User-Centred Design and Development of a Smartphone Application () for Digital Phenotyping in Ophthalmology

Overview

Journal Healthcare (Basel)

Specialty Health Services

Date 2025 Jan 8

PMID 39765977

Authors

Kishan Devraj

Lee Jones

Bethany Higgins

Peter B M Thomas

Mariya Moosajee

Affiliations

Soon will be listed here.

Abstract

Background: Visual impairment can significantly impact an individual's daily activities. Patients require regular monitoring, typically occurring within hospital eye services. Capacity constraints have necessitated innovative solutions to improve patient care. Existing digital solutions rely on task-based digital home monitoring such as visual acuity testing. These require active involvement from patients and do not typically offer an indication of quality of life. Digital phenotyping refers to the use of personal digital devices to quantify passive behaviour for detecting clinically significant changes in vision and act as biomarkers for disease. Its uniqueness lies in the ability to detect changes passively. The objective was to co-design an accessible smartphone app () for the purposes of digital phenotyping in people with sight impairment.

Methods: Development of included stakeholder consultations following principles of user-centred design. Apple iOS software frameworks (HealthKit, ResearchKit, and SensorKit) and a SwiftUI developer toolkit were used to enable the collection of active and passive data streams. Accessibility and usability were assessed using the System Usability Scale (SUS) and feedback following a 3-month pilot study. Consultations with patients informed the design of , including preferred survey scheduling and the relevancy of patient support resources.

Results: Twenty visually impaired participants (mean age 42 ± 19 years) were recruited to the pilot study. The average score on the SUS was 76.8 (±8.9), indicating good usability. There was a statistically significant moderate negative correlation between SUS scores and visual acuity in both the better (r = -0.494; ≤ 0.001) and worse eye (r = -0.421; ≤ 0.001).

Conclusions: offers promising potential for collecting patient-generated health data for the purposes of digital phenotyping in patients with eye disease. Through further testing and validation, this novel approach to patient care may ultimately provide opportunities for remote monitoring in ophthalmology.

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