The MAT-sf: clinical relevance and validity

Abstract

Background: The measurement of mobility is essential to both aging research and clinical practice. A newly developed self-report measure of mobility, the mobility assessment tool-short form (MAT-sf), uses video animations to improve measurement accuracy/precision. Using a large baseline data set, we recalibrated the items, evaluated the extent to which older patients' self-efficacy (i.e., confidence) for walking was related to MAT-sf scores beyond their actual 400-m walk time, and assessed the relationship of the MAT-sf with body mass index and other clinical variables.

Methods: The analyses employed baseline data from the Lifestyle Interventions and Independence for Elders Study.

Results: Item recalibration demonstrated that the MAT-sf scoring algorithm was robust. In an analysis with 400-m walk time and self-efficacy regressed on the MAT-sf, both variables shared unique variance with the MAT-sf (p < .001). The MAT-sf was inversely related to several comorbidities, most notably hypertension and arthritis (p < .001), and scores were lowest when body mass index ≥ 35 kg/m(2). Finally, MAT-sf scores were directly related to Short Physical Performance Battery scores, inversely related to difficulty with activities of daily living (p < .001) and higher for men than for women (p < .001).

Conclusions: The findings extend the validity and clinical utility of this innovative tool for assessing self-reported mobility in older adults. Longitudinal data on the MAT-sf from the Lifestyle Interventions and Independence for Elders Study will enable us to evaluate the relative contributions of self-report and performance-based measures of mobility on important health outcomes.

Keywords: Geriatric assessment; MAT-sf; Mobility; Physical function.

Figures

Figure 1.

(A) Category response curves and information curve for Item 1 asking “For how many minutes could you walk on level ground at the pace shown?” On the left panel, responses to the four categories are none and 1 (Category 0), 5–15 (Category 1), 20–30 (Category 2), and more than 30 minutes (Category 3). The four dashed lines represent the probability of each response across the range of function and the y-axis is on the left. The solid line represents the information curve, and the y-axis on the right provides the scale. On the right panel, Categories 2 and 3 in the original data are combined to form the new Category 2. Original (n = 234) and new (n = 1343) response curves for Item #1 in MAT-sf. (B) Category response curves and information curve for the Item 2 asking “For how many minutes could you jog on level ground at the pace shown?” On the left panel, responses to the four categories are none and 1 (Category 0), 5–15 (Category 1), 20–30 (Category 2), and more than 30 minutes (Category 3). The four lines represent the probability of each response across the range of function and the y-axis is on the left. The solid line represents the information curve, and the y-axis on the right provides the scale. On the right panel, Categories 2 and 3 in the original data are combined to form the new Category 2. Original (n = 234) and new (n = 1643) response curves for Item #2 in MAT-sf .

Figure 2.

Plot of the MAT-sf scores versus the standard error (SE) for these scores.