OBJECTIVE: Previous studies identified essential user preferences for seizure detection devices (SDDs), without addressing their relative strength. We performed a discrete choice experiment (DCE) to quantify attributes' strength, and to identify the determinants of user SDD preferences.METHODS: We designed an online questionnaire targeting parents of children with epilepsy to define the optimal balance between SDD sensitivity and positive predictive value (PPV) while accounting for individual seizure frequency. We selected five DCE attributes from a recent study. Using a Bayesian design, we constructed 11 unique choice tasks and analyzed these using a mixed multinomial logit model.RESULTS: One hundred parents responded to the online questio...
Background: A targeted treatment approach is increasingly promoted in epilepsy management. Aim: To i...
This qualitative study investigated factors that guide caregiver decision making and ethical trade-o...
Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (...
OBJECTIVE: Previous studies identified essential user preferences for seizure detection devices (SDD...
Objective Previous studies identified essential user preferences for seizure detection devices (SDDs...
Background: Diagnosing epilepsy is a lengthy and burdensome process for patients and their family. A...
Introduction: User preferences for seizure detection devices (SDDs) have been previously assessed us...
ObjectiveNovel and minimally invasive neurotechnologies offer the potential to reduce the burden of ...
Introduction: User preferences for seizure detection devices (SDDs) have been previously assessed us...
Background: There is an increasing number of self-management programs developed for patients with ep...
Objective: To assess the performance of a multimodal seizure detection device, first tested in adult...
Introduction: Caring for a child with epilepsy has a significant impact on parental quality of life....
Background: Discrete Choice Experiments (DCEs) are increasingly used in studies in healthcare resear...
Objectives: There is a growing interest in eliciting stated preferences from patients or other harde...
Background. In paediatric epilepsy, the evidence of effectiveness of antiseizure treatment is inconc...
Background: A targeted treatment approach is increasingly promoted in epilepsy management. Aim: To i...
This qualitative study investigated factors that guide caregiver decision making and ethical trade-o...
Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (...
OBJECTIVE: Previous studies identified essential user preferences for seizure detection devices (SDD...
Objective Previous studies identified essential user preferences for seizure detection devices (SDDs...
Background: Diagnosing epilepsy is a lengthy and burdensome process for patients and their family. A...
Introduction: User preferences for seizure detection devices (SDDs) have been previously assessed us...
ObjectiveNovel and minimally invasive neurotechnologies offer the potential to reduce the burden of ...
Introduction: User preferences for seizure detection devices (SDDs) have been previously assessed us...
Background: There is an increasing number of self-management programs developed for patients with ep...
Objective: To assess the performance of a multimodal seizure detection device, first tested in adult...
Introduction: Caring for a child with epilepsy has a significant impact on parental quality of life....
Background: Discrete Choice Experiments (DCEs) are increasingly used in studies in healthcare resear...
Objectives: There is a growing interest in eliciting stated preferences from patients or other harde...
Background. In paediatric epilepsy, the evidence of effectiveness of antiseizure treatment is inconc...
Background: A targeted treatment approach is increasingly promoted in epilepsy management. Aim: To i...
This qualitative study investigated factors that guide caregiver decision making and ethical trade-o...
Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (...