Edorium Journal of

Disability and Rehabilitation

 
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Original Article
 
Dynamic gait index post-stroke: What is the item hierarchy and what does it tell the clinician? A Rasch analysis
Stacey E. Aaron1, Ickpyo Hong1, Mark G. Bowden2, Chris M. Gregory2, Aaron E. Embry3, Craig A. Velozo4
1PhD Candidate, Department of Health Sciences & Research, Medical University of South Carolina, Charleston, South Carolina, United States.
2Associate Professor, Department of Health Sciences & Research, Medical University of South Carolina, Charleston, South Carolina, United States; Division of Physical Therapy, Medical University of South Carolina, Charleston, South Carolina, United States; Ralph H. Johnson VA Medical Center, Charleston, South Carolina, United States.
3Research Associate, Department of Health Sciences & Research, Medical University of South Carolina, Charleston, South Carolina, United States; Division of Physical Therapy, Medical University of South Carolina, Charleston, South Carolina, United States; Ralph H. Johnson VA Medical Center, Charleston, South Carolina, United States.
4Occupational Therapy Division Director and Professor, Division of Occupational Therapy, Medical University of South Carolina, Charleston, South Carolina, United States.

Article ID: 100017D05SA2016
doi:10.5348/D05-2016-17-OA-13

Address correspondence to:
Stacey Elizabeth Aaron
MS, 77 President St, MSC 700
Charleston, South Carolina
United States, 29425

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How to cite this article
Aaron SE, Hong I, Bowden MG, Gregory CM, Embry AE, Velozo CA. Dynamic gait index post-stroke: What is the item hierarchy and what does it tell the clinician? A Rasch analysis. Edorium J Disabil Rehabil 2016;2:105–114.


Abstract
Aims: The purpose of this study was to use the Rasch measurement model to determine (1) the dynamic gait index (DGI) item-level psychometrics, (2) if the item-difficulty hierarchical order is consistent with a clinically logical progression from easiest to hardest, and (3) if the range of tasks is sufficient to measure the functional ability levels of the sample.
Methods: Data were retrieved retrospectively from study records, which included initial DGI scores and subject demographics collected at multiple university laboratories. Individuals were eligible to participate if 18+ years of age, >6 months post-stroke, residual paresis in lower extremity, and ability to walk with/without assistive device (n=117). Psychometrics of the DGI were tested with confirmatory factor analysis (CFA) and Rasch measurement modeling.
Results: DGI demonstrated acceptable psychometric properties: unidimensionality (CFA: χ2/df =2.12, CFI=0.98, TLI=0.97, RMSEA=0.09), no misfit items to the Rasch model, local independence (all item residual correlations <0.2), and a good internal reliability (Cronbach alpha of 0.86). Item-level analysis revealed a clear item-difficulty hierarchical order that is consistent with clinical observation and expectations. While the instrument separates the sample into three significant strata, there was mismatch between the average of person ability distribution (0.86 logit) and the average of item difficulties (0.00 logit).
Conclusion: The DGI demonstrated good item-level psychometric properties and an expected item-difficulty hierarchical order. Order of administration and adding more challenging items may improve precision and person-item matching to better differentiate between individuals with higher ability levels.

Keywords: Dynamic gait index (DGI), Gait, Psychometrics, Rasch, Stroke


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Author Contributions:
Stacey E. Aaron – Substantial contributions to conception and design, Acquisition of data, Analysis and interpretation of data, Drafting the article, Revising it critically for important intellectual content, Final approval of the version to be published
Ickpyo Hong – Analysis and interpretation of data, Drafting the article, Revising it critically for important intellectual content, Final approval of the version to be published
Mark G. Bowden – Substantial contributions to conception and design, Acquisition of data, Revising it critically for important intellectual content, Final approval of the version to be published
Chris M. Gregory – Acquisition of data, Revising it critically for important intellectual content, Final approval of the version to be published
Aaron E. Embry – Acquisition of data, Revising it critically for important intellectual content, Final approval of the version to be published
Craig A. Velozo – Substantial contributions to conception and design, Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published
Guarantor of submission
The corresponding author is the guarantor of submission.
Source of support
None
Conflict of interest
The seven studies used for this study were funded by VA Rehabilitation R&D grant B3983R, VA Rehabilitation R&D Center of Excellence grant F2182C, VA Rehabilitation R&D I01 RX000844, American Heart Association BgIA7450016, NIH/NIGMS U54 GM10494, NIH/NIGMS P20 GM109040, and NIH/NICHHD R01 HD 46820.
Copyright
© 2016 Stacey E. Aaron et al. This article is distributed under the terms of Creative Commons Attribution License which permits unrestricted use, distribution and reproduction in any medium provided the original author(s) and original publisher are properly credited. Please see the copyright policy on the journal website for more information.



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