To develop an assessment tool for evaluation of competence in routine electroencephalography (rEEG) interpretation.
We recently published common curricular objectives for teaching and assessing rEEG interpretation. Here, we used this curriculum framework to develop and evaluate a multiple-choice examination for adult and child neurology trainees.
An online, anonymous rEEG examination was developed. A previously published curriculum map was used to design 30 single-best-answer multiple choice questions covering four EEG domains: normal, abnormal, normal variants, and artifacts. Each question contained an EEG image displayed in two montages (bipolar and average). Questions were pre-reviewed, modified, and correct answers adjudicated by EEG experts (FAN/RF/SR/WT/SB). Respondents reported their level of confidence (LOC, 5-point scale) with answering questions in each domain. Accuracy and item discrimination were calculated for each question, and LOC for each domain. The test was disseminated by the ILAE and shared on social media.
Of 2,076 responses, 922 were complete. Respondents comprised medical students, neurology residents, EEG/epilepsy fellows, neurology and non-neurology attending physicians, neurophysiologists/epileptologists (experts), technologists, and others. Mean accuracy [95%CI] was 74.4% [73.4-74.4]. Accuracy and LOC correlated with level of experience: experts had highest mean accuracy and LOC; neurology residents performed significantly lower than experts (p=0.002) and fellows (p<0.001), and were significantly less confident than experts and fellows in all 4 domains (all p<0.001). Accuracy was similar for fellows and experts, fellows had lower overall LOC. Among neurology residents, accuracy and LOC correlated with the number of prior weeks of EEG rotation. Accuracy increased progressively from 64% (0 prior EEG weeks) to 75% (>12 prior weeks). All but 3 questions had discrimination index of >0.25.