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Stroke. 1997;28:2155-2161

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(Stroke. 1997;28:2155-2161.)
© 1997 American Heart Association, Inc.


Articles

A Stroke-Adapted 30-Item Version of the Sickness Impact Profile to Assess Quality of Life (SA-SIP30)

A. van Straten, MS; R. J. de Haan, RN, PhD; M. Limburg, MD, PhD; J. Schuling, MD, PhD; P. M. Bossuyt, PhD; G. A. M. van den Bos, PhD

From the Department of Social Medicine (A. van S., G.A.M. van den B.), Department of Clinical Epidemiology and Biostatistics (R.J. de H., P.M.B.), and Department of Neurology (A. van S., M.L.), Academic Medical Center, University of Amsterdam (the Netherlands), and the Department of General Practice (J.S.), University of Groningen (the Netherlands).

Correspondence to A. van Straten, MS, Department of Social Medicine, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, Netherlands. E-mail a.vanstraten{at}amc.uva.nl

Background and Purpose In view of the growing therapeutic options in stroke, measurement of quality of life has become increasingly relevant as an outcome parameter. The Sickness Impact Profile (SIP) is one of the most widely used measures to assess quality of life. To overcome the major disadvantage of the SIP, its length, we constructed a short stroke adapted 30-item SIP version (SA-SIP30).

Methods Data on the original SIP version were collected for 319 communicative patients at 6 months after stroke. The 12 subscales and the 136 items of the original SIP were reduced to 8 subscales with 30 items in a three step procedure, on the basis of relevancy and homogeneity. Reliability of the SA-SIP30 was evaluated by means of an analysis of homogeneity (Cronbach's {alpha} coefficient). Different types of validity were assessed: construct, clinical, and external validities.

Results Homogeneity of the SA-SIP30 was demonstrated by a high Cronbach's {alpha} (0.85). Principal component analyses revealed the same two dimensions as in the original SIP (a physical and a psychosocial dimension). The SA-SIP30 could explain 91% of the variation in scores of the original SIP in the same cohort of patients, and 89% in a different cohort. Furthermore, the SA-SIP30 was related to other functional health measures similar to how the original SIP was. We could demonstrate that the SA-SIP30 was able to distinguish patients with lacunar infarctions from patients with cortical or subcortical lesions.

Conclusions We conclude that the SA-SIP30 is a feasible and clinimetrically sound measure to assess quality of life after stroke.


Key Words: quality of life • stroke outcome • stroke assessment




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