Three different methods for demonstrating that gain in Functional Independence Measure increases with higher cognitive ability

Tokunaga, Makoto; Sannomiya, Katsuhiko; Ohashi, Taeko; Yonemura, Miki; Sakata, Daisuke; Imaya, Masami; Sugitani, Eitaro; Mitsunaga, Wataru; Shiiba, Seiya; Nakashima, Yukihiko

doi:10.11336/jjcrs.5.26

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…For the analysis, we first confirmed the participants' cognitive function during hospitalization, using the mini-mental state examination scores ≥21 (Folstein, Folstein and McHugh, 1975) or FIM-cognitive scores ≥25 (Manuel et al, 2002;Tokunaga et al, 2014), and participants who did not meet these criteria were excluded from the analysis. Data were reported as mean and standard deviation (SD) or median and frequency (percentage).…”

Section: Discussionmentioning

confidence: 99%

Minimal clinically important difference in physical activity in patients with stroke

Hiragami,

Yoshida,

Otsuka

et al. 2024

F1000Res

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Background Estimates of the minimal clinically important difference (MCID) for stroke-related outcomes are needed, but the MCID for physical activity is unknown. Objective To provide an anchor-based estimate of the MCID for physical activity in patients with stroke. Methods This study included 31 patients with stroke admitted to a hospital and discharged home. Physical activity, including the daily number of steps and metabolic equivalents (METs), was evaluated shortly after informed consent was obtained following admission (baseline) and discharge using an Active-style Pro HJA-750C with a triaxial accelerometer. We calculated the number of steps and time rate (%) of sedentary behavior (SB), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) per day. After discharge, the physical therapist rated each participant’s perceived amount of physical activity recovery on the Global Rating of Change scale (GRC). The mean change in each physical activity data point from baseline to after discharge in the group of participants who answered “a little better, meaningful” in the GRC was considered the MCID. Results Eighteen participants were included in the analysis. Participants’ physical function improved from baseline to at discharge during hospitalization, although mild motor paralysis persisted. MCID values for the step activity, SB, LPA, and MVPA were 1828 steps, -11.2%, 6.9%, 4.3% per day, respectively. Conclusion For researchers and clinicians, this study’s MCIDs provide a benchmark for interpreting changes in the effects of intervention studies, and specific guidelines for interventions in clinical practice. Further research with larger sample sizes is required to confirm these findings.

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Section: Discussionmentioning

confidence: 99%

Minimal clinically important difference in physical activity in patients with stroke

Hiragami,

Yoshida,

Otsuka

et al. 2024

F1000Res

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A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy

Tokunaga

Watanabe

Sonoda

2017

Journal of Stroke and Cerebrovascular Diseases

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Methods for Improving the Predictive Accuracy Using Multiple Linear Regression Analysis to Predict the Improvement Degree of Functional Independence Measure for Stroke Patients

Tokunaga¹,

Hashimoto²,

Watanabe³

et al. 2017

Int J Phys Med Rehabil

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Multiple linear regression analysis is frequently used in studies investigating the degree of Functional Independence Measure (FIM) improvement in stroke patients. However, the coefficient of determination R 2 is about 0.46 to 0.73, meaning that the prediction accuracy is not necessarily high. In order to improve the prediction accuracy, the following methods are used; using appropriate explanatory variables, using FIM effectiveness which corrected the ceiling effect as the objective variable, creating multiple prediction formulas, converting numerical variable of explanatory variables into dummy variable, adding FIM improvement for one month to the explanatory variables. Even so, it is difficult to predict patients whose FIM gain is extremely large or small. It is desirable to combine these methods or develop new methods to achieve the accurate prediction.

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Three different methods for demonstrating that gain in Functional Independence Measure increases with higher cognitive ability

Cited by 3 publications

References 14 publications

Minimal clinically important difference in physical activity in patients with stroke

Minimal clinically important difference in physical activity in patients with stroke

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy

Methods for Improving the Predictive Accuracy Using Multiple Linear Regression Analysis to Predict the Improvement Degree of Functional Independence Measure for Stroke Patients

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