Journal of clinical epidemiology · 2010
Unidimensionality of the Elderly Mobility Scale in older acute medical patients: different methods, different answers.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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de Morton Natalie A, Nolan Jo S
Аннотация
OBJECTIVE: To investigate the unidimensionality of the Elderly Mobility Scale (EMS) in an older acute medical population.
STUDY DESIGN: EMS data were collected within 48 hours of hospital admission and discharge, respectively, from consecutive older acute medical patients. Rasch and factor analysis of EMS data were conducted.
SETTING: Acute tertiary hospital, South Australia.
RESULTS: Factor analysis identified a two-factor solution for both admission and discharge EMS data. At hospital admission (n=120), EMS data fitted the Rasch model (χ(2)=18.31, P=0.19, df=14). One item, the timed walk test, had a high positive fit residual (+3.93). At hospital discharge (n=105), EMS data did not fit the Rasch model (χ(2)=25.66, P=0.03, df=14). Item and person scores were not well matched because of a ceiling effect in discharge EMS scores. The functional reach item showed some misfit to the Rasch model and the gait item had a disordered threshold. After rescoring this disordered threshold, discharge EMS data fitted the Rasch model.
CONCLUSION: Conflicting results were identified using a classical test theory and item response theory approach. Although the EMS fitted the Rasch model, an unacceptable ceiling effect at hospital discharge limits the validity of the EMS for measuring and monitoring the mobility of older acute medical patients in the hospital setting.
STUDY DESIGN: EMS data were collected within 48 hours of hospital admission and discharge, respectively, from consecutive older acute medical patients. Rasch and factor analysis of EMS data were conducted.
SETTING: Acute tertiary hospital, South Australia.
RESULTS: Factor analysis identified a two-factor solution for both admission and discharge EMS data. At hospital admission (n=120), EMS data fitted the Rasch model (χ(2)=18.31, P=0.19, df=14). One item, the timed walk test, had a high positive fit residual (+3.93). At hospital discharge (n=105), EMS data did not fit the Rasch model (χ(2)=25.66, P=0.03, df=14). Item and person scores were not well matched because of a ceiling effect in discharge EMS scores. The functional reach item showed some misfit to the Rasch model and the gait item had a disordered threshold. After rescoring this disordered threshold, discharge EMS data fitted the Rasch model.
CONCLUSION: Conflicting results were identified using a classical test theory and item response theory approach. Although the EMS fitted the Rasch model, an unacceptable ceiling effect at hospital discharge limits the validity of the EMS for measuring and monitoring the mobility of older acute medical patients in the hospital setting.