Re-Examining the Dimensionality of a Disability Assessment Tool Using Exploratory Structural Equation Modeling...

Area of Science:

• Rehabilitation Medicine
• Psychometrics
• Health Services Research

Background:

• Low back pain (LBP) significantly impacts daily functioning and well-being.
• Accurate assessment tools are crucial for understanding the multifaceted nature of LBP disability.
• Existing tools may not fully capture the complex interplay of physical and psychosocial factors in LBP.

Purpose of the Study:

• To compare Exploratory Structural Equation Modeling (ESEM) with Confirmatory Factor Analysis (CFA) in assessing a low back pain disability measurement tool.
• To determine if ESEM offers a superior method for revealing the multidimensionality of LBP.
• To evaluate the alignment of findings with the International Classification of Functioning, Disability and Health (ICF) framework.

Main Methods:

• Data from 266 low back pain patients were analyzed using both CFA and ESEM.
• A 99-item measurement tool assessing body functions, activities, and participation was utilized.
• Mplus 8 software was employed to compare model fit and item factor loadings.

Main Results:

• ESEM demonstrated a slightly better model fit compared to CFA.
• ESEM revealed significant item cross-loadings, indicating overlap between "Body Functions" and "Activity-Participation" factors.
• Findings support the ICF model, reflecting the broad impact of LBP on individuals.

Conclusions:

• ESEM provides a more nuanced understanding of low back pain disability compared to CFA.
• The study supports the utility of ESEM in disability research for capturing multifaceted health conditions.
• Findings suggest ESEM can guide clinicians toward more holistic LBP management strategies addressing physical and psychosocial aspects.