Much More Than the Malady: The Promise of a Web-Based Digital Platform Incorporating Self-Report for Research and Clinical Care in Mild Cognitive Impairment
Year: 2025
Type: article
Study design: Observational Study
Abstract: Unstructured Abstract: Traditional clinical trials in neurodegenerative disorders have utilized combinations of examination-based outcomes, global assessments by investigators and participants, and scales aimed at function, some of which are patient-reported outcomes (PROs). It is debatable whether these tools optimally convey therapeutic efficacy. A complimentary approach using digital biomarkers to surpass exam-based limitations for detecting physical change coupled to a direct report from participants on what their sources of suffering are could be a useful advance in demonstrating beneficial effects of interventions, particularly if changes track together. We sought to determine the feasibility of remotely assessing speech, facial features and cognition in an MCI population, whether those extracted features could distinguish MCI from controls, and to explore what self-reported problems could reveal about the MCI experience. Our web-based platform was easy to use and revealed facial features in particular as capable of discriminating MCI from controls. Using the features that showed a statistically significant difference between cohorts (p < 0.01) produced an area under the receiver operating curve (ROC) of 0.75. Self-reported problems with cognition, gait, sleep, and behavior were more common in the MCI group. MCI was associated with six times more difficulty with falls (N=6 vs. 1).These data support the feasibility and discriminative utility of using remote monitoring technology in combination with participant self-report in an MCI population. Future work will investigate the extent to which multimodal biomarkers combined with self-report can characterize MCI longitudinally and for potential research applications as a measure of therapeutic effect.
Institutions: Cooper Medical School of Rowan University, Cooper Norcross Health, Rowan University, Nodality (United States), San Francisco VA Medical Center, San Francisco VA Health Care System, Johnson & Johnson (United States), Janssen Research & Development (United States), University of California, San Francisco
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funder: Johnson and Johnson
OpenAlex ID: W4410109362
