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85 Relationships between neuropsychological functioning and adaptive functioning in a clinical sample of children with Spina Bifida
- Sara K Pardej, Jennifer I Koop, Daniel Holliday, Erin T Kaseda, Amy K Heffelfinger
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 77
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Objective:
Individuals with Spina Bifida (SB) are at increased risk for difficulties with various aspects of adaptive functioning. Poorer adaptive functioning could delay or prevent an individual from successfully living independently and managing their own condition. Despite the importance of understanding adaptive functioning in SB, currently the literature on predictors of and associated neurocognitive skills with adaptive functioning is sparse. Thus, this retrospective chart review study aimed to explore the extent to which intellectual functioning, predicts adaptive functioning in a clinical sample of children with SB.
Participants and Methods:A retrospective chart review of children with SB was conducted at a Midwestern academic medical center. Children were seen in the context of routine neuropsychological evaluations to identify neuropsychological diagnoses and provide treatment recommendations. All measures were administered based on the age of the child and in accordance with administration guidelines. Only children with complete data were included in analyses. The sample included 42 participants (Mage=10.89, SDage=3.15; 18 male, 24 female). Intellectual functioning was evaluated using either the Wechsler Intelligence Scale for Children - Fifth Edition (WISC-V) or Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV). Adaptive functioning was evaluated using primary caregiver-report scores from the Adaptive Behavior Assessment System - Third Edition (ABAS-3). Hierarchical regressions were conducted to investigate the extent to which intellectual functioning predicts parent-reported adaptive functioning. The unique contribution of each predictor variable was also considered.
Results:Model predictors included participant sex, verbal comprehension, working memory, processing speed, and full scale IQ to predict 4 different indices on the ABAS-3. Results showed a significant contribution of participant sex in all models, with males having been rated as having poorer adaptive skills. Intellectual functioning did not significantly contribute to the models. Semipartial correlations revealed that processing speed and working memory often each accounted for a fair amount of variability when controlling for all of the remaining variables in the models. In particular, when accounting for all of the remaining variables, processing speed accounted for 6.3% of variability in global adaptive functioning, 6.1% in Conceptual Skills, and 10.11% in Social Skills. Furthermore, after controlling for all of the other variables, working memory accounted for 4.5% of the variability in global adaptive functioning.
Conclusions:The present results suggest that males with SB are at increased risk for poorer adaptive functioning, and there may be some preliminary evidence of processing speed and working memory playing contributory roles as well. This may suggest at least in childhood, the verbal and global cognitive capacities of individuals with SB are not as contributory to adaptive functioning as more basic cognitive skills, such as processing speed and working memory. It is recommended that males with SB in particular should be closely monitored with regard to their development of adaptive skills, as they may be at risk of poorer adaptive abilities. Additionally, our findings provide preliminary evidence of processing speed and working memory impacting adaptive functioning. Thus, interventions and accommodations targeting both of these domains may be appropriate to implement to help with poorer adaptive skills in this population.
58 Parent Ratings of Internalizing and Externalizing Behaviors in Children with NF1 Across Childhood: A Longitudinal Investigation
- Sara K Pardej, Kristin M Lee, Bonita P Klein-Tasman
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 663-664
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Objective:
The purpose of the present study is to characterize the trajectory of internalizing and externalizing behaviors in children with NF1 longitudinally from the early childhood period to the school age period on a broad psychosocial norm-referenced measure using linear mixed model growth curves.
Participants and Methods:Children with NF1 (n=28) were seen at least once between the ages of 3-8 years old and then again between the ages of 9-13 years old. Parents completed the Behavior Assessment System for Children (BASC) Second Edition; the version of the BASC administered depended on age (i.e., preschool form or child form). Linear mixed model growth curve analyses were used to examine the developmental trajectories of children with NF1 on the following scales, which were selected due to findings in the literature: Externalizing Problems, Internalizing Problems, Hyperactivity, Anxiety, Depression, Attention, and Executive Function. T-scores (M=50, SD=10) were used. Higher scores indicate more challenges.
