Self-control of Epileptic Seizures by Nonpharmacological Strategies
Overview
Psychology
Social Sciences
Authors
Affiliations
Despite the unpredictability of epileptic seizures, many patients report that they can anticipate seizure occurrence. Using certain alert symptoms (i.e., auras, prodromes, precipitant factors), patients can adopt behaviors to avoid injury during and after the seizure or may implement spontaneous cognitive and emotional strategies to try to control the seizure itself. From the patient's view point, potential means of enhancing seizure prediction and developing seizure control supports are seen as very important issues, especially when the epilepsy is drug-resistant. In this review, we first describe how some patients anticipate their seizures and whether this is effective in terms of seizure prediction. Secondly, we examine how these anticipatory elements might help patients to prevent or control their seizures and how the patient's neuropsychological profile, specifically parameters of perceived self-control (PSC) and locus of control (LOC), might impact these strategies and quality of life (QOL). Thirdly, we review the external supports that can help patients to better predict seizures. Finally, we look at nonpharmacological means of increasing perceived self-control and achieving potential reduction of seizure frequency (i.e., stress-based and arousal-based strategies). In the past few years, various approaches for detection and control of seizures have gained greater interest, but more research is needed to confirm a positive effect on seizure frequency as well as on QOL.
Pan-cortical electrophysiologic changes underlying attention.
Lesser R, Webber W, Miglioretti D Sci Rep. 2024; 14(1):2680.
PMID: 38302535 PMC: 10834435. DOI: 10.1038/s41598-024-52717-w.
Stress and Epilepsy: Towards Understanding of Neurobiological Mechanisms for Better Management.
Jhaveri D, McGonigal A, Becker C, Benoliel J, Nandam L, Soncin L eNeuro. 2023; 10(11).
PMID: 37923391 PMC: 10626502. DOI: 10.1523/ENEURO.0200-23.2023.
Online Learning for Wearable EEG-Based Emotion Classification.
Moontaha S, Schumann F, Arnrich B Sensors (Basel). 2023; 23(5).
PMID: 36904590 PMC: 10007607. DOI: 10.3390/s23052387.
Unsupervised EEG preictal interval identification in patients with drug-resistant epilepsy.
Leal A, Curty J, Lopes F, Pinto M, Oliveira A, Sales F Sci Rep. 2023; 13(1):784.
PMID: 36646727 PMC: 9842648. DOI: 10.1038/s41598-022-23902-6.
Would people living with epilepsy benefit from palliative care?.
Kluger B, Drees C, Wodushek T, Frey L, Strom L, Brown M Epilepsy Behav. 2020; 114(Pt A):107618.
PMID: 33246892 PMC: 9326903. DOI: 10.1016/j.yebeh.2020.107618.