The Virtual Short Physical Performance Battery

Transcription

1 Journals of Gerontology: MEDICAL SCIENCES, 015, 1 9 doi: /gerona/glv09 Research Article Research Article The Virtual Short Physical Performance Battery Anthony P. Marsh, 1 Abbie P. Wrights, 1 Eric H. Haakonssen, 1 Meredith A. Dobrosielski, 1 Elizabeth A. Chmelo, 1 Ryan T. Barnard, Anthony Pecorella, Edward H. Ip, and W. Jack Rejeski 1 1 Department of Health and Exercise Science, Wake Forest University, Winston-Salem, North Carolina. Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina. Address correspondence to Anthony P. Marsh, PhD, Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC marshap@wfu.edu Abstract Background. Performance-based and self-report instruments of physical function are frequently used and provide complementary information. Identifying older adults with a mismatch between actual and perceived function has utility in clinical settings and in the design of interventions. Using novel, video-animated technology, the objective of this study was to develop a self-report measure that parallels the domains of objective physical function assessed by the Short Physical Performance Battery (SPPB) the virtual SPPB (vsppb). Methods. The SPPB, vsppb, the self-report Pepper Assessment Tool for Disability, the Mobility Assessment Tool-short form, and a 400-m walk test were administered to 110 older adults (mean age = 80.6 ± 5. years). One-week test retest reliability of the vsppb was examined in 30 participants. Results. The total SPPB (mean [±SD] = 7.7 ±.8) and vsppb (7.7 ± 3.) scores were virtually identical, yet moderately correlated (r =.601, p <.05). The component scores of the SPPB and vsppb were also moderately correlated (all p values <.01). The vsppb (intraclass correlation =.963, p <.05) was reliable; however, individuals with the lowest function overestimated their overall lower extremity function while participants of all functional levels overestimated their ability on chair stands, but accurately perceived their usual gait speed. Conclusion. In spite of the similarity between the SPPB and vsppb, the moderate strength of the association between the two suggests that they offer unique perspectives on an older adult s physical function. Key Words: Aging Lower extremity physical function Animation. Decision Editor: James Goodwin, PhD Assessing physical function in older adults is a critical step in understanding disability and its prevention. Performance-based measures are popular for this purpose because they are objective, reproducible, and sensitive to change, and focus on actual capacities (1,). However, performance-based tests can be time-consuming, require the availability of trained staff, and often demand dedicated space for administration (1,3,4). Self-report instruments of physical function are popular because they avoid these limitations; however, they are frequently criticized because they are based on perceptions of capacities, vary widely in the phrasing of questions and response items, and assume that people understand the content of questions that are being asked (1,5). Although there are pros and cons of both approaches, several reports suggest that each is valuable because both offer unique and therefore complementary information about function (5 7). The Author 015. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For permissions, please journals.permissions@oup.com 1

2 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No. 00 Typically, the association between performance-based and selfreport assessments of activities is low to moderate (,4,5,7 10). One explanation for this is that the instruments measure different aspects of the same construct, that is, actual versus perceived ability to do a task (8). However, it is also true that self-report tests of function rarely capture the same domains of function being assessed with performance-based measures. In other words, there is a lack of congruence in the assessment of the underlying construct (5,11,1). Interestingly, Guralnik and colleagues found that, of participants unable to complete a 4-m walk at usual pace, 13.6% stated that they could walk a half mile unassisted, suggesting that participants either misunderstood the question being asked or had no concept of what it meant to walk for a half mile (13). Likewise, in a comparison of the Functional Status Questionnaire (FSQ) and the Physical Performance Test (PPT), Reuben and colleagues (5) reported that 6% of 83 participants reported no difficulty in eating on the FSQ, but when asked to simulate the task as part of the PPT the same participants all scored in the lowest category. Similarly, Brach and colleagues (8) reported that 60% of their participants exhibited a ceiling effect on the FSQ whereas only 7% achieved a perfect score on the PPT. In fact, incongruence between self-report and performance-based measures has been estimated at between 5% and 35% with older adults both overestimating