April 2010
Volume 51, Issue 13
ARVO Annual Meeting Abstract  |   April 2010
Item Banking for the Measurement of Visual Disability, Symptoms and Quality of Life
Author Affiliations & Notes
  • K. Pesudovs
    NHMRC Ctr Clin Eye Res/Optometry and Vision Science, Flinders University SA, Bedford Park, Australia
  • V. K. Gothwal
    Meera and L B Deshpande Centre for Sight Enhancement, Vision Rehabilitation Centres, L V Prasad Eye Institute, Hyderabad, India
  • T. A. Wright
    NHMRC Ctr Clin Eye Res/Optometry and Vision Science, Flinders University SA, Bedford Park, Australia
  • E. L. Lamoureux
    Ophthalmology, University of Melbourne, Centre for Eye Research Australia, Melbourne, Australia
  • Footnotes
    Commercial Relationships  K. Pesudovs, None; V.K. Gothwal, None; T.A. Wright, None; E.L. Lamoureux, None.
  • Footnotes
    Support  NHMRC Grant 264620, NHMRC Grant 426765, NHMRC grant 359277, ARC grant LP0560779.
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 937. doi:
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      K. Pesudovs, V. K. Gothwal, T. A. Wright, E. L. Lamoureux; Item Banking for the Measurement of Visual Disability, Symptoms and Quality of Life. Invest. Ophthalmol. Vis. Sci. 2010;51(13):937.

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

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Purpose: : The measurement of patient-reported outcomes in ophthalmology using questionnaires is limited by the suitability of content to the population and the scoring properties of the instrument. The aim of this project was to develop broadly-based item banks for the measurement of visual disability, symptoms and quality of life with items calibrated using Rasch analysis.

Methods: : People on the waiting list for cataract surgery at Flinders Medical Centre, South Australia, were invited to participate. Each participant completed, by self-administration, a questionnaire comprising all items considered to represent each latent trait. 353 items were drawn from 19 existing questionnaires, culled for duplication and augmented with additional items representing more difficult visual disability tasks. This resulted in 110 visual disability items, 20 symptoms items and 60 quality of life items. All items were organized on common 5-category rating scales for each trait. Items were tested using Rasch analysis (Winsteps v3.67) and those fitting the model were calibrated and retained in the item bank. Comprehensive demographic data were also collected.

Results: : 110 participants have been recruited to date: 45% were male, 55% female; mean ± SD age was 74.3±9.2 years; 58% had bilateral cataract, 42% were awaiting second eye surgery; 46% had co-morbid eye disease (age-related macular degeneration and glaucoma 17% and 9%, of total respectively) and visual acuity was R 0.24±0.22 (6/9.5--) in the better eye and L 0.58±0.34 (6/24+) in the worse eye. The Rasch model for each latent trait performed adequately (person separation >2.0) with no misfitting items (fit statistic range 0.50 to 1.50). Rasch estimates of item calibrations were generated with an average standard error on the measure of 0.15 logits. Across all three traits, item difficulty was well targeted to participant ability (difference between person and item means <1.0 logits).

Conclusions: : These data represent the initial creation of three item banks to measure visual disability, symptoms and quality of life. Further data collection, across countries and disease groups, is required to generate comprehensive, stable and internationally valid calibrations. Measurement of these three latent traits can be performed using computer adaptive testing facilitating widespread implementation.

Keywords: quality of life • clinical (human) or epidemiologic studies: biostatistics/epidemiology methodology • treatment outcomes of cataract surgery 

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