Convergent and known-groups validity of common protocols for mobility measurement among community-dwelling adults

Convergent and known-groups validity of common protocols for mobility measurement among community-dwelling adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Convergent and known-groups validity of common protocols for mobility measurement among community-dwelling adults Qiukui Hao, Ayse Kuspinar, Gordon Guyatt, Parminder Raina, Lauren Griffith, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9407249/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background and aim: Performance-based measures, including the Timed Up and Go (TUG), gait speed, chair-rise, and Single-Leg Stance (SLS), are important assessments for mobility. However, the comparative psychometric strength of their various protocols remains poorly defined. This study evaluated the validity of these measures to guide evidence-based selection. Methods: This cross-sectional analysis of 157 community-dwelling adults (mean age: 70 years) assessed convergent validity by correlating different protocol measures with self-reported physical function and physical activity. We defined convergent validity as Spearman’s correlations (ρ) exceeding 0.1 for weak, 0.3 for moderate and 0.5 for strong association. To determine each measure's ability to discriminate between groups, we calculated the Area Under the ROC Curve (AUC), with an AUC of 0.70 considered acceptable. Results: Most protocols demonstrated moderate to strong convergent validity with self-reported physical function (ρ: 0.39 to 0.57) and weak or moderate validity for physical activity, except for the chair rise without arm use. Although most protocols could discriminate physical functional limitation, discriminative abilities were mixed for perceived fall risk; gait speed, SLS, and TUG-fast proved valid, but TUG-normal, TUG-cognitive, and the chair rise test were not. No single protocol met the pre-specified threshold (AUC = 0.70) for discriminating fall history, although the TUG-fast approached it (AUC = 0.68, 95% CI: 0.56–0.80). Conclusion: While common mobility protocols validly assess physical function and perceived fall risk, their utility in identifying fall history is limited. TUG-fast emerged as a particularly robust tool for discriminating physical function limitation and fall history. Geriatric assessment falls Physical functional performance Timed Up and Go Figures Figure 1 Key points Most variations of common performance-based mobility tests demonstrate moderate to strong validity for assessing physical function and perceived fall risk in community-dwelling older adults. No single mobility test protocol met the acceptable threshold for discriminating individuals with a recent history of falls. The Timed Up and Go performed at a fast pace (TUG-fast) emerged as the most robust protocol. Why does this paper matter? Clinicians and researchers frequently use mobility assessments such as the TUG and gait speed, but wide variations in administration protocols complicate the interpretation of patients’ results. This study provides evidence and recommendations to help healthcare professionals select the most robust test protocols. Background Mobility is fundamental to functional ability and plays a critical role in healthy aging.[ 1 ] As individuals age, mobility declines can lead to adverse outcomes, including functional limitations, increased risk of falls, and higher healthcare utilization.[ 2 ] Functional limitations and disabilities significantly impact the quality of life of older adults and increase costs for the health care system.[ 3 , 4 ] Falls are the leading cause of injury-related morbidity and mortality among older adults and contribute significantly to health care costs.[ 5 ] Identifying individuals with limited mobility or those at risk of mobility impairment could help delay functional decline, prevent falls, and promote better overall health and healthy aging. Comprehensive mobility assessment frameworks consider three distinct facets: perceived mobility, actual mobility, and locomotor capacity for mobility.