BACKGROUND AND PURPOSE: Augmenting changes in recovery is core to the rehabilitation process following a stroke. Hence it is essential that outcome measures are able to detect change as it occurs, a property known as responsiveness. This article critically reviewed the responsiveness of functional outcome measures following stroke, specifically examining tools that captured upper-extremity (UE) functional recovery. METHODS: A systematic search of the literature was undertaken to identify articles providing responsiveness data for 3 types of change (observed, detectable, and important). RESULTS: Data from 68 articles for 14 UE functional outcome measures were retrieved. Larger percentage changes were required to be considered important when obtained through anchor-based methods (eg, based on patient opinion or comparative measure) compared with distribution methods (eg, statistical estimates). Larger percentage changes were required to surpass the measurement error for patient-perceived functional measures (eg, Motor Activity Log) compared with laboratory-based performance measures (eg, Action Research Arm Test). The majority of rehabilitation interventions have similar effect sizes on patient-perceived UE function and laboratory-based UE function. CONCLUSIONS: The magnitude of important change or change that surpasses measurement error can vary substantially depending on the method of calculation. Rehabilitation treatments can affect patient perceptions of functional change as effectively as laboratory-based functional measures; however, larger sample sizes may be required to account for the larger measurement error associated with patient-perceived functional measures.
BACKGROUND AND PURPOSE: Augmenting changes in recovery is core to the rehabilitation process following a stroke. Hence it is essential that outcome measures are able to detect change as it occurs, a property known as responsiveness. This article critically reviewed the responsiveness of functional outcome measures following stroke, specifically examining tools that captured upper-extremity (UE) functional recovery. METHODS: A systematic search of the literature was undertaken to identify articles providing responsiveness data for 3 types of change (observed, detectable, and important). RESULTS: Data from 68 articles for 14 UE functional outcome measures were retrieved. Larger percentage changes were required to be considered important when obtained through anchor-based methods (eg, based on patient opinion or comparative measure) compared with distribution methods (eg, statistical estimates). Larger percentage changes were required to surpass the measurement error for patient-perceived functional measures (eg, Motor Activity Log) compared with laboratory-based performance measures (eg, Action Research Arm Test). The majority of rehabilitation interventions have similar effect sizes on patient-perceived UE function and laboratory-based UE function. CONCLUSIONS: The magnitude of important change or change that surpasses measurement error can vary substantially depending on the method of calculation. Rehabilitation treatments can affect patient perceptions of functional change as effectively as laboratory-based functional measures; however, larger sample sizes may be required to account for the larger measurement error associated with patient-perceived functional measures.
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