{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T02:24:08Z","timestamp":1790043848882,"version":"4.0.1"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,7,1]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>The modified Dynamic Gait Index (mDGI) measures the capacity to adapt gait to complex tasks utilizing 8 tasks and 3 facets of performance. The measurement stability of the mDGI in specific diagnostic groups is unknown.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>This study examined the psychometric properties of the mDGI in 5 diagnostic groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>This was a cross-sectional, descriptive study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A total of 794 participants were included in the study: 140 controls, 239 with stroke, 140 with vestibular dysfunction, 100 with traumatic brain injury, 91 with gait abnormality, and 84 with Parkinson disease. Differential item functioning analysis was used to examine the comparability of scores across diagnoses. Internal consistency was computed using Cronbach alpha. Factor analysis was used to examine the factor loadings for the 3 performance facet scores. Minimal detectable change at the 95% confidence level (MDC95%) was calculated for each of the groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Less than 5% of comparisons demonstrated moderate to large differential item functioning, suggesting that item scores had the same order of difficulty for individuals in all 5 diagnostic groups. For all 5 patient groups, 3 factors had eigenvalues &amp;gt;1.0 and explained 80% of the variability in scores, supporting the importance of characterizing mobility performance with respect to time, level of assistance, and gait pattern.<\/jats:p><\/jats:sec><jats:sec><jats:title>Limitations<\/jats:title><jats:p>There were uneven sample sizes in the 6 groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The strength of the psychometric properties of the mDGI across the 5 diagnostic groups further supports the validity and usefulness of scores for clinical and research purposes. In addition, the meaning of a score from the mDGI, regardless of whether at the task, performance facet, or total score level, was comparable across the 5 diagnostic groups, suggesting that the mDGI measured mobility function independent of medical diagnosis.<\/jats:p><\/jats:sec>","DOI":"10.2522\/ptj.20130294","type":"journal-article","created":{"date-parts":[[2014,2,21]],"date-time":"2014-02-21T05:31:24Z","timestamp":1392960684000},"page":"996-1004","source":"Crossref","is-referenced-by-count":30,"title":["Evidence for the Validity of the Modified Dynamic Gait Index Across Diagnostic Groups"],"prefix":"10.1093","volume":"94","author":[{"given":"Patricia Noritake","family":"Matsuda","sequence":"first","affiliation":[{"name":"P.N. Matsuda, PT, PhD, DPT, Department of Rehabilitation Medicine, Division of Physical Therapy, University of Washington, 1959 NE Pacific St, Box 356490, Seattle, WA 98195 (USA)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine S.","family":"Taylor","sequence":"additional","affiliation":[{"name":"C.S. Taylor, PhD, College of Education, University of Washington."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne","family":"Shumway-Cook","sequence":"additional","affiliation":[{"name":"A. 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