.

The BP+ group was less accurate in identifying negative emotions but not positive emotions compared to the BP- and HC groups. Further investigation is required to determine factors that contribute to this differential performance.

The pairwise dependency between neuropsychiatric symptoms differs as a function of CT. Future research is needed to identify factors that influence symptom reporting, including interpersonal dynamics, amount of time spent together, and overall burden of symptoms.

Objective:Recent conceptualizations of concussion symptoms have begun to shift from a latent perspective (which suggests a common cause; i.e., head injury), to a network perspective (where symptoms influence and interact with each other throughout injury and recovery). Recent research has examined the network structure of the Post-Concussion Symptom Scale (PCSS) cross-sectionally at pre-and post-concussion, with the most important symptoms including dizziness, sadness, and feeling more emotional. However, within-subject comparisons between network structures at pre-and post-concussion have yet to be made. These analyses can provide invaluable information on whether concussion alters symptom interactions. This study examined within-athlete changes in PCSS network connectivity and centrality (the importance of different symptoms within the networks) from baseline to post-concussion.Participants and Methods:Participants were selected from a larger longitudinal database of high school athletes who completed the PCSS in English as part of their standard athletic training protocol (N=1,561). The PCSS is a 22-item self-report measure of common concussion symptoms (i.e., headache, vomiting, dizziness, etc.) in which individuals rate symptom severity on a 7-point Likert scale. Participants were excluded if they endorsed history of brain surgery, neurodevelopmental disorder, or treatment history for epilepsy, migraines, psychiatric disorders, or alcohol/substance use. Network analysis was conducted on PCSS ratings from a baseline and acute post-concussion (within 72-hours post-injury) assessment. In each network, the nodes represented individual symptoms, and the edges connecting them their partial correlations. Estimations of the regularized partial correlation networks were completed using the Gaussian graphical model, and the GLASSO algorithm was used for regularization. Each symptom’s expected influence (the sum of its partial correlations with other symptoms) was calculated to identify the most central symptoms in each network. Recommended techniques from Epskamp et al. (2018) were completed for assessing the accuracy of the estimated symptom importance and relationships. Network Comparison Tests were conducted to observe changes in network connectivity, structure, and node influence.Results:Both baseline and acute post-concussion networks contained negative and positive relationships. The expected influence of symptoms was stable in both networks, with difficulty concentrating having the greatest expected influence in both. The strongest edges in the networks were between symptoms within similar domains of functioning (e.g., sleeping less was associated with trouble falling asleep). Network connectivity was not significantly different between networks (S=0.43), suggesting the overall degree to which symptoms are related was not different at acute post-concussion. Network structure significantly differed at acute post-concussion (M=0.305), suggesting specific relationships in the acute post-concussion network were different than they were at baseline. In the acute post concussion network, vomiting was less central and sensitivity to noise and mentally foggy more central.Conclusions:PCSS network structure at acute post-concussion is altered, suggesting concussion may disrupt symptom networks and certain symptoms’ associations with the experience of others after sustaining a concussive injury. Future research should compare PCSS networks later in recovery to examine if similar structural changes remain or return to baseline structure, with the potential that observing PCSS network structure changes post-concussion could inform symptom resolution trajectories.

Objective: Recently, factor analysis has supported a five-factor model of negative symptoms in schizophrenia (anhedonia, avolition, alogia, asociality, and blunted affect). Associations between these unique negative symptom domains and neurocognition are yet to be examined. The following study investigates relationships between the five distinct negative symptoms and cognitive functioning. Methods: Outpatients diagnosed with schizophrenia (n=245) were assessed during periods of clinical stability for negative symptom severity using the Brief Negative Symptom Scale (BNSS). The MATRICS Consensus Cognitive Battery (MCCB) was used to assess seven domains of neurocognition, including processing speed, working memory, verbal learning, visual learning, reasoning, problem solving, and social cognition. To evaluate external correlates, the five-domain negative symptoms were correlated with measures of neurocognition. Results: Greater negative associations were found between the five negative symptom domains with processing speed, attention, working memory, social cognition, and overall MCCB scores. Correlational analyses demonstrated the strongest negative relationships between the domain of attention with alogia and blunted affect. Conclusions: The present study examined unique associations between cognitive abilities and the five negative symptom domains. Strong negative associations were found between negative symptoms and distinct measures of neurocognition, indicating a unique variance in cognitive performance correlates with severity of negative symptoms. Results suggest greater severity of negative symptoms is associated with greater impairments in select neurocognitive domains. Further research using analytic approaches would offer additional support for this hypothesis. Findings have implications for developing differential treatments targeting the five negative symptom domains separately, as they may have distinct underlying pathophysiological and neurocognitive mechanisms.