Feasibility and usability of remote monitoring in Alzheimer's disease

Journal article

Introduction

Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants.

Methods

For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews.

Results

Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible.

Conclusions

This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

Authors: Muurling, M; de Boer, C; Hinds, C; Atreya, A; Doherty, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: SAGE Publications
• Journal: Digital Health
• Volume: 10
• Place of publication: United States
• Publication date: 2024-04-09
• Acceptance date: 2024-02-22
• DOI: 10.1177/20552076241238133
• EISSN: 2055-2076
• Pmid: 38601188
• Language: English
• Keywords: remote clinical trials ≺ studies; remote patient monitoring; RADAR-AD consortium; eHealth ≺ general; dementia ≺ disease; neurology ≺ medicine; wearables ≺ personalised medicine; apps ≺ personalised medicine; digital health ≺ general; Alzheimers ≺ disease