Self-reported assessment of dry eye in a population-based setting

Research output: Contribution to journalArticle

Abstract

Purpose. To report on a subjective dry eye assessment method for use in large-scale research, to evaluate its application in a population-based study of dry eye among elderly persons in the United States, and to apply novel techniques to improve simple questionnaire item summaries. Methods. A dry eye questionnaire was administered to a population-based sample of 2520 volunteers ages 65 to 84 years in Salisbury, Maryland. Individual symptoms and signs, counts of symptoms and signs, and latent class model summary of item responses were evaluated for validity and internal consistency. Results. Approximately 15% of participants reported experiencing one or more of six dry eye symptoms often or all the time; 90% reported experiencing three or more symptoms sometimes, often or all the time. Four groups were derived on the basis of symptomatology, using latent class analysis. The groups exhibited face validity, revealed symptom patterns that added specificity to simple symptom counts, and were qualitatively similar when derived separately within population subgroups. Internal consistency was moderate (Cronbach's alpha = 0.61), indicating some variability in reporting. Conclusions. Dry eye symptoms are commonly reported in a representative elderly population. Symptom data were moderately consistent, suggesting their usefulness for dry eye assessment if properly summarized. A latent class summary revealed biologically meaningful summary patterns of symptoms reported in this population and holds promise for use in risk factor investigations and in clinical trials.

Original languageEnglish (US)
Pages (from-to)2469-2475
Number of pages7
JournalInvestigative Ophthalmology and Visual Science
Volume38
Issue number12
StatePublished - Nov 1 1997

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Keywords

  • Aging
  • Diagnosis
  • Dry eye
  • Epidemiology
  • Latent class analysis

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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