Feasibility of smartphone-based digital phenotyping to measure visual function and mental health outcomes in patients with inherited retinal diseases

This study evaluated the feasibility of collecting passive and active digital phenotyping data using the OverSight iOS application in individuals with inherited retinal diseases (IRDs), and explored associations between digital behavioural markers, visual function and mental health. Participants with IRDs were recruited from Moorfields Eye Hospital (UK) and followed for 12 months. OverSight passively captures mobility data through HealthKit and typing-derived metrics through SensorKit. Participants completed patient-reported outcome measures (EQ-5D, NEI-VFQ-25, HADS and MRDQ) within the app. Passive data included step count, walking speed, typing speed, total words typed, autocorrections, and sentiment word categories (anxiety, down and health-related terms). Feasibility indices included enrolment, retention and completeness of passive datastreams. Twenty-five participants were enrolled, and 92% were retained at 12 months. Seventeen participants met the validity threshold for HealthKit data, and 16 also met SensorKit thresholds. Median daily step count was 6087, walking speed 1.18 m/s and typing speed 2.19 characters/s. Age was negatively correlated with typing speed and anxiety-related word use, and photopic peripheral visual difficulty was negatively correlated with anxiety- and down-related word use. Digital phenotyping using OverSight was feasible over 12 months. Exploratory analyses suggest mobility, typing behaviour and sentiment markers may represent useful adjunctive indicators of functional vision and psychological status. These data may support remote monitoring and earlier identification of clinically relevant changes, informing more timely personalised patient management in IRDs.