Epilepsy Education: Recent Advances and Future Directions
Purpose of Review
The goal of this review is to survey the current literature on education in epilepsy and provide the most up-to-date information for physicians involved in the training of future doctors on this topic. We intended to review what opportunities exist to enhance our current teaching practices that may not be well-known or widely used, but may be adapted to a broader audience.
Many new techniques adopting principles of education (e.g., retrieval practice and spaced learning) or new technologies (e.g., pre-recorded lectures, computer-enhanced modules, and simulation practice) have been trialled to enhance medical education in epilepsy with some success. Many of these techniques are currently adaptable to a wider audience or may soon be available.
The use of these opportunities more broadly may allow expansion of educational research opportunities as well as enhancing our ability to pass on information. As the knowledge base in epilepsy continues to dramatically expand, we need to keep evaluating our teaching techniques to ensure we are able to pass along this knowledge to our future providers.
KeywordsEpilepsy education Graduate medical education Technology in education
Compliance with Ethical Standards
Conflict of Interest
Daniel J. Weber and Jeremy J. Moeller each declare no potential conflicts of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- 1.England MJ, Liverman CT, Schultz AM, Strawbridge LM. Epilepsy across the spectrum: promoting health and understanding. Washington, DC: National Academies Press; 2012.Google Scholar
- 3.Education ACfGM. The Neurology Milestone Project. 2015. http://www.acgme.org/portals/0/pdfs/milestones/neurologymilestones.pdf. Accessed 15 April 2019.
- 8.Education ACfGM. ACGME program requirements for graduate medical education in neurology. 2017. https://www.acgme.org/Portals/0/PFAssets/ProgramRequirements/180_neurology_2017-07-01.pdf. Accessed 15 April 2019.
- 14.Cooke M, Irby D, O’Brien B. Educating physicians: a call for reform of medical school and residency. Hoboken: John Wiley & Sons; 2010.Google Scholar
- 15.Flexner A. Medical education in the United States and Canada: a report to the Carnegie Foundation for the advancement of teaching. Bulletin number four. New York: The Carnegie Foundation for the Advancement of Teaching; 1910.Google Scholar
- 17.Lomis K, Amiel JM, Ryan MS, Esposito K, Green M, Stagnaro-Green A, et al. Implementing an entrustable professional activities framework in undergraduate medical education: early lessons from the AAMC core entrustable professional activities for entering residency pilot. Acad Med. 2017;92(6):765–70.PubMedCrossRefGoogle Scholar
- 20.•• Le TT, Prober CG. A proposal for a shared medical school curricular ecosystem. Acad Med. 2018;93(8):1125–8. This paper provides an exciting vision for a shared “ecosystem” of curricular elements that would be available to all medical schools, in formats that could be adapted to the specific purposes of each individual curriculum. PubMedCrossRefGoogle Scholar
- 21.Anderson J, Mader JE, Gutierrez A, Oliva A. EEG and sleep team-based learning. MedEdPORTAL. 2015;11:10071.Google Scholar
- 22.Barratt D, Mader E Jr, Gutierrez A, Oliva A. EEG and sleep team-based learning. MedEdPORTAL. 2015;11:10071.Google Scholar
- 23.Moeller JJ, Farooque P, Leydon G, Dominguez M, Schwartz ML, Sadler RM. A video-based introductory EEG curriculum for neurology residents and other EEG learners. MedEdPORTAL. 2017;13:10570.Google Scholar
- 24.Reid J, Stone K. Pediatric emergency medicine simulation curriculum: seizure scenario. MedEdPORTAL. 2014;10:9794.Google Scholar
- 26.• Lau KHV, Farooque P, Leydon G, Schwartz ML, Sadler RM, Moeller JJ. Using learning analytics to evaluate a video-based lecture series. Med Teach. 2018;40(1):91–8. This paper demonstrates how analytic information from a web-based educational tool can be used for curriculum evaluation and improvement. PubMedCrossRefGoogle Scholar
- 33.Larsen DP, Butler AC, Lawson AL, Roediger HL 3rd. The importance of seeing the patient: test-enhanced learning with standardized patients and written tests improves clinical application of knowledge. Adv Health Sci Educ Theory Pract. 2013;18(3):409–25. 10.1007/s10459-012-9379-7.PubMedCrossRefGoogle Scholar
- 40.• Fahy BG, Vasilopoulos T, Bensalem-Owen M, Chau DF. Evaluating an interdisciplinary EEG initiative on in-training examination EEG-related item scores for anesthesiology residents. J Clin Neurophysiol. 2018:1. This study is the most recent of a series of publications outlining a successful innovative approach to teaching EEG to anesthesia residents using an interdisciplinary approach. Google Scholar
- 41.• Weber D, McCarthy D, Pathmanathan J. An effective automated method for teaching EEG interpretation to neurology residents. Seizure. 2016;40:10–2. This study demonstrated that engagement with an automated platform improved resident performance in EEG interpretation, and can be a useful tool in supplementing resident learning. PubMedCrossRefGoogle Scholar
- 44.•• Malakooti MR, McBride ME, Mobley B, Goldstein JL, Adler MD, McGaghie WC. Mastery of status epilepticus management via simulation-based learning for pediatrics residents. J Grad Med Educ. 2015;7(2):181–6. This study demonstrated the deliberate practice in a high-fidelity simulation setting allowed pediatrics residents to achieve mastery and increased self-efficacy in the management of children with status epilepticus. PubMedPubMedCentralCrossRefGoogle Scholar
- 48.Fernandez A. Personal Communication. 2018.Google Scholar
- 50.Roy S, Kiral-Kornek I, Harrer S. Deep learning enabled automatic abnormal EEG identification. Conf Proc IEEE Eng Med Biol Soc. 2018;2018:2756–9.Google Scholar
- 53.Lamberink HJ, Otte WM, Geerts AT, Pavlovic M, Ramos-Lizana J, Marson AG, et al. Individualised prediction model of seizure recurrence and long-term outcomes after withdrawal of antiepileptic drugs in seizure-free patients: a systematic review and individual participant data meta-analysis. Lancet Neurol. 2017;16(7):523–31.PubMedCrossRefGoogle Scholar
- 54.van Diessen E, Lamberink HJ, WOM O, Doornebal N, Brouwer OF, Jansen FE, et al. A prediction model to determine childhood epilepsy after 1 or more paroxysmal events. Pediatrics. 2018;142(6).Google Scholar