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Craig A. Velozo, PhD, OTR/L; Michelle L. Woodbury, PhD, OTR/L

Translating measurement findings into rehabilitation practice: An example using Fugl-Meyer Assessment-Upper Extremity with patients following stroke. Craig A. Velozo, PhD, OTR/L; Michelle L. Woodbury, PhD, OTR/L. Study Aim

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Craig A. Velozo, PhD, OTR/L; Michelle L. Woodbury, PhD, OTR/L

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  1. Translating measurement findings into rehabilitation practice: An example using Fugl-Meyer Assessment-Upper Extremity with patients following stroke Craig A. Velozo, PhD, OTR/L; Michelle L. Woodbury, PhD, OTR/L

  2. Study Aim • Demonstrate how patient performance can be documented on a keyform and used with other patient-specific information to set goals and plan treatment. • Relevance • Standardized assessments are critical for advancing clinical rehabilitation, yet assessment scores often provide little information for rehabilitation treatment planning.

  3. Methods • Keyform map of poststroke upper-limb recovery defined by items of the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) was generated by previously published Rasch analysis. • 3 individuals with stroke were randomly selected and their performance on each item was displayed on FMA-UE keyform.

  4. Results • The forms directly connected qualitative descriptions of patients’ motor ability to assessment measures. • Furthermore, since item descriptions are ordered from easiest to hardest (bottom to top) and patient performance is indicated (can do, can partially do, cannot do), therapists can plan shorter and longer term rehabilitation goals.

  5. Sample FMA-UE Keyform Patient with severe upper-limb motor impairment (FMA-UE = 19/60, Rasch Ability Measure = –1.14 ± 0.33 logits).

  6. Conclusions • Evaluation forms, such as keyforms, may help therapists make day-to-day clinical decisions. • Keyforms can be created using IRT statistical methods, which connect the score to patients’ performance on specific items. • Well-developed standardized assessments, especially those with a logical item-difficulty structure, may be promising candidates for generating keyforms.

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