by
Michelle Woodbury;
Craig A. Velozo;
Paul A. Thompson;
Kathye Light;
Gitendra Uswatte;
Edward Taub;
Carolee J. Winstein;
David Morris;
Sarah Blanton;
Deborah S. Nichols-Larsen;
Steven Wolf
Background. Tools chosen to measure poststroke upper-extremity rehabilitation outcomes must match contemporary theoretical expectations of motor deficit and recovery because an assessmentg's theoretical underpinning forms the conceptual basis for interpreting its score. Objective. The purpose of this study was to investigate the theoretical framework of the Wolf Motor Function Test (WMFT) by (1) determining whether all items measured a single underlying trait and (2) examining the congruency between the hypothesized and the empirically determined item difficulty orders. Methods. Confirmatory factor analysis (CFA) and Rasch analysis were applied to existing WMFT Functional Ability Rating Scale data from 189 participants in the EXCITE (Extremity Constraint-Induced Therapy Evaluation) trial. Fit of a 1-factor CFA model (all items) was compared with the fit of a 2-factor CFA model (factors defined according to item object-grasp requirements) with fit indices, model comparison test, and interfactor correlations. Results. One item was missing sufficient data and therefore removed from analysis. CFA fit indices and the model-comparison test suggested that both models fit equally well. The 2-factor model yielded a strong interfactor correlation, and 13 of 14 items fit the Rasch model. The Rasch item difficulty order was consistent with the hypothesized item difficulty order. Conclusion. The results suggest that WMFT items measure a single construct. Furthermore, the results depict an item difficulty hierarchy that may advance the theoretical discussion of the person ability versus task difficulty interaction during stroke recovery.
Background. Efficacy of task-oriented training can be reliably trusted only when the inherent measurement variability is determined. The Actual Amount of Use Test (AAUT) and the Motor Activity Log (MAL) have been used together as measures of spontaneous arm use after an intervention; however, the minimal detectable change (MDC) of AAUT and MAL has not been addressed. Objective. To compare the MDC90 of the AAUT and the MAL in the context of a randomized controlled trial of a neurorehabilitation intervention, the Extremity Constraint-Induced Therapy Evaluation trial. Methods. A preplanned secondary analysis was conducted using pre-post test data from the control group. Estimated MDC90 were normalized to the maximum value of the scale of the AAUT and the MAL for each subscale: amount of use (AAUTa, MALa) and quality of movement (AAUTq, MALq). Results. The MDC90 of the AAUTq and the MALq were 14.4% and 15.4%, respectively. However, the MDC90 required greater change for the AAUTa (24.2%) than the MALa (16.8%). The training-induced spontaneous arm use exceeded the MDC90 for the MAL but fell below that for the AAUT immediately after the intervention and at 1-year follow-up visit. Conclusions. The greater variability and insensitivity to treatment effect for the AAUTa is likely because of the low resolution of its scoring system. As such, there is a considerable need to develop valid and reliable tools that capture purposeful arm use outside the laboratory, perhaps through leveraging new sensing technologies with objective activity monitoring.