ArticlePCN reports : psychiatry and clinical neurosciences2024
Reduced multiscale complexity of daily behavioral dynamics in autism spectrum disorder.
Article in PCN reports : psychiatry and clinical neurosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Reduced multiscale complexity of daily behavioral dynamics in autism spectrum disorder.PCN reports : psychiatry and clinical neurosciences · 2024Article
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Authors and funding
4 authors.
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Abstract
Aim: Autism spectrum disorder (ASD) is difficult to diagnose objectively due to its heterogeneous and complex manifestations. This study aimed to objectively characterize the behavioral phenotypes of ASD children by exploring the multiscale behavioral dynamics. Methods: We applied behavioral organization (BO) and multiscale sample entropy (MSE) analyses to physical activity data collected from ASD and typically developing children, using wearable monitors in their daily life. We also examined their correlation with auditory startle response measures and clinical questionnaires, including the Social Responsiveness Scale (SRS) and the Strengths and Difficulties Questionnaire (SDQ). Results: A significant decrease in MSE at timescales longer than 6 min was observed in ASD children, suggesting decreased irregularity or unpredictability, potentially linked to repetitive behaviors or stereotyped patterns commonly observed in ASD. Additionally, an increase in MSE positively correlated with prepulse inhibition levels, indicating its relationship with sensorimotor gating. Moreover, the observed significant negative correlation with the total difficulty score of SDQ substantiates MSE's potential as an objective metric for assessing general mental health problems associated with ASD. Conclusion: Multiscale analysis enhances the understanding of ASD's behavioral dynamics, providing valuable metrics for real-world assessments.
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