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RISS 인기검색어
- 검색키워드
- 저자 : Timothy A. Reistetter (검색결과 3 건)
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홍익표,김영주,Mandi L. Sonnenfeld,Emily Grattan,Timothy A. Reistetter 대한재활의학회 2018 Annals of Rehabilitation Medicine Vol.42 No.2
Objective To investigate the psychometric properties of the activities of daily living (ADL) instrument used in the analysis of Korean Longitudinal Study of Ageing (KLoSA) dataset. Methods A retrospective study was carried out involving 2006 KLoSA records of community-dwelling adults diagnosed with stroke. The ADL instrument used for the analysis of KLoSA included 17 items, which were analyzed using Rasch modeling to develop a robust outcome measure. The unidimensionality of the ADL instrument was examined based on confirmatory factor analysis with a one-factor model. Item-level psychometric analysis of the ADL instrument included fit statistics, internal consistency, precision, and the item difficulty hierarchy. Results The study sample included a total of 201 community-dwelling adults (1.5% of the Korean population with an age over 45 years; mean age=70.0 years, SD=9.7) having a history of stroke. The ADL instrument demonstrated unidimensional construct. Two misfit items, money management (mean square [MnSq]=1.56, standardized Z-statistics [ZSTD]=2.3) and phone use (MnSq=1.78, ZSTD=2.3) were removed from the analysis. The remaining 15 items demonstrated good item fit, high internal consistency (person reliability=0.91), and good precision (person strata=3.48). The instrument precisely estimated person measures within a wide range of theta (-4.75 logits < q < 3.97 logits) and a reliability of 0.9, with a conceptual hierarchy of item difficulty. Conclusion The findings indicate that the 15 ADL items met Rasch expectations of unidimensionality and demonstrated good psychometric properties. It is proposed that the validated ADL instrument can be used as a primary outcome measure for assessing longitudinal disability trajectories in the Korean adult population and can be employed for comparative analysis of international disability across national aging studies.
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Challenges and Opportunities for Occupational Therapy in Big Data Research
홍익표,Meredith F. Shields,Mi Jung Lee,Riqiea Kitchens,Karen Ratcliff,Timothy A. Reistetter,홍익표 대한작업치료학회 2019 대한작업치료학회지 Vol.27 No.4
The advance of information technology with governmental support allows researchers to utilize big data to conductrigorous rehabilitation-related studies in both the United States and Korea. While big data research has beenactively conducted in the United States, few Korean rehabilitation scientists currently conduct big data research. Inthis paper, we discuss the existing rehabilitation-related big data in Korea and introduce the current big dataresearch trends in the United States. In addition, we provide potential research areas by discussing the previousbig data studies in the United States, including 1) functional outcomes, 2) geographical variation, 3) linkage of apopulation-based cohort to hospital data, 4) cross-national comparison, and 5) scale development. We also discussvarious statistical methods required in big data research and compare how these methods differ compared to thetraditional research methods in rehabilitation research. Lastly, we discuss the importance of workforce developmentin rehabilitation-related big data research. We hope this paper will provide occupational therapy scientists andclinicians with practical and useful information about big data research and accelerate big data rehabilitationresearch communities in Korea.
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Challenges and Opportunities for Occupational Therapy in Big Data Research
Ickpyo Hong,Meredith F. Shields,Mi Jung Lee,Riqiea Kitchens,Karen Ratcliff,Timothy A. Reistetter 대한작업치료학회 2019 대한작업치료학회지 Vol.27 No.5
The advance of information technology with governmental support allows researchers to utilize big data to conduct rigorous rehabilitation-related studies in both the United States and Korea. While big data research has been actively conducted in the United States, few Korean rehabilitation scientists currently conduct big data research. In this paper, we discuss the existing rehabilitation-related big data in Korea and introduce the current big data research trends in the United States. In addition, we provide potential research areas by discussing the previous big data studies in the United States, including 1) functional outcomes, 2) geographical variation, 3) linkage of a population-based cohort to hospital data, 4) cross-national comparison, and 5) scale development. We also discuss various statistical methods required in big data research and compare how these methods differ compared to the traditional research methods in rehabilitation research. Lastly, we discuss the importance of workforce development in rehabilitation-related big data research. We hope this paper will provide occupational therapy scientists and clinicians with practical and useful information about big data research and accelerate big data rehabilitation research communities in Korea.
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