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A Simplified Stroke Rehabilitation Assessment of Movement Instrument

IP Hsueh, OT, MA, is Assistant Professor, School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan
WC Wang, PhD, is Professor, Department of Psychology, Chung-Cheng University, Chiayi, Taiwan
CH Wang, PT, BS, is Professor, School of Physical Therapy, College of Medical Technology, Chung-Shan Medical University, and Department of Physical Therapy, Chung-Shan Medical University Rehabilitation Hospital, Taichung, Taiwan
CF Sheu, PhD, is Professor, Institute of Cognitive Science, National Cheng Kung University, Tainan, Taiwan
SK Lo, PhD, is Professor, Faculty of Health and Behavioral Sciences, Deakin University, Melbourne, Australia
JH Lin, PT, PhD, is Professor, Faculty of Physical Therapy, Kaohsiung Medical University, Kaohsiung, Taiwan
CL Hsieh, OT, PhD, is Professor and Chair, School of Occupational Therapy, College of Medicine, National Taiwan University, and Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, 4F, 17 Shiujou Rd, Taipei 100, Taiwan

(mike26{at}ha.mc.ntu.edu.tw) Address all correspondence to Dr Hsieh

Background and Purpose. An efficient, reliable, and valid instrument for assessing motor function in patients with stroke is needed by both clinicians and researchers. To improve administration efficiency, we applied the multidimensional Rasch model to the 30-item, 3-subscale Stroke Rehabilitation Assessment of Movement (STREAM) instrument to produce a concise, reliable, and valid instrument (simplified STREAM [S-STREAM]) for measuring motor function in patients with stroke. Subjects and Methods. The STREAM (consisting of 3 subscales: upper-limb movements, lower-limb movements, and mobility) was administered to 351 subjects with first stroke occurrence and a median time after stroke of 12.5 months. The unidimensionality of each subscale of the STREAM first was verified with unidimensional Rasch analysis. Each subscale of the STREAM then was simplified by deleting redundant items on the basis of expert opinion and the results of the Rasch analysis. The Rasch reliability of the S-STREAM and the concurrent validity of the S-STREAM with the STREAM were examined with multidimensional Rasch analysis and the intraclass correlation coefficient (ICC), respectively. Results. After deleting the items that did not fit the Rasch model, we found that the 8-item upper-limb movement subscale, the 9-item lower-limb movement subscale, and the 10-item mobility subscale assessed single, unidimensional upper-limb movements, lower-limb movements, and mobility, respectively. We selected 5 items from each subscale to construct the S-STREAM and found that the reliability of each subscale of the resulting simplified instrument was high (Rasch reliability coefficients of .91). The agreement between the subscale scores (Rasch estimates) of the S-STREAM and those of the STREAM was excellent (ICC of .99, with a lower limit for the 95% confidence interval of .985), indicating good concurrent validity of the S-STREAM with the STREAM. Discussion and Conclusion. The S-STREAM demonstrates high Rasch reliability, unidimensionality, and concurrent validity with the STREAM in patients with stroke. Furthermore, the S-STREAM is efficient to administer, as it consists of only half the number of items in the original STREAM. Additional studies to examine other psychometric properties (eg, predictive validity and responsiveness) of the S-STREAM or its psychometric properties in various recovery stages after stroke are needed to further establish its utility in both clinical and research settings.

Key Words: Motor function • Psychometrics • Rasch model • Stroke