What question did this study set out to answer?

This study aims to evaluate community reintegration levels in chronic stroke individuals and identify significant predictive factors.

May 7, 2026PNF and Movement0 citationsOpen Access

Predictors of Community Reintegration among Individuals with Chronic Stroke: Focus on Walking Ability

SASeung-Heun AnNational Rehabilitation Center EKEun-Joo KimNational Rehabilitation Center DPDong-Min ParkUniversity of Zenica

Key Points

This study aims to evaluate community reintegration levels in chronic stroke individuals and identify significant predictive factors.
Retrospective cross-sectional design involving 30 individuals with chronic stroke.
Data collection included demographic information and multiple functional assessments such as 6MWT, FMA-L/E, and RNLI-K.
Hierarchical multiple regression analysis was performed to assess the predictive power of these variables.
ABC was the strongest predictor of community reintegration with r=0.680, p<0.0001.
The 6MWT was significant in Model 3 with =0.693, p=0.017, explaining 22.9% of variance in RNLI-K.
In the final model, ABC was significant with =0.459, p=0.009, with the model explaining 29.2% of variance.

Abstract

Purpose: This study aimed to assess the level of community reintegration in individuals with chronic stroke using the Reintegration to Normal Living Index-Korean version (RNLI-K), to identify the factors significantly associated with RNLI scores, and to examine the relative influence of these factors on community reintegration.Methods: This study employed a retrospective cross-sectional design.Data were collected from 30 individuals with stroke, including general characteristics such as age and sex.Functional assessments included the 6-minute walk test (6MWT), Fugl-Meyer assessment for lower extremity (FMA-L/E), Berg Balance Scale (BBS), Modified Barthel Index (MBI), Activities-specific Balance Confidence Scale (ABC-scale), and the RNLI. Results:The variable most strongly correlated with RNLI-K was the ABC (r=0.680),followed by the 6MWT (r=0.587),BBS (r=0.506), and FMA-L/E (r=0.414).All correlations were statistically significant.A four-step hierarchical multiple regression analysis was conducted to examine the relative contribution of these variables to community reintegration.In Model 1, FMA-L/E was the only significant predictor (=0.377,p=0.030), explaining 11.3% of the variance in RNLI-K scores.In Model 2, BBS was added; however, no variable reached statistical significance.In Model 3, 6MWT emerged as the only significant predictor ( =0.693, p=0.017), and the explained variance increased to 22.9%.In the final Model 4, ABC was identified as a significant predictor (=0.459,p=0.009), with the overall model explaining the highest proportion of variance (29.2%).

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