This study of male and female adolescent delinquency trajectories focuses on the prediction of late adolescence delinquency, based on earlier delinquency and social support. In this 3-wave longitudinal survey, 270 Dutch adolescents (113 males and 157 females) ages 12 to 14, were followed for a period of 6 years. For males, the level of delinquent activity in late adolescence strongly depends on earlier delinquent activities (R2 = .33, p < .0005). In contrast, the level of female delinquency in late adolescence is far less predictable (R2 = .18, p < .001), and could not be predicted from delinquent activities during pre and early adolescence, while support from the mother during late adolescence was associated with reduced delinquency for females. Different models may be needed to explain the development of delinquency for males versus females.
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BioData Min
January 2025
Department of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia.
Background: This study employs a LSTM-FC neural networks to address the critical public health issue of child undernutrition in Ethiopia. By employing this method, the study aims classify children's nutritional status and predict transitions between different undernutrition states over time. This analysis is based on longitudinal data extracted from the Young Lives cohort study, which tracked 1,997 Ethiopian children across five survey rounds conducted from 2002 to 2016.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA.
Background: Shorter weeknight sleep duration has not been assessed as a mediating mechanism linking earlier pubertal timing to a greater burden of adolescent depression symptoms.
Methods: Among 1138 participants (48.6 % female) from Project Viva, a pre-birth longitudinal cohort, we examined relationships among pubertal timing measures, actigraphy-captured and self-reported weeknight sleep duration across mid-adolescence, and depression symptoms in late adolescence.
Biol Psychiatry Cogn Neurosci Neuroimaging
January 2025
Department of Psychiatry, Washington University in St. Louis, School of Medicine, Saint Louis, MO, USA.
Background: The understanding of the neural correlates of borderline personality disorder (BPD) is limited, but suggests alterations in limbic structures play a role in adult BPD. The developmental course of structural neural differences in BPD is unknown. Whether there is specificity for structural alterations in BPD compared with other psychiatric presentations, such as major depressive disorder (MDD), remains unexplored.
View Article and Find Full Text PDFJ Youth Adolesc
January 2025
Department of Psychology, George Mason University, Fairfax, VA, USA.
Because educational attainment is associated with well-being in the long term, it is important to understand the developmental processes that enhance academic outcomes during adolescence. Also, although the importance of friends is well documented in adolescence, little is known about how close friends' characteristics work together with youth's own characteristics to shape adolescents' educational trajectories. This study fills an important gap in knowledge by focusing on how middle school students' academic achievement and externalizing problems are associated with their friends' achievement and externalizing problems over time, and how these variables predict educational attainment in adulthood.
View Article and Find Full Text PDFEur J Paediatr Neurol
January 2025
Department of Pediatric Neurology, Children's Hospital Datteln, Witten/Herdecke University, Datteln, Germany. Electronic address:
Background: Early onset pediatric multiple sclerosis (EOPMS) provides an early window of opportunity to understand the mechanisms leading to MS.
Objective: To investigate clinical, laboratory and imaging differences between children with early onset pediatric MS (<11 years, EOPMS) and late onset pediatric MS (≥11 years, LOPMS).
Methods: Mostly prospectively collected data of children with MS including clinical presentation, MRI at onset, time to second relapse, relapse rate, treatment history, and CSF markers were eligible.
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