and underestimating their functioning (14). Therefore, even when there is reasonable agreement in the construct being assessed, incongruence between actual and perceived function is reported. The reliable identification of older individuals with a mismatch between their actual and perceived function may have value in a clinical or intervention setting (14,15). For example, this information could be used to guide strategies that mitigate fall risk for inpatients who believe that their balance is better than it is or to adapt a behavioral intervention to assist those who have sufficient physical capacity to engage in an activity, but believe that they are unable to do so. We have pioneered the use of animated videos of physical tasks to help older adults better understand task demands and help with the complex decision making required to determine self-reported ability (16,17). Here, we extend this work to focus on the Short Physical Performance Battery (SPPB) (13), a widely used performance-based assessment of lower extremity function for older adults that is associated with institutionalization, morbidity, and mortality. The primary objective of this study was to develop a measure of perceived physical function, the virtual SPPB (vsppb), that directly parallels the domains of function assessed by the SPPB and then to compare results from the two forms of assessment. We expected that scores on the two measures would not be isomorphic; rather, they would be only moderately correlated. The secondary objective was to conduct an exploratory analysis of factors that may influence incongruence between the SPPB and vsppb; specifically, age, sex, minutes of moderate-to-vigorous physical activity (MVPA), and level of lower extremity function. It should be noted that we do not propose that the vsppb should be used as a replacement for the SPPB. The two provide different information. Also, the vsppb is not a measure of self-efficacy; one would need to ask can you do this task, and also how confident are you that you can do this task, and use the appropriate scale of measurement for selfefficacy (0% 100%). Methods Testing Overview A total of 110 participants were recruited from the local community in Winston-Salem, North Carolina. Seventy-nine individuals were previously enrolled in the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) study at the Wake Forest Field Center (18). They were contacted as part of a follow-up study, which assessed their function years after the completion of the LIFE-P intervention (19). Major inclusion criteria at the beginning of the LIFE-P study were as follows: men and women of age years, SPPB summary score less than 10, ability to complete the 400-m walk in 15 minutes at baseline, and sedentary (<0 minutes of exercise each week for the past month). Individuals were excluded if they had a major medical or psychiatric condition that might pose a risk for either safety or intervention compliance or if they had a Mini Mental State Examination score less than 1. Complete details can be found in the design paper for the LIFE-P (0). We also tested 31 individuals at a local continuing care retirement community to increase the sample size. These individuals were living independently at the continuing care retirement community and were recruited based on the inclusion and exclusion criteria described earlier. All assessments were completed at a university laboratory unless participants were unable or unwilling to leave their home, in which case the assessments were completed at their home. This study was approved by the Institutional Review Board and all participants provided written informed consent prior to their participation. All participants were tested in a single 60-minute session by two trained personnel. Demographic and anthropometric variables were collected followed by the measures of lower extremity function. Order of testing for the vsppb and SPPB was randomly assigned. A sample of 30 participants was recruited to examine the 7-day test retest reliability of the vsppb. Short Physical Performance Battery The lower extremity function was measured using the SPPB (13). The study personnel who administered the SPPB were trained and given detailed information prior to testing regarding administration and scoring of the test. Total time to complete the SPPB was ~5 10 minutes per participant. The SPPB consists of: up to three hierarchical balance tasks held for a maximum of 10 seconds each (side-byside stance, modified tandem stance, and tandem stance); two 4-m usual pace walks (fastest walk selected); and rising from a chair five times as fast as possible without the use of the arms. The time measures for each of the three tasks were converted to an ordinal scale with a range of 0 (lowest performance) to 4 (highest performance) based on performance quartiles and a total score (0 1) was obtained by aggregating the three component scores. The SPPB is a predictor of future institutionalization, hospital admission, mortality, and disability (13,1) and improves after a physical activity intervention (). Intraclass correlation (ICC) coefficients range from.88 to.9 for measures made 1 week apart, with a 6-month average correlation coefficient of.78 (3). Virtual Short Physical Performance Battery The vsppb is a novel self-report measure that uses computer animation to present the physical tasks in the SPPB as described in detail below. Figure 1 shows a still frame shot of the video from each component of the vsppb. The software displays the task and the participant is asked if the performance displayed in the video represents