Results:By using loess lines to qualitatively describe the patterns of ratings across time, it is evident that most scales (Externalizing Problems, Internalizing Problems, Hyperactivity, Attention Problems, Executive Function) demonstrated curvilinear trajectory patterns, with scores peaking in the 8-10-year-old range, then decreasing again. However, there was no statistically significant effect of age on any of the scales. Notably, trajectories largely included standard scores within the normative range (T-scores between 45-55).
Conclusions:Overall, the models also suggest that most children with NF1 are within the average range of functioning on all scales examined across the childhood period. Furthermore, with the exception of the Depression and Anxiety scales, ratings tend to peak around the 8-10-year period, and then decrease into early adolescence. Thus, when working with patients with NF1, it may be the case that clinicians note relative increases in challenges across these domains in late childhood, though these challenges may decrease over time during this age range. Linear growth curve modeling identified that the developmental trajectories of internalizing and externalizing behaviors of children with NF1, as rated by parents, remain stable across the childhood period. Importantly, low power may have contributed to the lack of observed age effects. Longitudinal research would be beneficial to capture patterns that may emerge in adolescence or adulthood.
79 Concordance Between Theorized Cognitive Profiles, Medical Risk Factors, and Clinical Diagnoses Within Preschool-Aged Children
- Erin T. Kaseda, Jennifer I. Koop, Sara K. Pardej, Lauren E. Miller, Amy K. Heffelfinger
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 71-72
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Objective:
Early childhood is recognized as a critical window of rapid cognitive development. Unfortunately, many risk factors for atypical cognitive development may occur during this period, including genetic syndromes, congenital neuroanatomical malformations, pre- or perinatal injury, and neurological and medical disorders. The impact of these risk factors on cognitive functioning may not always map onto patterns typically observed in adults. Limited literature exists on the presentation of cognitive profiles within clinical populations in the preschool developmental period. The present study aimed to evaluate whether discrete a priori cognitive profiles consistent with common neurobehavioral syndromes emerge and are distinguishable on testing in early childhood in a mixed clinical sample. We also aimed to determine if there was a consistent association between known medical risk factors and resultant cognitive profiles.
Participants and Methods:Participants included 163 children aged 1-5 years (M=48.5 months, SD=12.8 months) referred for neuropsychological evaluation. The sample was predominantly male (67.5%) and White (72.9%), followed by other/mixed race (11.6%), Black (9.7%), and Latino/Hispanic (5.8%). Cognitive abilities assessed included broad intellectual abilities, verbal abilities, nonverbal abilities, attention, and executive functioning. Continuous test scores were transformed into categorical ranges of performance, with scores classified as “above average,” “average,” “below average,” or “extremely low” to allow for profile classification. Theoretical clinical profiles consistent with common neurobehavioral syndromes were determined a priori by consensus among three authors (JK, AH, LM). Chi square tests of independence were conducted to compare membership across neurobehavioral diagnostic groups, clinical profile groups, and medical groups.
Results:Based on cognitive data, 55.2% of the sample (n=90) was classified as Global Developmental Delay/Intellectual Disability, 19.6% (GDD/ID; n=32) was classified as
Language Disorder, and 18.4% (n=30) was classified as Typical Cognitive Development. 4.3% (n=7) of the sample was classified as Attention-Deficit/Hyperactivity Disorder (ADHD), and 2.5% (n=4) was classified as Nondominant Hemisphere Dysfunction. As hypothesized, cognitive profile group membership was consistent with diagnostic impressions, as actual clinical diagnoses of Language Disorder, ADHD, GDD/ID, or a classification of typical cognitive development were significantly associated with theorized cognitive profile based on test performance alone (x2 (1,20) = 147.29, p < .001). Cognitive profile group membership was also significantly associated with referral source (1,28) = 62.88, p < .001) and the presence of a neurological disorder (1,4) = 14.64, p =.006).
Conclusions:Findings support the presence of specific theorized cognitive profiles in preschoolers in a mixed clinical sample. Specifically, GDD/ID, Language Disorder, and typical cognitive development are discrete and consistently distinguishable cognitive profiles in this age range. Early life neurological risk factors are also significantly related to cognitive profile membership, suggesting that these factors may be useful in predicting cognitive development even in very young children. Future work is needed to examine the consistency of these profiles over time and their predictive value in estimating subsequent development, and the possibility of discriminating unique cognitive profiles for specific medical conditions in preschoolers.