June 2013
Volume 54, Issue 15
ARVO Annual Meeting Abstract  |   June 2013
Can chronic visual symptoms measures accurately predict acute visual discomfort symptoms?
Author Affiliations & Notes
  • Stefanie Drew
    Psychology, California State University, Northridge, Northridge, CA
  • Amy Escobar
    2U, Inc., Landover, MD
  • Chunming Liu
    College of Optometry, Western University of Health Sciences, Pomona, CA
  • Efrain Castellanos
    College of Optometry, Western University of Health Sciences, Pomona, CA
  • Lawrence Stark
    Southern California College of Optometry, Fullerton, CA
  • Eric Borsting
    Southern California College of Optometry, Fullerton, CA
  • Chris Chase
    College of Optometry, Western University of Health Sciences, Pomona, CA
  • Footnotes
    Commercial Relationships Stefanie Drew, None; Amy Escobar, None; Chunming Liu, None; Efrain Castellanos, None; Lawrence Stark, None; Eric Borsting, None; Chris Chase, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 5326. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Stefanie Drew, Amy Escobar, Chunming Liu, Efrain Castellanos, Lawrence Stark, Eric Borsting, Chris Chase; Can chronic visual symptoms measures accurately predict acute visual discomfort symptoms?. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5326.

      Download citation file:

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

  • Supplements

Purpose: Most surveys of discomfort symptoms are retrospective and assess the frequency and severity of chronic conditions. To our knowledge, there are no studies that have shown chronic symptom surveys can predict acute symptoms. We investigated the relationship between chronic visual discomfort and ratings of acute discomfort symptoms after tests of accommodation and vergence.

Methods: Prior to testing accommodation and vergence function, the Conlon visual discomfort survey (Conlon et al., Vis Cogn 1999;6:637-666) assessed chronic visual discomfort symptoms in 38 graduate students. This survey consists of 23 items that address one of five symptom categories (text movement, headache and soreness, blur, reading problems and glare). Acute symptoms were measured with four questions using a five-point rating scale i) discomfort experienced, ii) amount of distortions or movement, iii) discomfort from overhead lights and iv) amount of headache experienced. Binocular function was tested using standard clinical procedures. After a control accommodation facility test using ± 0.12D lens, baseline acute visual discomfort was 5.05 (1.11). A second acute symptom test was made after the binocular exam, producing an average score of 7.63 (3.35). Individuals were classified into High (N=16) or Low (N=22) acute symptom groups with a post-exam cut-off score ≥ 7. A logistic regression analysis was performed with the symptom group as a dependent variable and scores from the Conlon question categories as the independent variables to determine how well the chronic symptom survey predicts acute symptom grouping.

Results: A full model significantly predicted post-exam classification (High or Low) (omnibus chi square = 13.039, df = 5, p = 0.023). This model accounts for between 29.7% and 40.1% of the variance in post-exam performance, with 81.8% of the Low post-exam symptoms correctly predicted and 66.7% of High post-exam symptoms predicted. Overall, 75.7% of predictions were accurate. Examination of the predictor variables revealed that only headache questions reliably predict post-exam symptom group (B = .381, df = 1, p = 0.018).

Conclusions: These data suggest that a chronic symptom survey can make reasonably good predictions about acute symptoms associated with tests of accommodation and vergence and that questions assessing headache and soreness symptoms are the best correlate.

Keywords: 466 clinical (human) or epidemiologic studies: treatment/prevention assessment/controlled clinical trials • 669 quality of life  

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.