June 2015
Volume 56, Issue 7
ARVO Annual Meeting Abstract  |   June 2015
Development of a Reading Accessibility Index using the MNREAD acuity chart.
Author Affiliations & Notes
  • Aurelie Calabrese
    Psychology, University of Minnesota, Minneapolis, MN
  • Sing-Hang Cheung
    Psychology, The University of Hong Kong, Hong Kong, Hong Kong
  • Yihan Yang
    School of Statistics, University of Minnesota, Minneapolis, MN
  • Yangfan Qin
    School of Statistics, University of Minnesota, Minneapolis, MN
    Computer Science and Engineering, University of Minnesota, Minneapolis, MN
  • Gerald McGwin
    Epidemiology, University of Alabama at Birmingham, Birmingham, AL
    Ophthalmology, University of Alabama at Birmingham, Birmingham, AL
  • Cynthia Owsley
    Ophthalmology, University of Alabama at Birmingham, Birmingham, AL
  • Gordon E Legge
    Psychology, University of Minnesota, Minneapolis, MN
  • Footnotes
    Commercial Relationships Aurelie Calabrese, None; Sing-Hang Cheung, None; Yihan Yang, None; Yangfan Qin, None; Gerald McGwin, None; Cynthia Owsley, None; Gordon Legge, Precision Vision (P)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 4788. doi:https://doi.org/
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Aurelie Calabrese, Sing-Hang Cheung, Yihan Yang, Yangfan Qin, Gerald McGwin, Cynthia Owsley, Gordon E Legge; Development of a Reading Accessibility Index using the MNREAD acuity chart.. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):4788. doi: https://doi.org/.

      Download citation file:

      © ARVO (1962-2015); The Authors (2016-present)

  • Supplements

Purpose: We define a new measure of reading accessibility, primarily intended for evaluating low-vision reading. We illustrate this measure with data from the Impact of Cataracts on Mobility (ICOM) study (Owsley et al, JAMA, 2002).

Methods: The reading accessibility index (AI) is defined as a subject’s average reading speed in words/min on the MNREAD acuity chart over the print size range from 0.4 to 1.3 logMAR corresponding to physical x-heights of 1.46 to 11.8 mm, normalized by the average value for a group of 78 normally sighted young adults. This is the range of print size for which reading speed is maximum for normally sighted subjects, and contains the vast majority of published printed material (Legge & Bigelow, J. Vis., 2011). The AI is intended to capture both the range of accessible print sizes for a subject, and the subject’s speed (fluency) of reading within the range in a single-valued measure. Changes in a subject’s AI can be used to evaluate the impact of ophthalmic treatment, rehabilitation program or assistive technology on reading accessibility. We calculated AI values from MNREAD data collected in subjects with cataracts (N=92), with pseudophakia (N=131) and with crystalline lenses but no cataract (N=98), who participated in the ICOM study. Correlation coefficients were calculated for the association between AI and letter acuity, contrast sensitivity, and reading-related performance on Timed Instrumental Activities of Daily Living (TIADL).

Results: AI values of the ICOM subjects ranged from 0.21 to 1.23, where a value of 0 means no reading within the accessible range, and 1 is the normal average. The mean AI (± SD) for the cataract group (0.66 ± 0.17) was significantly lower (p<0.001) than for either the pseudophakia group (0.77 ± 0.15) or the no cataract group (0.77 ± 0.13). Overall, the correlation between AI and letter acuity (r=0.27, p<0.01) and contrast sensitivity (r=0.29, p<0.01) was weaker than with the TIADL measure (r=0.68, p<0.01).

Conclusions: The Reading Accessibility Index is a new measure representing a subject’s access to text over the range of print sizes found in everyday life. Its calculation has the advantages that it does not rely on curve fitting, and it gives a direct comparison with the performance of normally sighted individuals. Results from the ICOM dataset imply that the AI reflects characteristics of reading performance in everyday life and may be sensitive to cataract surgery.


This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.