Heterogeneity in Cognitive and Socio-Emotional Functioning in Adolescents With On-Track and Delayed School Progression

Changes in ImPACT Cognitive Subtest Networks Following Sport-Related Concussion

OBJECTIVE

High school athletes are administered ImPACT at the start of the academic year or sport season and again after suspected concussion. Concussion management involves the comparison of baseline and post-injury cognitive scores with declines in scores providing evidence for concussive injury. A network framework may provide additional information about post-concussive cognitive changes and expand characterization of sport-related concussion (SRC) recovery.

DESIGN

Retrospective cohort study.

SETTING

High school.

PARTICIPANTS

High school athletes (n = 1553) were administered ImPACT at baseline (T1), post-SRC (T2 = 72 h of injury), and prior to return to play (T3 = within two weeks post-injury).

INDEPENDENT VARIABLES

ImPACT cognitive subtest scores.

MAIN OUTCOME MEASURES

Cognitive networks were calculated and compared over three time points. Centrality indices were calculated to determine the relative importance of cognitive variables within networks.

RESULTS

Network connectivity increased from T1 to T2 and remained hyperconnected at T3. There was evidence of network reorganization between T1 and T3. Processing speed was central within each network, and visual memory and impulsivity became more central over time.

CONCLUSIONS

The results suggest potential evidence of cognitive network change over time. Centrality findings suggest research specific to visual memory and impulse control difficulties during the post-concussion recovery period is warranted. Network analysis may provide additional information about cognitive recovery following SRC and could potentially serve as an effective means of monitoring persisting cognitive symptoms after concussion.

Understanding patterns of heterogeneity in executive functioning during adolescence: Evidence from population-level data

Executive functioning (EF) is fundamental to positive development. Yet, little is known about how to best characterize constellations of EF skills that may inform disparate associations between EF and behavior during adolescence. In the current study, cross-validated latent profile analysis (LPA) was used to derive profiles of EF based on measures of inhibitory control, working memory, and cognitive flexibility using data from 11,672 youth (52.2% male, mean age = 9.91 years) in the Adolescent Brain and Cognitive Development study. Four meaningful EF profiles emerged from the data representing Average EF, High EF, Low Inhibitory Control, and Low EF. Boys, youth from low-income households, and early developing youth were more likely to be in profiles distinguished by lower EF. Profile membership also predicted differences in externalizing, internalizing, and other problem behaviors assessed one year later. Findings indicate that youth may have distinct constellations of EF skills, underscoring the need for person-centered approaches that focus on patterns of individual characteristics.

Psychosocial assessment of families caring for a child with acute lymphoblastic leukemia, epilepsy or asthma: Psychosocial risk as network of interacting symptoms

The purpose of this study is to assess psychosocial risk across several pediatric medical conditions and test the hypothesis that different severe or chronic pediatric illnesses are characterized by disease specific enhanced psychosocial risk and that risk is driven by disease specific connectivity and interdependencies among various domains of psychosocial function using the Psychosocial Assessment Tool (PAT). In a multicenter prospective cohort study of 195 patients, aged 5–12, 90 diagnosed with acute lymphoblastic leukemia (ALL), 42 with epilepsy and 63 with asthma, parents completed the PAT2.0 or the PAT2.0 generic version. Multivariate analysis was performed with disease as factor and age as covariate. Graph theory and network analysis was employed to study the connectivity and interdependencies among subscales of the PAT while data-driven cluster analysis was used to test whether common patterns of risk exist among the various diseases. Using a network modelling approach analysis, we observed unique patterns of interconnected domains of psychosocial factors. Each pathology was characterized by different interdependencies among the most central and most connected domains. Furthermore, data-driven cluster analysis resulted in two clusters: patients with ALL (89%) mostly belonged to cluster 1, while patients with epilepsy and asthma belonged primarily to cluster 2 (83% and 82% respectively). In sum, implementing a network approach improves our comprehension concerning the character of the problems central to the development of psychosocial difficulties. Therapy directed at problems related to the most central domain(s) constitutes the more rational one because such an approach will inevitably carry over to other domains that depend on the more central function.