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A summary score ranging from 0 worst performers to 12 best performers is calculated by summing the three component scores. Support for the measurement properties of the SPPB has been provided by Guralnik and colleagues 6 , A measure of self-efficacy was developed for the m walk based on the methodology described by Bandura After completing the m walk test, participants were asked how much confidence they had in their ability to walk five different distances at the same pace 1 week hence: 5 laps, 10 laps the same distance as today , 15 laps, 20 laps twice as far , and 25 laps.
Confidence ratings were made for each distance on a scale that ranged from 0 to The verbal anchors No Confidence appeared with a value of 0, Moderate Confidence with a value of 5, and Complete Confidence with a value of In the LIFE-pilot P study 16 , we found older adults who had more severe mobility problems as defined by SPPB scores less than 7 had significantly lower mean self-efficacy scores The Cronbach alpha for this measure of self-efficacy is 0.
One goal of the present study was to recalibrate the 10 items used in the MAT-sf employing a larger and more representative sample from the study. In the recalibration procedure, we first combined data from the original calibration with baseline data from the LIFE Study. Subsequently, the same item response models were used to calibrate the items and the new item parameters for the item MAT-sf to obtain individual scores for each participant. Category response curves and information curves from the recalibration were compared with those from the first calibration.
Both the difference and correlation between the mobility estimates from the two calibrations were examined for assessing the effect of the recalibration. Following the original calibration, a graded response model and a two-parameter logistic model were, respectively, used for recalibrating polytomous and dichotomous responses.
We further assessed goodness of fit of the unidimensional model, item fit, differential item functioning, and ceiling and floor effects. Descriptive statistics mean, standard deviation, and proportion were used to characterize the sample. Analyses of the unique relationships of the m walk time and self-efficacy for the m walk with both the MAT-sf and the PAT-D mobility subscale were conducted using general linear models; group comparisons including BMI classifications were made using t -tests or analysis of variance.
These analyses were conducted using SAS 9. Descriptive data illustrate that The most common comorbidity was hypertension at The item parameters for the MAT-sf showed only slight changes in the recalibrated set, with eight items being unaffected data not shown.
For two items, 1 and 2, the response categories had to be collapsed from 4 to 3 because the category characteristic curves showed poor performance as a higher ability category was dominated by a lower ability category.
The category response curve is a graphical representation of the probability of answering an item with a given response at a particular level of ability on the construct being measured; here, ability represents mobility. A steeper category response curve generally suggests higher discriminating power of the item or item category at the location where the curve has its steepest slope.
The information curve, denoted by the solid black line, indicates the amount of information contained in each item. Higher information suggests more accurate estimates of ability for a particular item or category.
The correlation between scores using the original parameters and the new parameters approached unity 0. 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. The four lines represent the probability of each response across the range of function and the y -axis is on the left.
Individual item fit statistics also suggested that item-level goodness of fit was acceptable. The p values of the chi-square-based marginal fit statistic for the 10 items ranged from 0. Differential item functioning analyses were conducted for sex because it is well known that men and women differ in their perceptions of physical functioning. We found neither uniform nor nonuniform differential item functioning for sex. Finally, Figure 2 provides a plot of the MAT-sf scores versus the standard errors for these scores.
As expected, this relationship was U shape. Additionally, there was only 0. Our first analyses involved linear models that jointly regressed m walk time and self-efficacy on both MAT-sf scores and the PAT-D mobility subscale. Table 2 provides the means for between-group comparisons on the MAT-sf for BMI classifications and several comorbidities.
This follow-up test revealed that participants with a BMI from 35 to Although we could not test for a curvilinear relationship due to the small number with a BMI less than Comorbidities that adversely affected MAT-sf scores included hypertension, arthritis, and diabetes see Table 2.
The LIFE Study is the largest multicenter clinical trial to date to examine whether physical activity can delay major mobility disability among older adults of age 70—89 with compromised lower extremity function. In addition, participants had to be sedentary to qualify, yet able to complete a m walk in less than or equal to 15 minutes. The current investigation used baseline data to recalibrate items in the MAT-sf using item response theory, explored several novel clinical questions related to this measure, and replicated several analyses from the original psychometric paper 7.
Results of the recalibration procedures were highly consistent with previous findings reported on the MAT-sf items 10 and speak to the robustness of the item response theory-derived scoring algorithm used for this measure. There was an almost imperceptible loss in information following recalibration of two items and the correlation between the original and revised scoring approached unity.
