MNREAD iPad app

As a post-doc at the University of Minnesota, I have been leading a team constituted of researchers, clinicians and a developer to create the MNREAD app ©2017, a tablet version of the MNREAD acuity chart.

The MNREAD app was designed to include the primary MNREAD layout and linguistic principles, with the main differences that reading stimuli are displayed on a screen and that MNREAD parameters are estimated automatically in real time.

In Calabrèse et al., (2018), the MNREAD app was validated by testing a large sample of normally sighted participants, including children and older adults (N=165) and a low-vision sample of participants with a wide range of visual impairment (N=43). Overall, MNREAD parameters measured with the printed chart and the iPad app were found to be comparable, proving the reliability of the app.

MNREAD iPad app testing sequence

Available through the App Store since March 2017 in several languages, the MNREAD app has been patented by the University of Minnesota. A comprehensive user manual is also available here.

Compared to the printed version, the MNREAD app presents some significant improvement:

  • Increased inter-tester reliability, thanks to more consistent sentence display, more accurate timing measurement and unified methods for parameter estimation.
  • Significantly shorter testing time thanks to a smoother and quicker way of administration paired with an instantaneous presentation of the results. Such time saving can be especially valuable in clinics where many patients need to be seen.
  • Easy data sharing and increased portability, with several test versions available within a single device.
  • Possibility for self-administration: patients can launch and stop a trial with a simple click, automatically recording their reading time. Self-administration is a positive feature that helps motivate and engage patients during testing.

Overall, the major advantage of this digital reading test is to provide more uniform automated methods for measuring reading performance and therefore help standardize reading assessment. Thanks to its digital implementation, it will also be possible to generalize the MNREAD principles to evaluate the effects on reading of dependent variables other than print size e.g., typeface, letter spacing and line length.

mnreadR: an R package to analyse MNREAD data

In an effort to improve standardization of MNREAD results interpretation, I developed the R language package mnreadR to assist researchers and clinicians in analyzing data obtained with the MNREAD test.

In short, mnreadR provides functions to:

  • Plot MNREAD curves automatically,
  • Estimate all four MNREAD parameters with automated algorithms, including both:
    • the original algorithm described in Legge, 2007
    • non-linear mixed effect (NLME) modeling (Cheung, Kallie et al., 2008)

The unique contribution of this software package is to provide an automated framework to compute all necessary MNREAD calculations in R and therefore facilitate MNREAD data analyses in both clinical and research environments. Because mnreadR relies on user-friendly functions using basic R language, it constitute an excellent tool to fully analyze the data collected with the MNREAD acuity chart, even with very minimal knowledge of R.

Since its first release on CRAN in July 2017, I have tried to keep implementing new functions to the mnreadR package. Please feel free to contact me if you encounter any issues or have suggestions for improvement!