The Oswestry Disability Index, confirmatory factor analysis in a sample of 35,263 verifies a one-factor structure but
Charles Philip Gabel1, Antonio Cuesta-Vargas2, Meihua Qian3
1Coolum Physiotherapy Sunshine Coast, Coolum Beach, Queensland, Australia.
Purpose:
To analyze the factor structure of the Oswestry Disability Index (ODI) in a large symptomatic low back pain (LBP) population using exploratory (EFA) and confirmatory factor analysis (CFA).
Methods:
Analysis of pooled baseline ODI LBP patient data from the international Spine Tango registry of EUROSPINE, the Spine Society of Europe. The sample, with n = 35,263 (55.2% female; age 15-99, median 59 years), included 76.1% of patients with a degenerative disease, and 23.9% of the patients with various other spinal conditions. The initial EFA provided a hypothetical construct for consideration. Subsequent CFA was considered in three scenarios: the full sample and separate genders. Models were compared empirically for best fit.
Results:
The EFA indicated a one-factor solution accounting for 54% of the total variance. The CFA analysis based on the full sample confirmed this one-factor structure. Sub-group analyses by gender achieved good model fit for configural and partial metric invariance, but not scalar invariance. A possible two-construct model solution as outlined by previous researchers: dynamic-activities (personal care, lifting, walking, sex and social) and static-activities (pain, sleep, standing, travelling and sitting) was not preferred.
Conclusions:
The ODI demonstrated a one-factor structure in a large LBP sample. A potential two-factor model was considered, but not found appropriate for constructs of dynamic and static activity. The use of the single summary score for the ODI is psychometrically supported. However, practicality limitations were reported for use in the clinical and research settings. Researchers are encouraged to consider a shift towards newer, more sensitive and robustly developed instruments.
More Related Videos
Related Concept Videos
Factorial Design
Factors Affecting Illness
For instance, risk factors are connected to illness,...
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
Five-Factor Theory of Personality
Openness reflects creativity, curiosity, and openness to new experiences. Individuals scoring high in openness are imaginative, have a wide range of interests, and are independent...
Reliability and Validity
Cattell's 16 Personality Factors
In contrast, source traits are the...


