To investigate the face validity (technology fit and user need) of typing behaviour to detect disease related changes in people with multiple sclerosis (MS).

Evidence about acceptability and face validity of mobile health solutions that measure smartphone interactions are lacking. Technology matched to patient needs and symptoms can potentially increase study compliance and data quality, improving measurement of clinical outcomes.

223 Dutch MS patients with mixed subtype diagnoses (67.7% RRMS), ages (44.2 (23-66) years) and genders (79.8% female) were recruited together with PlatformMS. Participants first read a description of the technology developed by Neurocast B.V., followed by questions regarding symptom experiences since diagnosis and desire to use this technology. A questionnaire concerning typing behaviour related to six symptom domains (cognition, social, emotion, arm/hand function, sleep, and fatigue) using 19 5-point Likert scale questions per domain was conducted. Median responses were grouped thematically as 1) social or language use 2) processing time, error, and speed, and 3) phone interaction.

When asked whether they experienced more problems with these endpoints since diagnosis, participants agreed most strongly with fatigue (87.9%), cognition (76.9%) and arm/hand function (71.4%). Participants agreed an app measuring keyboard interaction could most likely measure arm/hand function (76.9%), cognition (72.9%) and fatigue (67.7%).

During difficulties with cognition, fatigue, arm/hand function and sleep participants agreed they need more processing time, make more errors and typed slower. (median responses = 3.9, 4.0, 3.8, 3.7 respectively). There was high disagreement with questions focused on decreasing social and language behaviours (2.1, 2.2, 2.2, 2.4 respectively). Regarding emotional and social difficulties, participants responded neutrally to all questions.

Considering technology fit and user need, typing behaviour potentially reflects both motor and non-motor symptoms, therefore could represent a promising avenue to monitor MS symptoms unobtrusively and passively in daily life.