A web-compatible instrument for measuring self-reported disease activity in arthritis

J Rheumatol. 2004 Feb;31(2):223-8.

Abstract

Objective: To describe a Web-based computer health assessment survey for patients with rheumatoid arthritis (RA) and to evaluate the survey in comparison with current paper versions.

Methods: Utilizing data from a study on RA, we compared results from 43 patients attending a university-based clinic who were each given a paper and a demonstration computer version of a patient self-assessment questionnaire including multiple-choice questions from a multi-dimensional Health Assessment Questionnaire (HAQ); visual analog scales (VAS) for pain, fatigue, and global disease severity; and a tender and swollen joint count reporting tool. Patients were given optional followup surveys to determine their opinion of the computer program.

Results: High correlations (intraclass correlation coefficient > 0.9) were seen across methods for the 10-item HAQ and psychological distress scores and the VAS scores for pain and global disease severity. Moderate correlation was observed for the self-efficacy scores, the VAS scores for fatigue, and tender joint counts. The data also revealed a small shift in the mean scores for the HAQ and self-efficacy questions, with patients reporting slightly higher scores on the computer instrument. Overall, patient opinions of the uniquely designed joint count tool were good, with 71% of responding patients answering favorably.

Conclusion: Web-based computer versions of patient self-assessment surveys in RA are comparable to paper versions, and their use in clinics or over the Internet could dramatically facilitate the ability of physicians to monitor patients' health.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Arthritis, Rheumatoid / diagnosis*
  • Female
  • Health Status Indicators*
  • Health Surveys
  • Humans
  • Internet*
  • Male
  • Microcomputers
  • Middle Aged
  • Pain Measurement
  • Reproducibility of Results
  • Software