Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Dec 4, 2020
Date Accepted: Oct 1, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Vision Screening and Self-Testing by Mobile-Based Automated Visual Acuity Assessments Apps: A Systematic Review with Meta-Analysis
ABSTRACT
Background:
Vision impairments (VI) and blindness are one of the core global public health issues. Visual acuity (VA) is one of the most crucial standard psychophysical test of visual function, and used widely in a broad range of healthcare domain, especially in many clinical settings.
Objective:
To assess the accuracy and application of using Mobile devices-based visual acuity measurement apps.
Methods:
We searched Pubmed, Embase, Cochrane Library, and Google Scholar for relevant articles published between January 1, 2008 and July 1 2020. Two reviewers independently selected studies that assessed the mobile-based VA measurement apps. We included all studies that assessed a tablet and/or smartphone VA measurement apps.
Results:
Most of the enrolled 22 studies considered as high quality studies, evaluating by QUADAS-2. In meta-analysis, six studies involving 24284 participants were included. In 3~5 years old group, the pooled sensitivity was 0.87 (95% CI 0.79, 0.93); the pooled specificity was 0.78 (95% CI 0.70, 0.85); In 6~22 years old group, the pooled sensitivity was 0.86 (95% CI 0.84, 0.87); the pooled specificity was 0.91 (95% CI 0.90, 0.91). In ≥55 years old group, the pooled sensitivity was 0.85 (95% CI 0.55, 0.98); the pooled specificity was 0.98 (95% CI 0.95, 0.99).
Conclusions:
In this study, we conducted a comprehensive review of the state-of-the-art research to investigate the diagnostic value and limitations of existing mobile-based VA test applications. Evidence from this study shows that mobile-based app VA measurements may be useful tools for VI detection.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.