[ 6 ] Researchers commonly assess perceived and actual mobility using self-report instruments such as the Late-Life Function and Disability Instrument -Function Component (LLFDI-FC) and the Physical Activity Scale for the Elderly (PASE), with a higher score indicating better function or a higher physical activity level.[ 7 , 8 ] These tools have demonstrated acceptable reliability and validity in evaluating physical function and activity levels in older adults.[ 7 , 8 ] In contrast, performance-based tests conducted in controlled settings are widely used to assess locomotor capacity for mobility. These tests offer a more objective measure of mobility compared to self-reported assessments. Investigators and clinicians commonly use a range of performance-based measures, including the Timed Up and Go (TUG) test, gait speed, chair-rise test, and single-leg stance (SLS) test in both research and clinical settings. These tests have demonstrated moderate to excellent reliability for community-dwelling middle-aged and older adults. [ 9 – 14 ] However, variations in administration protocols are common. For instance, TUG may be performed at a normal or fast walking pace; gait speed can be measured over different course lengths; the chair-rise test may allow or restrict arm use; and the single-leg stance can be assessed on either leg or the participant’s preferred leg.[ 14 ] These protocol differences can affect the reliability of specific tests across different age groups of participants.[ 14 ] Such variations may also influence the validity of these measures. Although individual studies have demonstrated associations between performance-based measures and outcomes such as physical activity, functional limitations, and fall risk, most have examined these relationships in isolation.[ 15 – 19 ] For instance, the TUG predicts future functional dependency,[ 15 ] and single-leg stance has been linked to functional limitations and fall risk.[ 19 ] Systematic reviews have found only low-quality evidence to support the use of these measures in identifying individuals at high risk of falling.[ 20 – 22 ] Moreover, few studies have directly compared the construct validity of these measures or evaluated how protocol variations affect their ability to identify functional limitations and fall risk. To address these gaps, this study aims to examine the construct validity of four commonly used performance-based measures and their protocol variations for locomotor capacity for mobility: TUG, gait speed, chair-rise, and SLS, using data from a sub-study of the Canadian Longitudinal Study on Aging (CLSA). CLSA is a large-scale, national research initiative that follows approximately 50,000 Canadians aged 45 years and older, exploring the biological, medical, psychological, social, and economic dimensions of aging.[ 23 ] The present study provides evidence regarding convergent construct validity using related measures of physical activity and functional limitations, as well as known-groups validity in relation to fall risk and functional limitations. By directly comparing these measures and their protocol variations, we provide evidence to guide the selection of appropriate performance-based measure protocols for assessing mobility capacity in community-dwelling adults aged 50 years or older. Methods Using data from a previously published sub-study of the CLSA focused on reliability, we examined the validity of TUG, chair-rise, gait speed, and SLS tests and their common protocol variations for physical limitations and physical activity levels [ 12 , 24 , 25 ]. Briefly, the study included consecutive participants who participated in a baseline assessment session during their routine CLSA visit (n = 147). According to the CLSA protocol ( https://www.clsa-elcv.ca/researchers/physical-assessments ) [ 8 ] and descriptions in the study data collection sheet, CLSA research staff or postgraduate students in Rehabilitation Science at McMaster University administered these measures. The research staff also completed physical function and physical activity questionnaires. The Hamilton Integrated Research Ethics Board approved the study (2018-5280-GRA). Performance-based measures and their common protocol variations Four commonly used physical performance-based measures were administered in accordance with the CLSA operating procedures, including TUG, gait speed, chair rise, and SLS. For the sub-study, we incorporated common administration protocol variations to these measures. The TUG test evaluates functional mobility and balance by asking participants to rise from a chair 46 cm in height, walk three meters, turn around, return to the chair, and sit down. Participants were allowed to use their usual assistive devices or gait aids. The test was conducted in three variations: TUG-normal, where participants were instructed to “walk at your comfortable or normal pace”; TUG-fast, with the instruction to “walk as quickly and as safely as possible”; and TUG-cognitive, which involved walking while counting backward by ones or threes at a comfortable and safe pace. Of the 147 participants, all completed the TUG-normal and TUG-cognitive protocols. A subset of 113 individuals performed the normal-fast protocol. The chair rise test, also known as the Five-Times-Sit-to-Stand test, measures lower limb strength and balance. Participants were instructed to stand up and sit down five times as quickly as possible after the evaluator said “Go,” with timing starting at that cue and ending when the participant was fully standing for the fifth time. Two protocol variations were used: one without arm use, where participants crossed their arms over their chest, and one with arm use, where participants were told, “you may use your arms to rise from the chair.” For the chair rise test, 144 participants completed the protocol without arm use, and 143 completed the protocol that allowing the arm use. Gait speed was assessed by measuring the time it took participants to walk either 3 or 4 metres at their usual pace from a static start. The standardized instruction was: “After I say, ‘ready, set, go,’ please walk at your usual walking pace until I say to stop.” Both distances were used to accommodate different testing environments while maintaining consistency in administration. All participants competed both protocols for gait speed test. The SLS test evaluates static balance by timing how long participants can stand on one leg, up to a maximum of 60 seconds. Timing began when the foot left the ground and ended when the foot touched the ground again or balance was lost. Two protocol variations were included: one recording time for both the right and left legs, and another using the participant’s preferred leg for two trials. Both the mean and maximum durations were recorded to assess balance performance. For the chair rise test, 142 participants completed the preferred-leg protocol and 141 completed the both-legs protocol. Comparison measures We used the self-reported PASE to quantify physical activity levels over the previous seven days. The PASE scores are derived by weighting leisure, household, and occupational tasks, starting with 0 and no theoretical maximum, and with higher scores representing greater physical activity. Previous studies indicated that the PASE has acceptable reliability and validity for measuring physical activity.[ 8 ] To measure physical function limitations, we used the LLFDI-FC, which provides a scaled score from 0 to 100, with higher scores reflecting better physical function.[ 26 ] The LLFDI-FC showed good test-retest reliability (ICC = 0.77 to 0.98) and sensitivity to change in older adults.[ 7 ] In the absence of a standardized cutoff for defining functional limitation using the LLFDI-FC, we used our cohort's median score of 70 as the threshold. This approach considers that the reported mean scores for adults with slight and no functional limitations are 65.6 and 75.6, respectively.