One of the most interesting findings of this study were the results from linear models in which the m walk time and self-efficacy related to performing the m walk were regressed on scores of MAT-sf and PAT-D mobility subscale. In both analyses, performance on the m walk and a related measure of self-efficacy shared significant variance with both outcomes; the magnitude of the effects for both variables were comparable. In fact, in a prospective epidemiological study, we found that decline in timed stair climb performance over a month period among older adults with knee pain, who had low leg strength, was dramatically more pronounced among those whose baseline confidence in their ability to climb stairs was low compared with high This differential in explained variance supports the measurement advancement inherent in the MAT-sf.
The relationship observed between BMI categories and MAT-sf scores in this cohort of older adults is consistent with reports suggesting that excessive body weight is a risk factor for decline in mobility 21— However, it would appear that there is some protective effect associated with older adults being overweight, whereas the greatest compromise in mobility occurred in older adults who were more than or equal to Class II obesity.
In a pilot study that was conducted for the main LIFE trial, Manini and colleagues 25 reported that obesity attenuated the positive effect that the physical activity intervention had on improvement in m walk time.
Thus, although the current cross-sectional data would seem to support the position that weight loss is not warranted for older adults who are overweight or have class I obesity, such a conclusion seems premature. That is, weight loss in conjunction with increased physical activity is considerably different than weight loss alone and may well be preferable to assuming that being overweight or having class I obesity is health protective.
It is also worth noting that Consistent with past research using self-reported measures of disability, participants in the LIFE Study who had arthritis 29 , 30 , hypertension 31 , 32 , or diabetes 33 had lower scores on the MAT-sf than those without these chronic health conditions, albeit the magnitude of these effects were small.
Also, replicating our previous work 7 , MAT-sf scores were higher for men than for women and were directly related to performance on the SPPB. Of interest is the fact the MAT-sf scores exhibited a relatively normal distribution with only 0. The strengths of this investigation include a large sample size, advanced statistical methods employed to evaluate the measurement properties of the MAT-sf, and an interesting finding regarding the relationship between self-efficacy for m walk performance and MAT-sf scores after controlling for actual walk time.
Limitations include the cross-sectional nature of the study design and the fact that participants were excluded if their SPPB scores exceeded 9. The MAT-sf video technology offers a unique methodological advancement in the assessment of mobility; however, the current version does not include items related to transfer skills such as getting into or out of a bed or chair.
In summary, the MAT-sf scoring algorithm was found to be robust. Whereas the m walk time was related to MAT-sf scores, self-efficacy for performing this test had an equally important relationship with the MAT-sf even after controlling for actual walking performance. Scores on the MAT-sf were lower when BMI was more than or equal to 35, compromised by several comorbidities, and were related to sex and performance on the SPPB in the expected direction. Thus, we conclude that the MAT-sf provides an innovative and valid tool for assessing self-report mobility in older adult populations that have evidence of mild to modest deficits in physical functioning.
The longitudinal data in LIFE will enable us to evaluate the relative contributions of self-report and performance-based measures of mobility on important health outcomes. Studies of illness in the aged. Google Scholar. Rosow I Breslau N. A Guttman health scale for the aged. J Gerontol. A prospective study of long-term care institutionalization among the aged. Ann Surg. Self-reported mobility in older patients predicts early postoperative outcomes after elective noncardiac surgery.
Frailty as a predictor of surgical outcomes in older patients. Risk factors and outcomes for postoperative delirium after major surgery in elderly patients. PLoS One. Timed stair climbing is the single strongest predictor of perioperative complications in patients undergoing abdominal surgery. Development and validation of a video-animated tool for assessing mobility. The MAT-sf: clinical relevance and validity. Obesity, intentional weight loss and physical disability in older adults.
Obes Rev. Slower walking speed forecasts increased postoperative morbidity and 1-year mortality across surgical specialties.
Advanced age is a risk factor for post-operative complications and mortality after a pancreaticoduodenectomy: a meta-analysis and systematic review. HPB Oxford. Article Google Scholar. Download references. Sunghye Kim, Stephen B. You can also search for this author in PubMed Google Scholar.
SKim and LG were responsible for the study conception and design. All authors read and approved the final manuscript. Correspondence to Leanne Groban. All study subjects provided a written informed consent. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Reprints and Permissions. Kim, S. Self-reported mobility as a preoperative risk assessment tool in older surgical patients compared to the American College of Surgeons National Surgical Quality Improvement Program.
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