Investigating mechanisms and monitoring outcomes in functional neurological disorder: the unrealized potential of digital remote monitoring technologies.

Authors

Susannah Pick, Matthew Hotopf

Published in

Philosophical transactions of the Royal Society of London. Series B, Biological sciences. Volume 381. Issue 1958. Sep 17, 2026.

Abstract

Functional neurological disorder (FND) is characterized by involuntary, distressing neurological symptoms that are distinguishable from other neurological diagnoses in presentation, aetiology and mechanisms. Significant disability, impaired quality-of-life and substantial healthcare resource utilization often result from the disorder, yet its underlying mechanisms have not been proven empirically. Importantly, long-term clinical trajectories and predictive markers have been understudied in FND cohorts. Inadequate funding of large-scale mechanistic and longitudinal research, methodological limitations and the absence of standardized outcome measures necessitate development of innovative solutions. Digital remote monitoring technologies (dRMTs), which have been shown to be valuable across a range of other neurological and psychiatric disorders, may have substantial potential to address these research challenges in FND, yet this potential is currently unrealized. We propose that dRMTs could be harnessed to monitor subjective and/or objective functional neurological and associated symptoms, mechanistic variables and important outcome domains, with excellent temporal precision, flexibility and external validity. These methods could allow precise characterization of both short- and long-term fluctuations in FND symptoms, the influences on them and their impact on patients. Such data would strengthen mechanistic models, improve outcome prediction and facilitate personalized FND clinical management in this underserved population. This article is part of the discussion meeting issue 'Digital healthcare for the management of functional neurological disorders'.

PMID:
42750446
Bibliographic data and abstract were imported from PubMed on 17 Sep 2026.

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