Explaining the Unknown: Causal Illness Beliefs Among People with Epilepsy of Unknown Cause
Abstract number :
3.397
Submission category :
16. Epidemiology
Year :
2023
Submission ID :
1157
Source :
www.aesnet.org
Presentation date :
12/4/2023 12:00:00 AM
Published date :
Authors :
Presenting Author: John Wetmore, MPH – Columbia University Mailman School of Public Health
Itzel Camarillo, BA – Columbia University Irving Medical Center; Wendy Chung, MD – Columbia University Irving Medical Center; Cheng-Shiun Leu, PhD – Columbia University Irving Medical Center; Karolynn Siegel, PhD – Columbia University Irving Medical Center; Jo Phelan, PhD – Columbia University Irving Medical Center; Lawrence Yang, PhD – New York University School of Global Public Health; Hyunmi Choi, MD – Columbia University Irving Medical Center; Ruth Ottman, PhD – Columbia University Irving Medical Center
Rationale:
About two-thirds of people with epilepsy have no identified cause of their condition. Since causal illness beliefs (“attributions”) can affect patient-important outcomes like medication adherence and mental health, we explored how clinical features predicted causal attributions of epilepsy.
Methods:
At a large, urban academic medical center, we surveyed 644 patients with epilepsy of unknown cause from 2019 to 2022 and abstracted data from their medical records. Clinical features of epilepsy included family history of epilepsy, number of lifetime seizures, time since last seizure, current treatment regimen, epilepsy type, and age at epilepsy onset. Patients completed the revised Illness Perception Questionnaire, in which they rated the likelihood that each of 17 items was a cause of their epilepsy (1-4, “very unlikely” to “very likely”). We collapsed causal attributions into five factors: genetics, psychosocial, non-genetic biological, fate, and chance. In a free-response question, patients named what they believed was the most important cause of their epilepsy. We calculated associations between predictors and causal attributions using generalized linear and multinomial logistic regression models controlling for age, sex, race/ethnicity, education. All clinical features were included in the generalized linear regression models to evaluate the independent effect of each on causal attributions.
Results:
People with a family history of epilepsy rated genetics as a more likely cause of their epilepsy than people without a family history (adjusted mean [aM]: 2.9 vs. 2.0, p< 0.001), and were less likely to endorse chance (aM: 2.0 vs. 1.8, p=0.04). Those with generalized epilepsy also rated genetics as a more likely cause than those with focal epilepsy (aM: 2.6 vs. 2.3, p < 0.001). Patients whose last seizure was less than a year ago rated psychosocial factors as more likely causes of their epilepsy than those whose last seizure was a year ago or more (aM: 1.5 vs. 1.3, p< 0.001); they also rated non-genetic biological factors as more likely causes (aM: 1.8 vs. 1.7, p=0.02).
Epidemiology