Participant perception of recovery as criterion to establish importance of improvement for constraint-induced movement therapy outcome measures: a preliminary study.

BACKGROUND AND PURPOSE: Changes in function following constraint-induced movement therapy (CIMT) are characterized primarily by improvements in performance; however, the importance of these outcome measures to the participant may be unclear. The primary purpose of this study was to determine whether either change scores or raw follow-up scores for the Motor Activity Log amount scale (MALa) and the Wolf Motor Function Test (WMFT) predicted participants' self-reports of recovery of upper-extremity function at 4 to 6 months after starting CIMT. SUBJECTS AND METHODS: This study was a secondary analysis of a cohort of subjects (N=46) who participated in CIMT trials. SUBJECTS: completed measures at baseline and 4 to 6 months later. Hierarchical regression models determined whether change scores or raw follow-up scores of CIMT outcome measures were predictive of perceived recovery. Receiver operating characteristic (ROC) curves determined cutoff scores for measures that significantly contributed to participants' reports of perceived recovery. RESULTS: The regression models indicated that raw follow-up MALa scores (beta=0.80, P=.024) and WMFT scores (beta=-0.37, P=.03) contributed to perceived recovery. Proposed cutoff scores for the MALa scores were less than 1.15 (negative likelihood ratio [LR]=0.17) for predicting less than 50% recovery and greater than 2.50 (positive LR=2.75) for predicting 50% or greater recovery. Proposed cutoff scores for follow-up WMFT scores were greater than 34.0 seconds (negative LR=0.24) for predicting less than 50% recovery and less than 11.0 seconds (positive LR=5.96) for predicting 50% or greater recovery. DISCUSSION AND CONCLUSION: Raw follow-up scores for the MALa and WMFT were better predictors of self-report of recovery in comparison with change scores. These data also serve as a starting point for developing cutoff scores that accurately predict self-report of recovery.

Duke Scholars

Author Steven Zachary George Orthopaedic Surgery