Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/29165
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dc.contributor.authorLila Iznita Izhar-
dc.contributor.authorBabiker, Areej-
dc.contributor.authorRizki, Edmi Edison-
dc.contributor.authorLu, Cheng-Kai-
dc.contributor.authorMohammad Abdul Rahman-
dc.contributor.author(UniKL RCMP)-
dc.date.accessioned2023-11-30T06:28:25Z-
dc.date.available2023-11-30T06:28:25Z-
dc.date.issued2022-04-
dc.identifier.citationLila 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/s22072703en_US
dc.identifier.issn14248220-
dc.identifier.urihttps://ir.unikl.edu.my/jspui/handle/123456789/29165-
dc.description.abstractNeuroticism 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.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectElectroencephalographyen_US
dc.subjectEmotion regulationen_US
dc.subjectMindfulnessen_US
dc.subjectNeuroticismen_US
dc.titleEmotion Self-Regulation in Neurotic Students: A Pilot Mindfulness-Based Intervention to Assess Its Effectiveness through Brain Signals and Behavioral Dataen_US
dc.typeArticleen_US
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