[ 26 ] We defined a fall as "when you find yourself suddenly on the ground, without intending to get there, after you were in either a lying, sitting, or standing position." We asked patients, "How many times in the past year did you fall?" and recorded their response. Participants were categorized as non-fallers (without falls) or fallers (with at least one fall). Participants' perceptions of their own fall risk were collected by asking, "In general, how would you rate your risk of falling?" with the following response options: extremely low, low, medium, high, and extremely high. The participants were categorized into either a low-risk group (who responded “extremely low”, “low” or "medium") or a high-risk group (who responded "high" and “extremely high”). Statistical analysis We performed all statistical analyses using R version 4.2 in RStudio, setting the significance level at α = 0.05. To assess the distribution of continuous variables, we applied the Shapiro-Wilk test. For performance-based measures, most data were non-normally distributed, so we reported medians and interquartile ranges. To standardize the interpretation across all variables, time-based performance measures (e.g., TUG, chair-rise time, SLS) were converted to their reciprocals (1/s). To avoid the high risk of type II error associated with a small sample, we did not formally compare the correlation strengths or discriminative performances of related protocols within the same test (e.g., TUG-normal vs. TUG-fast). To evaluate convergent validity, we assessed the association between each performance-based measure and the total scores of the LLFDI-FC and PASE. Given most performance-based measure data were non-normally distributed, we calculated Spearman's correlation coefficients to quantify these associations. We assessed known-groups validity by testing whether each performance-based measure could differentiate participants based on physical function limitation (no or mild limitation versus moderate or severe limitation), fall history (non-fallers versus fallers), and perceived fall risk (low risk versus high risk). To quantify the discriminative ability of each measure, we used the Area Under the Receiver Operating Characteristic (ROC) curve (AUC). Validity hypotheses We hypothesized that all performance-based measures would moderately to strongly correlate with physical function (LLFDI-FC) and weakly to moderately with physical activity (PASE). The strength of the correlations was interpreted as strong (ρ ≥ 0.50), moderate (ρ = 0.30–0.49), or weak (ρ = 0.10–0.29).[ 27 ] We hypothesized that the performance-based measures would adequately discriminate between participants based on physical function limitation, fall history, and perceived fall risk. We set a threshold of AUC of 0.70 for acceptable discrimination.[ 28 ] Results Participant Characteristics A total of 157 community-dwelling adults 50 years and older (mean age 69.4 years) of whom 115 proved "Non-fallers" and 42 "Fallers" (n = 42, 27%) were included in the analysis. Table 1 presents the demographic and clinical characteristics of both groups. Compared to non-fallers in the past year, participants who experienced at least one fall had a higher number of medications, lower median scores for physical function as assessed by LLFDI-FC, a greater likelihood of using a gait aid, and having a higher perceived risk of falling. Table 1 Demographic Characteristics of the Participants Age (years), mean (SD) Non-fallers N = 115 Fallers N = 42 69.2 (10.3) 70.1 (9.3) Age groups, n (%) 50–64 39 (33.9) 9 (28.1) 65–74 39 (33.9) 11 (34.4) 75+ 37 (32.2) 12 (37.5) Sex Male 62 (53.9) 14 (43.8) Female 53 (46.1) 18 (56.2) Height (cm), mean (SD) 169.5 (9.7) 167.9 (10.2) Weight (Kg), mean (SD) 82.8 (16.3) 78.4 (18.2) BMI(kg/m 2 ), mean (SD) 28.8 (4.9) 27.9 (6.6) Number of medications, mean (SD) 2.9 (3.3) 4.6 (6.2) PASE, median [IQR] 136 [99, 174] 140[118, 181] LLFDI-FC, median [IQR] 72 [66, 81] 62 [56, 72] Use of Gait Aid, n (%) Yes 5 (4.3) 6 (18.8) No 110 (95.7) 26 (81.2) Perceived fall risk, n (%) Low Risk 111 (96.5) 27 (84.4) High Risk 4 (3.5) 5 (15.6) Function limitations, n (%) No/Mild 71 (61.7) 9 (28.1) Moderate/Severe 44 (38.3) 23 (71.9) Living alone, n (%) Yes 9 (11.8) 20 (28.2) No 67 (88.2) 51 (71.8) IQR= Interquartile Range; SD= Standard Deviation; PASE = Physical Activity Scale for the Elderly; LLFDI-FC = Late-Life Function and Disability Instrument-Function Component We present the descriptive statistics