The Fugl-Meyer Assessment of Motor Recovery after Stroke: A Critical Review of Its Measurement Properties
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Machine scores (provisional)
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- Teacher spread
- 0.240 · how far apart the two teachers sit on this one work
- Validation status
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Abstract
Measurement of recovery after stroke is becoming increasingly important with the advent of new treatment options under investigation in stroke rehabilitation research. The Fugl-Meyer scale was developed as the first quantitative evaluative instrument for measuring sensorimotor stroke recovery, based on Twitchell and Brunnstrom's concept of sequential stages of motor return in the hemiplegic stroke patient. The Fugl-Meyer is a well-designed, feasible and efficient clinical examination method that has been tested widely in the stroke population. Its primary value is the 100-point motor domain, which has received the most extensive evaluation. Excellent interrater and intrarater reliability and construct validity have been demonstrated, and preliminary evidence suggests that the Fugl-Meyer assessment is responsive to change. Limitations of the motor domain include a ceiling effect, omission of some potentially relevant items, and weighting of the arm more than the leg. Further study should test performance of this scale in specific subgroups of stroke patients and better define its criterion validity, sensitivity to change, and minimal clinically important difference. Based on the available evidence, the Fugl-Meyer motor scale is recommended highly as a clinical and research tool for evaluating changes in motor impairment following stroke.
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The record
- Venue
- Neurorehabilitation and neural repair
- Topic
- Stroke Rehabilitation and Recovery
- Field
- Medicine
- Canadian institutions
- University of TorontoHealth Sciences CentreSunnybrook Health Science Centre
- Funders
- —
- Keywords
- Physical medicine and rehabilitationStroke (engine)PsychologyRehabilitationConstruct validityInter-rater reliabilityPhysical therapyRating scalePsychometricsMedicineDevelopmental psychology
- Has abstract in OpenAlex
- yes