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Accuracy of a commonly used mobile ophthalmology application’s vision assessment tools in measuring five vision assessment parameters

Eye (2024)Cite this article

Subjects

Abstract

Background/Objectives

The use of mobile ophthalmology applications (MOA) is increasing, but many of these tools have not been validated. This study was performed to assess the accuracy of a popular MOA, Eye Handbook, in measuring five commonly-tested vision assessment parameters (distance visual acuity (DVA), near visual acuity (NVA), colour vision testing (CVT), contrast sensitivity (CS), and pupillary distance (PD)) was compared with traditional vision assessment methods (TVAM) [i.e. Snellen chart, Rosenbaum near card, Ishihara, Pelli Robson test, etc.] performed in the eye clinic setting.

Subjects/Methods

Prospective crossover clinical trial of 129 patients meeting inclusion criteria.

Results

Participants averaged significantly better DVA (p = 0.0008), NVA (p < 0.0001), and CVT (p = 0.0105) in the MOA than the TVAM, but all three MOA assessments were predictive of the TVAM values. CS was significantly better with the MOA (p < 0.0001). Linear regression and Spearman correlation tests were applied to assess the effect of CS on NVA, which showed no clear relationship between the difference in NVA and the difference in CS. PD using the two methods was in agreement with no significant difference (p = 0.2889).

Conclusion

The studied MOA offers an effective means of measuring four common vision parameters: DVA, NVA, CVT, and PD. The MOA can potentially be used by eye care providers, health care providers, and patients, both as a screening tool with correction factor and to monitor ocular pathologies. Atypical MOA measurements should prompt testing in the clinic with formal TVAMs.

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Data availability

The data collected and analysed in this study are not publicly available due to institutional policy and concerns for protecting protected health information (PHI). However, de-identified datasets can be shared with reasonable requests made in writing to the corresponding author. These requests will be reviewed and are subject to subsequent institutional administration approval for the release of the data sets.

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Acknowledgements

Jibran Sharieff, MD (PGY-1 ophthalmology resident at Dean McGee Eye Institute) assisted with instruction on testing methods and manuscript editing.

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Author notes

  1. These authors contributed equally: Austin Raney, Savannah Cottom.

Authors and Affiliations

  1. Department of Ophthalmology, Dean McGee Eye Institute, University of Oklahoma Health Sciences Center, 608 Stanton L. Young Blvd, Oklahoma City, OK, 73104, USA

    Austin Raney, Savannah Cottom, Jonathan Huff, Tavis Phan, Austin LaGrow, Christian Leal & Kamran M. Riaz

  2. College of Medicine, University of Oklahoma, Norman, OK, USA

    Austin Raney, Savannah Cottom, Jonathan Huff & Tavis Phan

  3. Department of Ophthalmology, Emory University, 100 Woodruff Circle, Atlanta, GA, 30322, USA

    Christian Leal

  4. Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

    Justin D. Dvorak

Authors
  1. Austin Raney
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  2. Savannah Cottom
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  3. Jonathan Huff
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  4. Tavis Phan
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  5. Austin LaGrow
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  6. Christian Leal
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  8. Kamran M. Riaz
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Contributions

AR and SC were responsible for supervising and conducting the research; extracting and analysing data; interpreting results; and writing the first draft of the manuscript. JH, TP, AL, and CL were responsible for conducting the data gathering; extracting and analysing the data; and creating tables and figures. JDD was responsible for the primary statistical analysis for the study. KMR was responsible for supervising all study participants; reviewing the collected data; and editing and finalizing the submitted final draft of the manuscript.

Corresponding author

Correspondence to Kamran M. Riaz.

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The authors declare no competing interests.

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Raney, A., Cottom, S., Huff, J. et al. Accuracy of a commonly used mobile ophthalmology application’s vision assessment tools in measuring five vision assessment parameters. Eye (2024). https://doi.org/10.1038/s41433-024-03315-7

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  • DOI: https://doi.org/10.1038/s41433-024-03315-7

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