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Effects of Electroencephalogram Biofeedback on Emotion Regulation and Brain Homeostasis of Late Adolescents in the COVID-19 Pandemic
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Wanju Park, Mina Cho, Shinjeong Park
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J Korean Acad Nurs 2022;52(1):36-51. Published online February 28, 2022
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DOI: https://doi.org/10.4040/jkan.21155
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 Abstract
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- Purpose
The purpose of this study was to examine the effects of electroencephalogram (EEG) biofeedback training for emotion regulation and brain homeostasis on anxiety about COVID-19 infection, impulsivity, anger rumination, meta-mood, and self-regulation ability of late adolescents in the prolonged COVID-19 pandemic situation.
Methods
A non-equivalent control group pretest-posttest design was used. The participants included 55 late adolescents in the experimental and control groups. The variables were evaluated using quantitative EEG at pre-post time points in the experimental group. The experimental groups received 10 sessions using the three-band protocol for five weeks. The collected data were analyzed using the Shapiro-Wilk test, Wilcoxon rank sum test, Wilcoxon signed-rank test, t-test and paired t-test using the SAS 9.3 program. The collected EEG data used a frequency series power spectrum analysis method through fast Fourier transform.
Results
Significant differences in emotion regulation between the two groups were observed in the anxiety about COVID-19 infection (W = 585.50, p = .002), mood repair of meta-mood (W = 889.50, p = .024), self-regulation ability (t = - 5.02, p < .001), self-regulation mode (t = - 4.74, p < .001), and volitional inhibition mode (t = - 2.61, p = .012). Neurofeedback training for brain homeostasis was effected on enhanced sensory-motor rhythm (S = 177.00, p < .001) and inhibited theta (S = - 166.00, p < .001).
Conclusion
The results demonstrate the potential of EEG biofeedback training as an independent nursing intervention that can markedly improve anxiety, mood-repair, and self-regulation ability for emotional distress during the COVID-19 pandemic.
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Citations
Citations to this article as recorded by  - From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications
Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos
Brain Sciences.2025; 15(3): 220. CrossRef - Neuroimaging Insights into the Public Health Burden of Neuropsychiatric Disorders: A Systematic Review of Electroencephalography-Based Cognitive Biomarkers
Evgenia Gkintoni, Apostolos Vantarakis, Philippos Gourzis
Medicina.2025; 61(6): 1003. CrossRef - The interaction between emotion dynamics and opinion changes in the era of generative AI
Shangqian Li, Shaoyang Fan, Gianluca Demartini
Computers in Human Behavior Reports.2025; 19: 100722. CrossRef - Augmenting self-guided virtual-reality exposure therapy for social anxiety with biofeedback: a randomised controlled trial
Preethi Premkumar, Nadja Heym, James A. C. Myers, Phoebe Formby, Steven Battersby, Alexander Luke Sumich, David Joseph Brown
Frontiers in Psychiatry.2024;[Epub] CrossRef - Infection Anxiety and Coping Strategies Among Individuals With Schizophrenia During the COVID-19 Pandemic: Mediating Effects of Protection Motivation
Jeawon Joung, Dug Ja Choi
Journal of Psychosocial Nursing and Mental Health Services.2023; 61(11): 43. CrossRef - The Effects of Integrated Neurofeedback and Salutogenesis Nursing Intervention to Relieve Post-COVID-19 Symptoms in Late Adolescents
Youngkyung Cho, Wanju Park
Journal of Korean Academy of psychiatric and Mental Health Nursing.2023; 32(4): 402. CrossRef - Effects of Brain Attention Biofeedback Self-regulation Training Nursing Intervention on Attention, Multidimensional Impulsivity, Emotional Response Intensity, and Self-regulated Learning Ability of School-aged Children in the COVID-19 Pandemic Situation
Youngkyung Cho, Wanju Park
Journal of Korean Academy of psychiatric and Mental Health Nursing.2022; 31(2): 111. CrossRef - Comparison of QEEG Findings before and after Onset of Post-COVID-19 Brain Fog Symptoms
Marta Kopańska, Danuta Ochojska, Renata Muchacka, Agnieszka Dejnowicz-Velitchkov, Agnieszka Banaś-Ząbczyk, Jacek Szczygielski
Sensors.2022; 22(17): 6606. CrossRef
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