3 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No Figure 1. A still frame shot of each virtual Short Physical Performance Battery component. their perceived ability on that task (yes/no response). The vsppb can be done on a tablet or a touch screen monitor. The figure used in the animations was a wooden artist s mannequin that was race- and gender-neutral. Scoring for the vsppb was consistent with the scoring of the SPPB. Each component of the vsppb was scored from 0 to 4 and the scores on the three components were summed to obtain the total vsppb score from 0 to 1. The total time to complete the vsppb was 3 minutes. living (ADL), and instrumental activities of daily living (IADL). Responses are made on a five-point Likert scale ranging from 1 ( usually did with no difficulty ) to 5 ( unable to do ) or a box can be checked that reads usually did not do for other reasons. The PAT-D is valid and reliable, and sensitive to change. Cronbach alphas for internal consistency for the three domains and overall summary score are all above.7: α =.77 for IADL, α =.76 for ADL, α =.87 for mobility, and α =.8 for the summary score (4,5). Balance The participant was asked the following yes or no questions each accompanied by an animation of the task: Can you balance, unassisted, with your feet next to each other for 10 seconds? Can you balance, unassisted, with one toe next to the other heel for 10 seconds? Can you balance, unassisted, with one foot directly behind the other for 3 seconds? For 10 seconds? The mannequin in the balance animations had a slight sway in their arms and upper torso in order to make the video more realistic. A 3 10 second countdown was shown on the screen, to give the participant a clear indication of the duration of each balanced task. The participants could replay the animation if needed. Gait speed The participants were first asked to take a moment and think about the speed at which they typically walk. They were then shown four animations of the mannequin walking a 4-m distance simultaneously, animation 1 being the slowest pace and animation 4 being the fastest. The participants were asked to choose the animation that best represented their usual walking pace. In animation 1 (score = 1), the mannequin took 1.5 seconds to complete the 4-m distance; animation (score = ) was completed in 8 seconds; animation 3 (score = 3) was completed in 5.8 seconds; and animation 4 (score = 4) was completed in 4.5 seconds. Chair rise The participants were first asked, yes or no, if they were able to stand up from a standard chair one time without using their arms with an accompanying animation. Next, they were shown a series of six animations, each depicting five consecutive chair rises done at progressively shorter durations: 30, 17, 14, 11, 9, and 7 seconds. They were asked to choose the animation that best matched their perceived ability. Each animation duration was chosen with the cutpoints for SPPB scoring in mind..if the participants chose either 30 or 17 seconds, they received a score of 1. They received points for 14 seconds and 3 points for 11 seconds. If they chose 9 or 7 seconds, they received 4 points. Pepper Assessment Tool for Disability The PAT-D self-administered questionnaire consists of 19 items that include a range of activities that assess mobility, activities of daily Mobility Assessment Tool-Short Form Self-reported physical function was assessed with the Mobility Assessment Tool-short form (MAT-sf), a 10-item computer-based assessment of mobility using animated video clips that cover a broad range of tasks (6). Each item is accompanied by an animated video clip together with the responses for that question (number of minutes, number of times, and yes/no). The test was completed on a laptop and the scores were saved to an exportable file. The time required to do the test with instructions from the examiner was ~5 minutes. 