Employing mHealth Applications for the Self-Assessment of Selected Eye Functions and Prediction of Chronic Major Eye Diseases among the Aging Population

Abstract

In the epoch of advanced mHealth (mobile health) use in ophthalmology, there is a scientific call for regulating the validity and reliability of eye-related apps. For a positive health outcome that works towards enhancing mobile-application guided diagnosis in joint decision-making between eye specialists and individuals, the aging population should be provided with a reliable and valid tool for assessment of their eye status outside the physician office. This interdisciplinary study aims to determine through hypothesis testing validity and reliability of a limited set of five mHealth apps (mHAs ) and through binary logistic regression the prediction possibilities of investigated apps to exclude the four major eye diseases in the particular demographic population. The study showed that 189 aging adults (45- 86 years old) who did complete the mHAs’ tests were able to produce reliable results of selected eye function tests through four out of five mHAs measuring visual acuity, contrast sensitivity, red desaturation, visual field and Amsler grid in comparison with a “gold standard” - comprehensive eye examination. Also, part of the participants was surveyed for assessing the Quality of Experience on mobile apps. Understanding of current reliability of existing eye-related mHAs will lead to the creation of ideal mobile application’ self-assessment protocol predicting the timely need for clinical assessment and treatment of age-related macular degeneration, diabetic retinopathy, glaucoma and cataract. Detecting the level of eye function impairments by mHAs is cost-effective and can contribute to research methodology in eye diseases’ prediction by expanding the system of clear criteria specially created for mobile applications and provide returning significant value in preventive ophthalmology.