Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/29165
Title: Emotion Self-Regulation in Neurotic Students: A Pilot Mindfulness-Based Intervention to Assess Its Effectiveness through Brain Signals and Behavioral Data
Authors: Lila Iznita Izhar
Babiker, Areej
Rizki, Edmi Edison
Lu, Cheng-Kai
Mohammad Abdul Rahman
(UniKL RCMP)
Keywords: Electroencephalography
Emotion regulation
Mindfulness
Neuroticism
Issue Date: Apr-2022
Publisher: MDPI
Citation: Lila Iznita Izhar, Babiker, A., Rizki, E. E., Lu, C.-K., & Mohammad Abdul Rahman. (2022). Emotion Self-Regulation in Neurotic Students: A Pilot Mindfulness-Based Intervention to Assess Its Effectiveness through Brain Signals and Behavioral Data. Sensors, 22(7), 2703. https://doi.org/10.3390/s22072703
Abstract: Neuroticism has recently received increased attention in the psychology field due to the finding of high implications of neuroticism on an individual’s life and broader public health. This study aims to investigate the effect of a brief 6-week breathing-based mindfulness intervention (BMI) on undergraduate neurotic students’ emotion regulation. We acquired data of their psychological states, physiological changes, and electroencephalogram (EEG), before and after BMI, in resting states and tasks. Through behavioral analysis, we found the students’ anxiety and stress levels significantly reduced after BMI, with p-values of 0.013 and 0.027, respectively. Furthermore, a significant difference between students in emotion regulation strategy, that is, suppression, was also shown. The EEG analysis demonstrated significant differences between students before and after MI in resting states and tasks. Fp1 and O2 channels were identified as the most significant channels in evaluating the effect of BMI. The potential of these channels for classifying (single-channel-based) before and after BMI conditions during eyes-opened and eyes-closed baseline trials were displayed by a good performance in terms of accuracy (~77%), sensitivity (76–80%), specificity (73–77%), and area-underthe-curve (AUC) (0.66–0.8) obtained by k-nearest neighbor (KNN) and support vector machine (SVM) algorithms. Mindfulness can thus improve the self-regulation of the emotional state of neurotic students based on the psychometric and electrophysiological analyses conducted in this study.
URI: https://ir.unikl.edu.my/jspui/handle/123456789/29165
ISSN: 14248220
Appears in Collections:Journal Articles



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