for the performance-based measures and their variations in the Appendix Table. In the TUG test, participants showed the fastest median time when instructed to move quickly, at 7.53 seconds (the median time of normal pace: 10.25 seconds). For the chair rise tests, participants were slower when not permitted to use their arms compared to when the use of arms was allowed (12.02 vs. 10.50 seconds). Gait speed was slightly faster over a shorter distance (3 meters: 0.91 m/s vs. 4 meters: 0.84 m/s). For the SLS test, the median time (max) from both legs was longer than using only the preferred leg (28.28 vs. 27.45 seconds). Convergent Validity All mobility protocols showed moderate to strong correlations with physical function as assessed by the LLFDI-FC (ρ = 0.39 to 0.57; Table 2 ). The TUG-fast (ρ = 0.60, 95% CI: 0.46 to 0.70), TUG-normal protocol (ρ = 0.57 95% CI: 0.45 to 0.67), 4-meter (ρ = 0.53, 95% CI: 0.46 to 0.70) and 3-meter gait speed tests (ρ = 0.57, 95% CI: 0.46 to 0.70) all showed strong correlations with physical function. The chair-rise protocol allowing arm use (ρ = 0.44, 95% CI: 0.29 to 0.56) and protocol without arm use (ρ = 0.39, 95% CI: 0.24 to 0.52) showed moderate correlations with physical function. The SLS test assessing both legs (ρ = 0.50, 95% CI: 0.37 to 0.62) had a strong correlation with physical function, whereas using only the preferred leg had a moderate correlation (ρ = 0.42, 95% CI: 0.27 to 0.54). As hypothesized, nearly all performance-based measures demonstrated weak to moderate correlations with physical activity (Spearman's ρ = 0.18 to 0.32); the chair rise test without allowing use of arms did not have a statistically significant correlation with physical activity (ρ = 0.18, 95% CI: -0.01 to 0.31, p = 0.067). TUG-normal, TUG-fast, and SLS assessing both legs had moderate correlations with physical activity (ρ = 0.31 to 0.32), while other performance-based measure protocols had low correlations with physical activity (ρ = 0.15 to 0.26, Table 2 ). Table 2 Convergent validity with physical function and physical activity levels Measure Outcome N rho (95% CI) p Physical function TUG – normal Physical function 147 0.57 [0.45–0.67] < 0.001 TUG – fast Physical function 113 0.60 [0.46–0.70] < 0.001 TUG – cognitive 1-task Physical function 146 0.57 [0.45–0.67] < 0.001 TUG – cognitive 3-task Physical function 146 0.55 [0.43–0.66] < 0.001 Chair rise – without arms Physical function 143 0.39 [0.24–0.52] < 0.001 Chair rise–allow using arms Physical function 142 0.44 [0.29–0.56] < 0.001 Gait speed – 4 m Physical function 147 0.53 [0.41–0.64] < 0.001 Gait speed – 3 m Physical function 147 0.57 [0.45–0.67] < 0.001 SLS both legs (max) Physical function 141 0.50 [0.37–0.62] < 0.001 SLS – preferred leg (max) Physical function 142 0.42 [0.27–0.54] < 0.001 Physical activity levels TUG – normal Physical activity 146 0.31 [0.15–0.45] < 0.001 TUG – fast Physical activity 113 0.31 [0.14–0.47] < 0.001 TUG – cognitive 1-task Physical activity 145 0.23 [0.07–0.38] 0.005 TUG – cognitive 3-task Physical activity 145 0.18 [0.02–0.34] 0.028 Chair rise – without arms Physical activity 142 0.15 [-0.01–0.31] 0.067 Chair rise – allow using arms Physical activity 141 0.23 [0.07–0.38] 0.005 Gait speed – 4 m walk Physical activity 146 0.22 [0.06–0.37] 0.007 Gait speed – 3 m walk Physical activity 146 0.26 [0.10–0.40] 0.002 SLS both legs (max) Physical activity 140 0.32 [0.17–0.46] < 0.001 SLS – preferred leg (max) Physical activity 141 0.28 [0.12–0.43] < 0.001 SLS= Single-Leg Stance; TUG= Timed Up and Go. Known-Groups Validity We evaluated the ability of each measure to discriminate between clinical subgroups or outcomes against the known-groups validity hypotheses. Table 3 presents the mean scores, mean difference, and AUC values of each mobility measure protocol. Physical function limitation In line with our hypothesis for physical function, nearly all performance measures demonstrated acceptable ability to discriminate between participants with and without functional limitations, with AUC values ranging from 0.71 to 0.80. The only measure that did not meet the acceptable discrimination