ArticleDevelopmental psychobiology2024
Comparative analysis of electrodermal activity metrics and their association with child behavior in autism spectrum disorder.
Article in Developmental psychobiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- Synchrony and Reciprocity in Rhythmic Interaction.Annals of the New York Academy of Sciences · 2026Review
- The emotion dysregulation inventory - self-report: development and psychometric evaluation.Psychological medicine · 2026Article
- Using Wearables in Mental Health Care for Children and Adolescents: A Scoping Review.Research on child and adolescent psychopathology · 2026Article
- Article
- Advancing Research on Suicide and Mental Health in Autistic Adults Through a Research Domain Criteria (RDoC)-Inspired Framework.Autism in adulthood · 2025Article
- Non-Invasive Wearables in Pediatric Healthcare: A Comprehensive Review of Uses and Implications.Children (Basel, Switzerland) · 2025Review
- Article
- Electrodermal Activity (EDA) Morphologies and Prediction of Engagement with Simple Moving Average Crossover: A Mixed-Method Study.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Researchers are increasingly utilizing physiological data like electrodermal activity (EDA) to understand how stress "gets under the skin." Results of EDA studies in autistic children are mixed, with some suggesting autistic hyperarousal, others finding hypoarousal, and yet others detecting no difference compared to non-autistics. Some of this variability likely stems from the different techniques used to assess EDA. Therefore, the purpose of this study is to investigate and compare commonly used metrics of EDA (frequency of peaks, average amplitude of peaks, and standard deviation of skin conductance level) using two data processing programs (NeuroKit2 and Ledalab) and their link to observed child behavior. EDA data were collected using Empatica E4 wristbands from 60 autistic children and adolescents (5-18 years old) during a 7-min play interaction with their primary caregiver. The play interaction was coded for a range of child behaviors including mood, social responsiveness, dysregulation, and cooperation. Results indicate a strong correlation between NeuroKit2 and Ledalab and a weak correlation between metrics within each program. Furthermore, the frequency of peaks was associated with more positive child social behaviors, and the magnitude of peaks was associated with less adaptive child behaviors. Recommendations for replication and the need for generalizability of this research are given.
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Registered trials
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