Performance-integrated self-report measurement of physical ability

Abstract

Background context The technology of self-report measures has advanced rapidly over the past few years. Recently, this technology was used to develop a performance-integrated self-report measure for use with patients with musculoskeletal impairments that may lead to work disability. Psychometric studies of the new measure in patient populations have been successful. A validation study of the measure with adults in good general health is necessary. Purpose The purpose of this study was to assess the concurrent validity of a new performance-integrated self-report measure, the multidimensional task ability profile (MTAP). Study design/setting A prospective validation study was conducted in which a self-report measure was administered online, and a physical performance test was administered at various clinics in North America. Patient sample One hundred ninety-six (34% male) adult volunteers in good general health participated in this study. Outcome measures Self-report measure—MTAP. Physiologic measure—EPIC Lift Capacity test. Methods The MTAP was administered online within 1 week of formal testing of lift capacity using a standardized lift capacity test, the EPIC Lift Capacity test. MTAP scores were compared with performance on the EPIC Lift Capacity test. Stepwise regression analysis was used to identify the strength of the relationship between the two measures and the relative explanation of lift capacity variance by the MTAP score, along with gender and age. Results The combination of MTAP score, gender, and age demonstrated a regression coefficient of R=0.82, which accounts for 67.3% of the variance in lift capacity. Conclusions The MTAP displayed good concurrent validity compared with actual physical performance as assessed by the EPIC Lift Capacity test. Modern performance-integrated self-report measures, such as the MTAP, have the potential to provide information about functional capacity that is sufficiently useful to confirm status and help guide treatment algorithms.