BACKGROUND: The Dynamic Gait Index (DGI) measures the capacity to adapt gait to complex tasks. The current scoring system combining gait pattern (GP) and level of assistance (LOA) lacks clarity, and the test has a limited range of measurement. OBJECTIVE: This study developed a new scoring system based on 3 facets of performance (LOA, GP, and time) and examined the psychometric properties of the modified DGI (mDGI). DESIGN: A cross-sectional, descriptive study was conducted. METHODS: Nine hundred ninety-five participants (855 patients with neurologic pathology and mobility impairments [MI group] and 140 patients without neurological impairment [control group]) were tested. Interrater reliability was calculated using kappa coefficients. Internal consistency was computed using the Cronbach alpha coefficient. Factor analysis and Rasch analysis investigated unidimensionality and range of difficulty. Internal validity was determined by comparing groups using multiple t tests. Minimal detectable change (MDC) was calculated for total score and 3 facet scores using the reliability estimate for the alpha coefficients. RESULTS: Interrater agreement was strong, with kappa coefficients ranging from 90% to 98% for time scores, 59% to 88% for GP scores, and 84% to 100% for LOA scores. Test-retest correlations (r) for time, GP, and LOA were .91, .91, and .87, respectively. Three factors (time, LOA, GP) had eigenvalues greater than 1.3 and explained 79% of the variance in scores. All group differences were significant, with moderate to large effect sizes. The 95% minimal detectable change (MDC95) was 4 for the mDGI total score, 2 for the time and GP total scores, and 1 for the LOA total score. LIMITATIONS: The limitations included uneven sample sizes in the 2 groups. The MI group were patients receiving physical therapy; therefore, they may not be representative of this population. CONCLUSIONS: The mDGI, with its expanded scoring system, improves the range, discrimination, and facets of measurement related to walking function. The strength of the psychometric properties of the mDGI warrants its adoption for both clinical and research purposes.
BACKGROUND: The Dynamic Gait Index (DGI) measures the capacity to adapt gait to complex tasks. The current scoring system combining gait pattern (GP) and level of assistance (LOA) lacks clarity, and the test has a limited range of measurement. OBJECTIVE: This study developed a new scoring system based on 3 facets of performance (LOA, GP, and time) and examined the psychometric properties of the modified DGI (mDGI). DESIGN: A cross-sectional, descriptive study was conducted. METHODS: Nine hundred ninety-five participants (855 patients with neurologic pathology and mobility impairments [MI group] and 140 patients without neurological impairment [control group]) were tested. Interrater reliability was calculated using kappa coefficients. Internal consistency was computed using the Cronbach alpha coefficient. Factor analysis and Rasch analysis investigated unidimensionality and range of difficulty. Internal validity was determined by comparing groups using multiple t tests. Minimal detectable change (MDC) was calculated for total score and 3 facet scores using the reliability estimate for the alpha coefficients. RESULTS: Interrater agreement was strong, with kappa coefficients ranging from 90% to 98% for time scores, 59% to 88% for GP scores, and 84% to 100% for LOA scores. Test-retest correlations (r) for time, GP, and LOA were .91, .91, and .87, respectively. Three factors (time, LOA, GP) had eigenvalues greater than 1.3 and explained 79% of the variance in scores. All group differences were significant, with moderate to large effect sizes. The 95% minimal detectable change (MDC95) was 4 for the mDGI total score, 2 for the time and GP total scores, and 1 for the LOA total score. LIMITATIONS: The limitations included uneven sample sizes in the 2 groups. The MI group were patients receiving physical therapy; therefore, they may not be representative of this population. CONCLUSIONS: The mDGI, with its expanded scoring system, improves the range, discrimination, and facets of measurement related to walking function. The strength of the psychometric properties of the mDGI warrants its adoption for both clinical and research purposes.
Authors: Francesca E Wade; Grace K Kellaher; Sarah Pesquera; Sidney T Baudendistel; Arkaprava Roy; David J Clark; Rachael D Seidler; Daniel P Ferris; Todd M Manini; Chris J Hass Journal: J Biomech Date: 2022-05-10 Impact factor: 2.789
Authors: Fatemeh Noohi; Catherine Kinnaird; Yiri De Dios; Igor Kofman; Scott J Wood; Jacob J Bloomberg; Ajitkumar P Mulavara; Kathleen H Sienko; Thad A Polk; Rachael D Seidler Journal: PLoS One Date: 2019-09-12 Impact factor: 3.240
Authors: Victor Santamaria; Moiz Khan; Tatiana Luna; Jiyeon Kang; Joseph Dutkowsky; Andrew M Gordon; Sunil K Agrawal Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2021-01-28 Impact factor: 4.528