BMC Neurology (Dec 2022)

Novel insights regarding the measurement properties of the SCOPA-AUT

  • Albert Westergren,
  • Klas Wictorin,
  • Oskar Hansson,
  • Peter Hagell

DOI
https://doi.org/10.1186/s12883-022-03008-2
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 10

Abstract

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Abstract Background The Scale for Outcomes in Parkinson’s disease for Autonomic symptoms (SCOPA-AUT) is an instrument intended to assess overall and domain-specific autonomic symptom burden. In this study the SCOPA-AUT is translated into Swedish and its measurement properties are assessed. Methods Following translation the SCOPA-AUT was field-tested regarding comprehensibility, relevance, and respondent burden (n = 20). It was then tested according to Rasch measurement theory using data from 242 persons with PD, of whom 162 completed SCOPA-AUT at baseline and 1–2 years later, giving a total of 404 data points for analysis. Results The Swedish SCOPA-AUT took a mean of 6 min to complete and was considered easy to use and relevant by respondents. SCOPA-AUT exhibited acceptable Rasch model fit, represents more severe levels of dysautonomia than that reported by the sample, and response categories were not working as expected for 17 items. Local dependency was identified and followed a pattern resembling the suggested subscales. Accounting for the subscale structure eliminated local dependency and reduced the initially inflated reliability from 0.81 to 0.68. Conclusions The SCOPA-AUT is useful as a clinical check-list but requires further developmental work in order to meet more rigorous standards as an outcome measurement instrument.

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