400-m Walk Test The 400-m walk test is a modified version of a walk test that was developed by Newman and her colleagues (7). The participants were timed while they walked 10 clockwise laps around a 40-m indoor course as quickly as possible without running, sitting, or the help of another person. The participants were allowed to rest in place and were given a maximum of 15 minutes to complete the 400-m walk. If the participants did not complete the 400-m course, we recorded the distance they walked to the nearest meter and the walking time. For all the participants, we calculated a gait speed in m/s by dividing the distance walked by the time. Minutes of Moderate-to-Vigorous Physical Activity We assessed each participant s self-reported levels of physical activity from a typical week from the past 4 weeks using the Community Health Activities Model Program for Seniors (CHAMPS) Questionnaire (8). The CHAMPS was administered in an interview style by a trained exercise physiologist with extensive experience assessing physical activity in older adults. The number of minutes per week spent doing physical activities with an intensity considered to be moderate or greater ( 3 metabolic equivalents) was recorded (MVPA). Statistical Analyses We used IBM SPSS Statistics, Version 1, for all statistical analyses. Tests for normality were performed to determine whether data transformations were appropriate and if nonparametric analyses would be required. We found, using a Shapiro Wilk test of normality, that

4 4 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No. 00 SPPB and vsppb total scores were not normally distributed; both were skewed to the right with comparable shape and range of distribution. Descriptive statistics were used to describe the demographic characteristics and outcomes for the sample. The Spearman correlations were used to explore the relationship between the SPPB and vsppb total score and the three component scores. We also examined Spearman correlations between the SPPB, vsppb, and the PAT- D, MAT-sf, 400-m gait speed, and MVPA. The test retest reliability of the vsppb was examined by performing ICCs on a subsample of participants (n = 30) collected 7 days apart. We compared the internal consistency of the SPPB and vsppb using Cronbach s alpha. Multiple linear regression analysis was used to identify factors that influence the discrepancy between the SPPB and the vsppb: specifically age, sex, MVPA, and level of function. Separate models were conducted for the level of function variables, one using scores from the SPPB and the other using scores for the vsppb. In addition, to enhance interpretation of the results, the participants were split into quartiles based on total SPPB scores. We used analysis of variance to compare differences between the SPPB and the vsppb (and the three components) by quartiles of function, using Tukey post hoc tests as a follow-up to significant group effects. Results A total of 110 participants were recruited in this study, 30 male participants (7.3%) and 80 female participants (7.7%). The mean age of the participants was 80.6 ± 5.19 years (range: 65 94) and they were predominately white (84.5%). The total SPPB and vsppb scores as well as the three component scores (balance, gait, and chair rise), PAT-D summary and component scores (mobility, ADL, and IADL), MAT-sf scores, 400-m gait speeds, and MVPA are presented in Table 1 aggregated and stratified by sex. There was a remarkable agreement in the total scores of the SPPB and vsppb for men, women, and for the combined sample with a mean difference of only 0.04 points in all 110 participants. This close agreement was also observed between each component of the SPPB and vsppb. There was a moderate association, Spearman r =.601 (p <.01), between the SPPB and vsppb total scores as well as between the component scores of the SPPB and vsppb, ranging from an r =.39 for chair rise to.55 for gait speed (Table ). The associations between the SPPB total score and its three components and the vsppb and its three components were very similar, ranging from an r =.69 to.84. The SPPB and vsppb total scores and gait speed scores were significantly correlated with the PAT-D summary score as well as the mobility, ADL, and IADL component scores (Table 3). The SPPB and vsppb chair rise scores were significantly correlated with all PAT-D scores except the IADL component. The SPPB balance score was associated with PAT-D summary and mobility scores and the vsppb balance score was associated with PAT-D summary, mobility, and ADL components. The SPPB and vsppb total and component scores were significantly correlated with the MAT-sf and the 400-m gait speed scores (except for the vsppb balance score). Both the SPPB and vsppb were significantly associated with MVPA (r for both =.3). The test retest reliability was examined in 30 participants (mean [±SD] age = 79.3 ± 5.1 years) on two occasions 7.4 (±.) days apart. Both the SPPB (ICC =.889, p <.05) and vsppb (ICC =.896, p <.05) were very reliable. We noted that the vsppb at visit was significantly different (p <.05) from visit 1, increasing by 1.13 (±1.55) points, likely due to participants remembering the actual SPPB tasks from visit 1. So we recruited a new, convenience sample of 5 participants. They performed only the vsppb on two occasions 7.0 (±1.) days apart. The ICC for