Descriptive characteristics as potential predictors of outcomes following constraint-induced movement therapy for people after stroke

Stacy L. Fritz, Kathye E. Light, Shannon N. Clifford, Tara S. Patterson, Andrea L. Behrman, Sandra B. Davis

    Research output: Contribution to journalArticlepeer-review

    35 Scopus citations

    Abstract

    Background and Purpose. Limited evidence exists regarding the characteristics of people who benefit most from constraint-induced movement therapy (CIMT). This study's purpose was to investigate 6 potential descriptors in predicting CIMT outcomes. Subjects. The participants were a convenience sample (N=55) of people who were more than 6 months poststroke. Methods. The Wolf Motor Function Test (WMFT) and the Motor Activity Log amount scale (MALa) were used to assess outcomes for CIMT. The potential predictors (side of stroke, time since stroke, hand dominance, age, sex, and ambulatory status) were entered into a linear regression model using stepwise entry, with simultaneous entry of the dependent variables' pretest scores as the covariate. Results. Age was the only significant predictor of the 6 potential predictors in the model and was predictive only of MALa scores. None of the independent variables showed a predictive relationship with the WMFT. Discussion and Conclusion. Although age was the only significant predictor, an equally strong finding in this study was that side of stroke, chronicity, hand dominance, sex, and ambulatory status were not found to be predictors at the follow-up session. This finding emphasizes the importance of not excluding people from CIMT based on these predictors.

    Original languageEnglish (US)
    Pages (from-to)825-832
    Number of pages8
    JournalPhysical therapy
    Volume86
    Issue number6
    DOIs
    StatePublished - Jun 2006

    Keywords

    • Constraint-induced movement therapy
    • Hemiplegia
    • Physical therapy
    • Stroke

    ASJC Scopus subject areas

    • Physical Therapy, Sports Therapy and Rehabilitation

    Fingerprint

    Dive into the research topics of 'Descriptive characteristics as potential predictors of outcomes following constraint-induced movement therapy for people after stroke'. Together they form a unique fingerprint.

    Cite this