The Relationship Between Self-Reported Hand Use and Movement Efficiency

SIGNIFICANCE: Stroke is the leading cause of disability in the United States. Loss of arm function contributes to poststroke disability. To efficiently grasp and manipulate functional objects during performance of daily living tasks, reaching movements must be smooth and direct. Therapists commonly address skillful reaching to increase clients’ real-world arm function, and they frequently utilize client self-reported arm use to document outcomes. However, there is a deficit of evidence from which therapists can make informed treatment decisions as to how aspects of skillful reach (movement smoothness and directness) affect improvements on self-reported arm use measures.

INNOVATION: Current stroke rehabilitation concepts emphasize repetitive task-practice treatment strategies and value client-reported outcomes. In this study, I seek to shift current practice paradigms from a focus on overall task practice to a focus on specific aspects of task performance by elucidating critical mechanisms underlying self-reported, real-world arm use.

APPROACH: I hypothesize that individuals with greater efficiency of arm movements (smoothness and directness) will report greater hand use. A goal of poststroke rehabilitation therapy is often to improve skillful arm movement, and self-reported arm use is a valued outcome measure. However, the relationship between movement skill and self-reported use is not clear. Inability to complete tasks efficiently is often reported as a reason for decreased levels of self-reported hand use.

METHOD: For the study design, I used preliminary cross-sectional analysis of existing data obtained from subjects enrolled in an ongoing federally funded randomized controlled trial (RCT). The setting occurred in a stroke rehabilitation research laboratory. Participants included 23 subjects (18 men), aged 19 to 77 yr, who were 9 to 116 mo post mild-to-moderately-severe ischemic stroke.

Summed Stroke Impact Scale—Hand Domain (SIS–Hand) ratings indicated self-reported, real-world hand use. Two kinematic variables indicated movement efficiency: hand path curvature (HPC) to measure the directness of a reach-to-target, and number of peaks (PKS) in the linear velocity profile to measure movement smoothness.

Using two univariate regression models and one multivariate model, I explored the individual and combined impacts of HPC and PKS on SIS–Hand (PROC REG, SAS Version 9.3). I used Akaike information criterion (AIC) to determine goodness of fit for model selection.

RESULTS: HPC alone was the best predictor of hand use (R ² = .32, β = −7.40, p = .01, AIC = 59.61). PKS did not significantly predict hand use (R ² = .13, β = −1.23, p = .11, AIC = 64.87). Combining the variables did not significantly improve the model (R ² = .30, HPC β = −6.62, HPC p = .02, PKS β = −.75, PKS p = .28, AIC = 60.18).

CONCLUSION: Results suggest that directness of movement during a reach-to-target, but not movement smoothness, is significantly related to self-reported hand use after stroke. The steep slope of the HPC regression coefficient suggests that therapy aimed at improving clients’ skill at making direct (i.e., straight line) reaching movements to a target will have a strong influence on changes in self-reported hand use.