the vsppb increased to.963 (p <.05). The SPPB and vsppb were internally consistent with Cronbach alphas of.67 and.70, respectively. Since the order of SPPB and vsppb testing was randomized, we also tested for an order effect. There was a significant interaction between the randomization order (SPPB or vsppb) and the task (p =.03). An individual s level of function, defined by the total SPPB score, was a significant predictor of the difference between the total SPPB and vsppb scores, and the balance and chair rise components, but not the gait speed component (Table 4). Interestingly, when the vsppb total score was used as the predictor, the standardized betas increased and age was a significant predictor for all differences in the component scores (Table 5). It should be noted that the SPPB vsppb difference score was normally distributed. Age was a significant predictor of the difference between actual and virtual chair stand scores. The individuals in the three lowest quartiles of age tended to overestimate their performance whereas the individuals in the highest quartile of age tended to underestimate their ability. The amount of MVPA was not a significant predictor of the difference between the SPPB or vsppb total or component scores. It should be noted that including the order of testing as a predictor in the regression did not alter the standardized beta weights or the interpretation of the analyses in any meaningful way. To further investigate the role of function in predicting the difference between actual and perceived function, we split the SPPB scores for the sample into quartiles (Figure a d). The analysis of variance was significant for the difference in total score (p =.00), balance component (p <.001), and gait speed (p =.035), but not for the chair stand component (p =.0). The post hoc tests showed that the participants with the lowest function were significantly overestimating their functional ability for the total score and the balance component. The SPPB and vsppb gait speed component scores were congruent in the lowest functioning quartile, but the three highst functioning quartiles tended to underestimate their functional ability. The individuals across all quartiles of function tended to overestimate their ability on the chair stand component. Discussion To examine congruence between the actual and the perceived physical function, we created a self-report instrument designed to replicate the tasks that comprise the SPPB, a widely-used and clinically relevant performance-based instrument, and the virtual, self-report version of the SPPB the vsppb. The vsppb had excellent test retest reliability. Although the vsppb was designed to be identical to the SPPB, we were still surprised by the very close agreement between the mean scores of the two measures. However, we observed only a moderate correlation between the SPPB and vsppb, suggesting that there are fundamental differences between the performance-based and self-report measure of lower extremity physical function. In previous research, only a modest correlation has been reported between the performance-based and self-report measures of activities (r =.3.50) (,4,10,9). Alexander and colleagues (30) compared the SPPB components to self-report of either dependence in ADLs or self-reported walking ability and found the strongest association to be between the self-reported walking ability and the SPPB walking task. This suggests that correlations are higher when selfreport questions are congruent with performance-based assessments. Our data support this observation. We found significant moderate

5 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No Table 1. Performance-Based and Self-reported Physical Function Scores Male (n = 30) Female (n = 80) Total Sample (n = 110) Mean ± SD Range % at floor, % at ceiling* Mean ± SD Range % at floor, % at ceiling* Mean ± SD Range % at floor, % at ceiling* SPPB total score 7.53 ± %, 0% 7.74 ± %, 10% 7.68 ± %, 7.3% SPPB balance.97 ± %, 46.7%.86 ± %, 40%.89 ± %, 41.8% SPPB gait speed.97 ± %, 36.7% 3.10 ± %, 50% 3.06 ± %, 46.4% SPPB chair rise 1.57 ± %, 3.3% 1.78 ± %, 15% 1.7 ± %, 11.8% vsppb total score 7.33 ± %, 10% 7.76 ± %, 13.8% 7.65 ± %, 1.7% vsppb balance.57 ± %, 43.3%.99 ± %, 53.8%.87 ± %, 50.9% vsppb gait speed.50 ± %, 0%.59 ± %, 7.5%.56 ± %, 5.5% vsppb chair rise.7 ± %, 33.3%.19 ± %, 7.5%.1 ± %, 9.1% PAT-D summary 1.43 ± ± ± PAT-D mobility 1.59 ± ± ± PAT-D ADL 1.35 ± ± ± PAT-D IADL 1.39 ± ± ± MAT-sf 49.7 ± ± ± m gait speed (m/s) 0.85 ± ± ± MVPA (min/wk) 15.0 ± ± ± Notes: ADL = activities of daily living; IADL = instrumental activities of daily living; MAT-sf = Mobility Assessment Tool-short form; MVPA = moderate-to-vigorous physical activity; PAT-D = pepper assessment tool for disability; SPPB = Short Physical Performance Battery; vsppb = virtual SPPB. *Participants are at floor if they have the lowest possible score for the test and at ceiling if they have the highest possible score.

