Elisabetta Bravini1, Franco Franchignoni2, Andrea Giordano3, Francesco Sartorio2, Giorgio Ferriero2, Stefano Vercelli4, Calogero Foti5. 1. School in Advanced Sciences and Technology in Rehabilitation Medicine and Sports, Tor Vergata University, Rome, Italy. 2. Unit of Occupational Rehabilitation and Ergonomics, Salvatore Maugeri Foundation, Scientific Institute of Veruno, Veruno, Italy. 3. Unit of Bioengineering, Salvatore Maugeri Foundation, Scientific Institute of Veruno, Veruno, Italy. 4. Unit of Occupational Rehabilitation and Ergonomics, Salvatore Maugeri Foundation, Scientific Institute of Veruno, Veruno, Italy. Electronic address: stefano.vercelli@fsm.it. 5. Department of Physical and Rehabilitation Medicine, Tor Vergata University Hospital, Rome, Italy.
Abstract
OBJECTIVE: To perform a comprehensive analysis of the psychometric properties and dimensionality of the Upper Limb Functional Index (ULFI) using both classical test theory and Rasch analysis (RA). DESIGN: Prospective, single-group observational design. SETTING: Freestanding rehabilitation center. PARTICIPANTS: Convenience sample of Italian-speaking subjects with upper limb musculoskeletal disorders (N=174). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The Italian version of the ULFI. Data were analyzed using parallel analysis, exploratory factor analysis, and RA for evaluating dimensionality, functioning of rating scale categories, item fit, hierarchy of item difficulties, and reliability indices. RESULTS: Parallel analysis revealed 2 factors explaining 32.5% and 10.7% of the response variance. RA confirmed the failure of the unidimensionality assumption, and 6 items out of the 25 misfitted the Rasch model. When the analysis was rerun excluding the misfitting items, the scale showed acceptable fit values, loading meaningfully to a single factor. Item separation reliability and person separation reliability were .98 and .89, respectively. Cronbach alpha was .92. CONCLUSIONS: RA revealed weakness of the scale concerning dimensionality and internal construct validity. However, a set of 19 ULFI items defined through the statistical process demonstrated a unidimensional structure, good psychometric properties, and clinical meaningfulness. These findings represent a useful starting point for further analyses of the tool (based on modern psychometric approaches and confirmatory factor analysis) in larger samples, including different patient populations and nationalities.
OBJECTIVE: To perform a comprehensive analysis of the psychometric properties and dimensionality of the Upper Limb Functional Index (ULFI) using both classical test theory and Rasch analysis (RA). DESIGN: Prospective, single-group observational design. SETTING: Freestanding rehabilitation center. PARTICIPANTS: Convenience sample of Italian-speaking subjects with upper limb musculoskeletal disorders (N=174). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The Italian version of the ULFI. Data were analyzed using parallel analysis, exploratory factor analysis, and RA for evaluating dimensionality, functioning of rating scale categories, item fit, hierarchy of item difficulties, and reliability indices. RESULTS: Parallel analysis revealed 2 factors explaining 32.5% and 10.7% of the response variance. RA confirmed the failure of the unidimensionality assumption, and 6 items out of the 25 misfitted the Rasch model. When the analysis was rerun excluding the misfitting items, the scale showed acceptable fit values, loading meaningfully to a single factor. Item separation reliability and person separation reliability were .98 and .89, respectively. Cronbach alpha was .92. CONCLUSIONS: RA revealed weakness of the scale concerning dimensionality and internal construct validity. However, a set of 19 ULFI items defined through the statistical process demonstrated a unidimensional structure, good psychometric properties, and clinical meaningfulness. These findings represent a useful starting point for further analyses of the tool (based on modern psychometric approaches and confirmatory factor analysis) in larger samples, including different patient populations and nationalities.