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Multisource Longitudinal Network and Latent Variable Model Analyses of ADHD Symptoms in Children.
J Clin Child Adolesc Psychol. 2020 Jun 01;:1-8
Authors: Preszler J, Burns GL, Becker SP, Servera M
Abstract
OBJECTIVE: Multisource longitudinal network analysis was used to determine if between-child and within-child variance of attention-deficit/hyperactivity disorder (ADHD) symptoms provided unique findings of ADHD relative to latent variable model (LVM) analyses.
METHOD: Mothers and fathers of 802 Spanish first-grade children (54% boys) provided ratings of ADHD symptoms at two time points six weeks apart (assessment 1: 723 mothers and 603 fathers; assessment 2: 667 mothers and 584 fathers). Network and latent variable models were applied to the ratings.
RESULTS: Inattention, hyperactivity, and mixed hyperactive/impulsive symptom communities occurred for the within- and between-children’s symptom networks with the results being consistent across mothers and fathers, especially for the between-children’s symptom networks. LVM analyses identified three factors with the same symptoms on each factor as in the symptom communities. These models also showed invariance across mothers and fathers as well as assessments.
CONCLUSIONS: Longitudinal networks provided several useful insights for ADHD, including centrality symptoms that differed across between- and within-child levels. However, many findings were also largely consistent with the LVM analyses. Future studies should use novel methods (e.g., intensive longitudinal measurement) and analytic tools to determine if more unique theoretical and clinical findings emerge when applying network analysis to longitudinally measured ADHD symptoms.
PMID: 32478577 [PubMed – as supplied by publisher]
via https://www.ncbi.nlm.nih.gov/pubmed/32478577?dopt=Abstract