TITLE:
Investigate Targeted Factors to Achieve Prediction Goal in Stroke Convalescence in Terms of Causal Relationships of Prediction Error
AUTHORS:
Takashi Kimura
KEYWORDS:
Prediction Error, Functional Independence Measure, Stroke, Convalescent Phase, Structural Equation Modeling
JOURNAL NAME:
Open Journal of Therapy and Rehabilitation,
Vol.10 No.4,
November
11,
2022
ABSTRACT: Background and Purpose: To investigate target
functional independence measure (FIM)
items to achieve the prediction goal in terms of the causal relationships
between prognostic prediction error and FIM among stroke patients in the
convalescent phase using the structural equation modeling (SEM) analysis.
Methods: A total of 2992 stroke patients registered in the Japanese
Rehabilitation Database were analyzed retrospectively. The prediction error was
calculated based on a prognostic prediction formula proposed in a previous
study. An exploratory factor analysis (EFA) then the factor was determined using confirmatory factorial analysis (CFA). Finally,
multivariate analyses were performed
using SEM analysis. Results: The fitted indices of the hypothesized model
estimated based on EFA were confirmed by CFA. The factors estimated by
EFA were applied, and interpreted as follows: “Transferring (T-factor),”
“Dressing (D-factor),” and “Cognitive function (C-factor).” The fit of the
structural model based on the three factors and prediction errors was supported by the SEM analysis. The effects of
the D- and C-factors yielded similar causal relationships on prediction
error. Meanwhile, the effects between the prediction error and the T-factor were low. Observed FIM items were related
to their domains in the structural model, except for the dressing of the
upper body and memory (p