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| http://dx.doi.org/10.1136/bmj.327.7411.394-a | DOI Listing |
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The psychometric properties of the child anxiety and depression life interference scale (CADLIS).
Child Adolesc Psychiatry Ment Health
January 2025
Black Dog Institute, University of New South Wales, Sydney, NSW, 2031, Australia.
Objective: Life interference is a key diagnostic feature for anxiety and depressive disorders. Measures focusing on life interference caused by anxiety and depressive disorders in children and adolescents have received minimal attention. This study evaluated the psychometric properties of the Child Anxiety and Depression Life Interference Scale (CADLIS), a brief child (CADLIS-C) and parent-report (CADLIS-P) measure designed to assess life interference from anxiety and depressive disorders in both the child and parent's life.
View Article and Find Full Text PDFGreater neural delay discounting on reward evaluation in anhedonia.
Int J Clin Health Psychol
January 2025
Department of Psychology, Guangzhou University, 230 Wai Huan Xi Road, Guangzhou Higher Education Mega Center, Guangzhou 510006, China.
Background/objective: Recent years have witnessed a surge of interest in dissecting the anticipatory and the consummatory aspects of anhedonia in terms of temporal dynamics. However, few research has directly examined reward valuation as a function of time in anhedonia.
Method: Using a delay discounting task, this event-related potential study examined the neural representation of rewards available immediately or in six months in a high-anhedonia group ( = 40) and a low-anhedonia group ( = 40) recruited from a nonclinical sample.
Dissociable ventral and dorsal sensorimotor functional circuits linking the hypomanic personality traits to aggression via behavioral inhibition system.
Int J Clin Health Psychol
January 2025
Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.
Article Synopsis
- Hypomanic personality traits (HPT) are linked to higher risk for psychiatric disorders like bipolar disorder and are associated with aggressive behaviors, yet the underlying neuropsychological mechanisms are not fully understood.
- The study used psychometric network analysis to identify key factors (Behavioral Inhibition System and mood volatility) that connect HPT to aggression, finding that mood volatility positively correlates with aggression, with BIS acting as a mediator.
- Further imaging studies revealed distinct functions of the dorsal and ventral sensorimotor cortices in processing rewards, and resting-state imaging confirmed these regions' connections to different brain networks, highlighting the importance of these circuits in mediating the relationship between mood volatility, aggression, and BIS.
Game changing electoral reforms and party system change? An analysis of the 2020 national assembly election in South Korea.
Heliyon
January 2025
School of International Studies, Hanyang University, 222Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea.
The article analyses the 2020 National Assembly election in South Korea. It was the first legislative election held after President Park Geun-hye had been successfully impeached, and removed from office, in March 2017. The 2020 election was also the first election after important changes to the electoral law were made in 2019.
View Article and Find Full Text PDFDiscovering patient groups in sequential electronic healthcare data using unsupervised representation learning.
BMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Design: We applied document embedding algorithms to real-world paediatric intensive care (PICU) EHR data to extract patient-specific features from 1853 patients' PICU journeys using 647 unique lab tests and medication events. We evaluated the clinical utility of the patient features via a K-means clustering analysis.
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