6 6 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No. 00 Table. Spearman Correlations Between SPPB and vsppb Scores SPPB Balance SPPB Gait Speed SPPB Chair Rise SPPB Total vsppb Balance vsppb Gait Speed vsppb Chair Rise vsppb Total Actual measure SPPB balance (.57) SPPB gait speed.400*** (.70) SPPB chair rise.316**.61*** (.86) SPPB total.687***.831***.84*** (.80) Virtual measure vsppb balance.391*** ** (.85) vsppb gait speed.350***.550***.498***.59***.330*** (.79) vsppb chair rise.331***.381***.531***.55***.46***.46*** (.93) vsppb total.463***.458***.494***.601***.74***.74.84*** (.93) Notes: The numbers in parentheses are reliability coefficients. SPPB = Short Physical Performance Battery; vsppb = virtual SPPB. **p <.01, ***p <.001 Table 3. Spearman Correlations Between SPPB and vsppb Scores, Physical Function, and Physical Activity SPPB Balance SPPB Gait Speed SPPB Chair Rise SPPB Total vsppb Balance vsppb Gait Speed vsppb Chair Rise vsppb Total PAT-D summary.315**.591***.435***.567***.360***.639***.419***.604*** PAT-D mobility.303**.563***.36***.517***.35***.600***.394***.56*** PAT-D ADL.17*.473***.40***.475***.35**.488***.395***.51*** PAT-D IADL **.03*.300**.1*.43*** *** MAT-sf.393***.600***.407***.579***.393***.658***.514***.657*** 400-m gait speed.533***.815***.6***.80***.01*.683***.383***.544*** MVPA.79**.98**.18*.35**.091.*.378***.34** Notes: ADL = activities of daily living; IADL = instrumental activities of daily living; MAT-sf = Mobility Assessment Tool-short form; MVPA = moderate-tovigorous physical activity; PAT-D = Pepper Assessment Tool for Disability; SPPB = Short Physical Performance Battery; vsppb = virtual SPPB. *p <.05, **p <.01, ***p <.001 positive associations between the total SPPB and the total vsppb as well as between each component of the SPPB and its corresponding vsppb component. However, the moderate correlation also demonstrates that self-report and performance-based assessments of physical function provide unique and complementary information about an individual s function (7,14,31). Both the SPPB and vsppb showed significant correlations with the other measures of physical function PAT-D, MAT-sf, 400-m gait speed, and MVPA. Interestingly, the vsppb showed consistently higher correlations with the two self-report measures (PAT-D and MAT-sf) than did the SPPB, while the SPPB had higher correlations with the performance-based measure, 400-m gait speed. Previously, Brach and colleagues (8) reported that physical activity, defined as the median number of steps per day assessed via accelerometry, was associated with both actual and perceived function. They reported that women who perceived that they had difficulty walking were physically less active than women who perceived that they had no difficulty. We found that MVPA was significantly related to the SPPB and vsppb and their components (except for vsppb balance component) in the expected direction, that is, higher levels of MVAP were associated with greater actual and perceived function. However, the amount of MVPA was not a significant predictor of the difference between actual and perceived function. For example, using the difference between the SPPB and vsppb chair stand components, there was no pattern of overestimating or underestimating function across the spectrum of MVPA. The lack of congruence between the actual and perceived function is likely a result of many factors including sociodemographic and environmental variables, personality, cognitive functioning, and depressive symptoms (4,7,14). However, Guralnik and colleagues (13) reported that there were no differences in cognitive functioning, depression, or educational status between the 33 individuals who were unable to complete a 4-m walk test and self-reported that they had no difficulty walking a half mile and those who were unable to complete the 4-m walk test and self-reported that they could not walk a half mile. Walking 4 m and walking half a mile are clearly different tasks. However, we observed differences between the total and component scores of the SPPB and vsppb, which are very similar, if not identical, reinforcing the notion that there is a fundamental difference between what older adults believe they can do and what they actually can do (9). We did not find sex to be a significant predictor of differences between the SPPB and vsppb total or component scores. In contrast, Kelly-Hayes and colleagues reported that women were significantly more likely than men to self-report more disability with walking compared to observed walking difficulty when assessed by a trained nurse (3). Also, although previous research suggests that community-dwelling older adults tend to underestimate their function (10,3), we did not observe any clear pattern of underestimation or overestimation of function for the total score or the components. On average, we did find that younger participants tended to overestimate their ability on the chair stand compared to participants at the upper end of the age spectrum. In part, this could be due to a lack of familiarity with the task because it is rarely, if ever, done in daily life (five repeated chair stands as fast as possible). However, the chair stand might be a task that is particularly sensitive for identifying individuals with a mismatch between the actual and perceived function because it is challenging and incorporates elements of balance and muscle strength and power.

