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The goal of this study was to disentangle the common and unique genetic and environmental influences on social-emotional competence, problem behavior, physiological dysregulation, and negative emotionality (NE) in toddlers. The sample consisted of 243 twin pairs (mean age = 31.94 months) rated by primary caregivers (>95% mothers) on the Children's Behavior Questionnaire and the Infant-Toddler Social and Emotional Assessment. A multivariate Cholesky Decomposition revealed three shared environmental factors, with one set of environmental influences common to competence, problem behavior, and physiological dysregulation, a second common to problem behavior and physiological dysregulation, and a third common to physiological dysregulation and NE. Also, there were two additive genetic factors, with one explaining variance in competence, NE, and a small amount of variance in problem behavior, and a second explaining variance in problem behavior and NE. Given the common shared environmental factors across outcomes, these results suggest that toddlerhood could be a particularly important time to intervene, as interventions could simultaneously improve competencies and reduce problem behaviors. This study also highlights the need for genetically informed research to examine the etiology of multiple outcomes and address overlap.
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http://dx.doi.org/10.1111/sode.12347 | DOI Listing |
Langmuir
September 2025
Microplastics Research Center, Yaroslav-the-Wise Novgorod State University, Veliky Novgorod 173003, Russia.
Microplastics, tiny fragments resulting from the degradation of plastic waste, are abundant in water, air, and soil and are currently recognized as a global environmental problem. There is also growing evidence that nanosized microplastics (nanoplastics) can be hazardous to living species. Unlike most experimental methods, computer modeling is particularly well suited to studying the effects of such nanoplastics.
View Article and Find Full Text PDFPerspect Behav Sci
September 2025
Integrated Center for Autism Spectrum Disorders, University of Nebraska Medical Center's Munroe-Meyer Institute, Omaha, NE USA.
Client well-being remains a central goal of research on the assessment and treatment of problem behavior. Although methodologies have evolved over the decades, the use of isolated- and synthesized-contingency functional analyses as a starting point remains debated. This article explores several factors potentially inhibiting consensus, the harm caused by division, and ways to shift the discourse regarding isolation and synthesis toward collaboration.
View Article and Find Full Text PDFPerspect Behav Sci
September 2025
School of Psychology, Ulster University, Coleraine, Northern Ireland.
Although applied behavior analysis (ABA) is regarded as providing the gold standard for interventions designed to meet the needs of autistic individuals in the United States, elsewhere this is not the case. In Northern Ireland, for example, successive governments have portrayed ABA simply as one of a number of commercially available interventions for autism. In this article, I argue that this view arises directly from the practice of behavior analysts who have courted the development of branded versions of ABA at the expense of promoting ABA directly.
View Article and Find Full Text PDFActa Psychol (Amst)
September 2025
Guangxi Center of Developmental Population Neuroscience, Nanning Normal University, Nanning 530001, China. Electronic address:
Background: Problem behaviors profoundly disrupt adolescents' overall quality of life, interpersonal relationships, and ability to engage effectively in learning. These behaviors are deeply influenced by psychological abuse, neglect, and school connectedness. Using a network approach to explore the relationships between these variables can provide new perspectives for reducing adolescent problem behaviors.
View Article and Find Full Text PDFJ Adv Res
September 2025
Institute of Big Data and Information Technology, Wenzhou University, Wenzhou 325000, China. Electronic address:
Introduction: Numerical optimization plays a key role in improving the efficiency of solar photovoltaic (PV) systems and solving complex engineering problems. Traditional optimization methods often struggle with finding optimal solutions within a reasonable timeframe due to high-dimensional and non-linear problem landscapes.
Objectives: This study aims to introduce a novel swarm intelligence algorithm, the Beaver Behavior Optimizer (BBO), inspired by the cooperative behaviors of beavers during dam construction.