7 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No Table 4. Regression Table With Age, Sex, MVPA and Actual Level of Function as Predictor Variables for the Difference Between SPPB and vsppb Scores Standardized β t p Total score Age r =.358 Sex p =.006 MVPA Level of function p <.001 Balance Age r =.380 Sex p =.00 MVPA Level of function Gait speed Age r =.4 Sex p =.171 MVPA Level of function Chair rise Age r =.407 Sex p =.001 MVPA Level of function Notes: MVPA = moderate-to-vigorous physical activity; SPPB = Short Physical Performance Battery; vsppb = virtual SPPB. Table 5. Regression Table With Age, Sex, MVPA and Perceived Level of Function as Predictor Variables for the Difference Between SPPB and vsppb Scores Standardized β T p Total score Age r =.606 Sex p <.001 MVPA Level of function p <.001 Balance Age r =.503 Sex p <.001 MVPA Level of function p <.001 Gait speed Age r =.437 Sex p <.001 MVPA Level of function p <.001 Chair rise Age r =.536 Sex p <.001 MVPA Level of function p <.001 Notes: MVPA = moderate-to-vigorous physical activity; SPPB = Short Physical Performance Battery; vsppb = virtual SPPB. The lower extremity function, whether actual or perceived, was a significant predictor of differences between the SPPB and vsppb total, balance, and chair stand scores. Typically people with fewer functional limitations have higher levels of self-efficacy (33,34) and self-efficacy has been shown to buffer functional decline in the face of diminished physical capacity (35). Thus, older individuals with higher function might be expected to overestimate their actual ability. In fact, we found the opposite for the total score and the balance and gait speed components. The participants in the lowest quartile of lower extremity function tended to overestimate what they could do, whereas those in the three highest quartiles underestimated their capacity on the total score and the balance and gait speed component scores. The lowest functioning participants had the greatest overestimation in their balance scores, suggesting that this task may play a large role in understanding the incongruence between the total SPPB and vsppb scores. One of the limitations of this study is a relatively small, mostly white female sample, all of whom were living independently in the community. We did not assess cognitive function or self-efficacy for lower extremity function and cannot comment on the role they may have played in the differences between the SPPB and vsppb. Our data may not be applicable to older adults who are hospitalized or with more severe lower extremity dysfunction. Further research is necessary to provide evidence for whether or not the vsppb is sensitive to change in both research and clinical settings. Finally, there is considerable variability across the literature in the way both self-reported function and performance-based function have been assessed and compared. This applies to the measurement scales that have been employed and to the constructs that have been assessed and compared with some studies using assessments of ADLs (eg, 8,10,3), and others using performance tests like the PPT (6,36). Caution should be used when assessing the results of studies that purport to have measured actual and perceived physical function.

8 8 Journals of Gerontology: MEDICAL SCIENCES, 015, Vol. 00, No. 00 Mean Difference between SPPB and vsppb Total Scores a Quartiles Mean Difference between SPPB and vsppb Balance Scores b Quartiles Mean Difference Between SPPB and vsppb Gait Speed Score c Quartile Mean Difference Between SPPB and vsppb Chair Stand Scores d Quartile Figure. (a d) Mean difference (SD) between Short Physical Performance Battery and virtual Short Physical Performance Battery. (a) Total scores, (b) balance scores, (c) gait scores, and (d) chair rise scores among quartiles of function. A negative score denotes an overestimation of one s actual function. The quartiles were created based on SPPB score: (1) score of 5 (n = 5), () score of 6 7 (n = 5), (3) score of 8 9 (n = 6), and (4) score of 10 1 (n = 34). Although it was specifically modeled on the SPPB, the vsppb provides unique information on lower extremity function. The initial rationale for this study was not to develop a surrogate measure of lower extremity physical function but rather to create a method to reliably assess self-perceived function that could be compared with the actual performance on the same task. We do not believe that one form of assessment is better than the other. Unfortunately, self-report measures are often perceived as inferior to performance-based assessments. This is surprising because limitations in physical function are precursors to disability, which is by definition a construct based on the perceptions of one s abilities. Therefore, we posit that self-report offers insights about the pathway to disability, which a performance-based measure cannot reveal, but both offer important information about an older adult s capacity for physical function. In fact, our point is demonstrated by the observation of an order effect. It is not at all surprising that the individuals perception of their function would be influenced by actually doing the SPPB tasks prior to responding to the vsppb. For this reason, it is recommended to administer the vsppb prior to the SPPB when both tests are desired. Nevertheless, we did a find remarkable agreement, on average, between the vsppb and SPPB and the correlations between the SPPB and vsppb with the other instruments were consistent and of the same order of magnitude. Therefore, in situations where a performance test is not feasible, for example, an individual confined to bed rest as a result of illness or injury, the vsppb could be used to rapidly assess function, even remotely. More importantly, our data show that the vsppb can be used in combination with the SPPB to identify individuals who significantly underachieve or overachieve based on their perceived versus actual function and might provide a broader and richer understanding of aging and disability. Future work will need to focus on the ongoing process of validation, including testing diverse samples, assessing the sensitivity of the vsppb to physical activity and other behavioral interventions, and testing the utility of the instrument to identify individuals with large variance in their actual and perceived physical function.

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