threshold was the SLS test on the preferred leg (AUC = 0.69, 95% CI: 0.60 to 0.77). The TUG-normal and TUG-fast protocols both exceeded the AUC threshold (AUC = 0.80, 95% CI: 0.72 to 0.87 and AUC = 0.79, 95% CI: 0.70 to 0.87) and so did the chair-rise protocol with and without using arms (AUC = 0.75, 95% CI: 0.66 to 0.83 vs. AUC = 0.71, 95% CI: 0.63 to 0.81). Only the SLS protocol using both legs met the AUC threshold (AUC = 0.76, 95% CI: 0.68 to 0.84 vs. AUC = 0.69, 95% CI: 0.60 to 0.77 for preferred leg). Both the 3-meter and 4-meter gait speed test protocols exceeded the AUC threshold (AUC = 0.79 for both, Table 3 ). Perceived fall risk Most measures showed acceptable discrimination between individuals with "Low" versus "High" perceived fall risk; TUG normal, and TUG cognitive dual tasks proved exceptions. The TUG-fast protocol (AUC = 0.80, 95% CI: 0.70 to 0.91) proved superior to other TUG variations for meeting the AUC threshold of 0.7 (e.g., TUG-normal: AUC 0.66; 95% CI: 0.51 to 0.80). Both the SLS protocols and the gait speed protocols showed acceptable discrimination, but neither of the chair-rise protocols showed acceptable discrimination (Table 3 ). Fall history No performance measures achieved the threshold for acceptable discrimination between fallers and non-fallers in the past year, with all AUCs below 0.7. The TUG-fast protocol had the highest point estimate for identifying fallers, with an AUC of 0.68 (95% CI: 0.56 to 0.80). No substantial differences in discriminative ability were found between the different protocols (Table 3 ). Table 3 Known-groups validity of different mobility protocol variations Measure N Mean (Ref.) Mean (case) MD AUC (95% CI) Physical Function Limitation TUG – normal (s) 147 9.60 11.52 1.92 0.80 [0.72–0.87] TUG – fast (s) 113 7.12 8.90 1.79 0.79 [0.70–0.87] TUG – cognitive 1-task (s) 146 9.39 11.73 2.35 0.79 [0.72–0.86] TUG – cognitive 3-task (s) 146 10.22 13.34 3.12 0.79 [0.72–0.87] Chair rise – without arms (s) 143 11.16 13.55 2.39 0.71 [0.63–0.80] Chair rise – allow using arms (s) 142 9.85 11.97 2.11 0.75 [0.66–0.83] Gait speed – 4 m walk (m/s) 147 0.97 0.82 -0.15 0.79 [0.72–0.87] Gait speed – 3 m walk (m/s) 147 0.89 0.75 -0.15 0.79 [0.71–0.86] SLS both legs (max, s) 141 41.32 20.66 -20.66 0.76 [0.68–0.84] SLS – preferred leg (max, s) 142 40.01 22.85 -17.16 0.69 [0.60–0.77] High perceived fall risk TUG – normal (s) 147 10.41 11.39 0.98 0.66 [0.51–0.80] TUG – fast (s) 113 7.85 9.53 1.68 0.80 [0.70–0.91] TUG – cognitive 1-task (s) 146 10.41 11.17 0.76 0.61 [0.43–0.79] TUG – cognitive 3-task (s) 146 11.51 13.65 2.14 0.69 [0.53–0.85] Chair rise – without arms (s) 143 12.32 10.83 -1.48 0.52 [0.36–0.67] Chair rise – allow using arms (s) 142 10.71 11.87 1.16 0.68 [0.56–0.80] Gait speed – 4 m walk (m/s) 147 0.91 0.79 -0.11 0.75 [0.63–0.87] Gait speed – 3 m walk (m/s) 147 0.83 0.71 -0.12 0.77 [0.69–0.86] SLS both legs (max, s) 141 33.91 6.97 -26.94 0.86 [0.76–0.97] SLS – preferred leg (max, s) 142 34.01 7.51 -26.50 0.78 [0.68–0.89] ≥ 1 fall in the past year TUG – normal (s) 147 10.30 11.10 0.80 0.57 [0.45–0.69] TUG – fast (s) 113 7.69 8.99 1.31 0.68 [0.56–0.80] TUG – cognitive 1-task (s) 146 10.28 11.09 0.81 0.60 [0.49–0.72] TUG – cognitive 3-task (s) 146 11.35 12.68 1.33 0.62 [0.50–0.73] Chair rise – without arms (s) 143 11.68 14.27 2.59 0.65 [0.54–0.76] Chair rise – allow using arms (s) 142 10.54 11.70 1.16 0.59 [0.46–0.72] Gait speed – 4 m walk (m/s) 147 0.91 0.85 -0.06 0.58 [0.46–0.71] Gait speed – 3 m walk (m/s) 147 0.84 0.78 -0.06 0.61 [0.50–0.72] SLS both legs (max, s) 141 34.34 25.15 -9.19 0.61 [0.50–0.71] SLS – preferred leg (max, s) 142 34.08 26.68 -7.40 0.59 [0.48–0.69] AUC= area under the curve; SLS= Single-Leg Stance; TUG= Timed Up and Go. Summary of validity against hypotheses Among the four TUG variations, the TUG–fast protocol met 4 out of 5 hypotheses. The TUG – normal, TUG cognitive with counting backwards by ones and threes performed similarly, each meeting 3 of the 5 hypotheses. Only the TUG-fast protocol met the hypothesis for perceived fall risk (Fig. 1 ). The chair rise test with arms protocol successfully met 3 of the 5 hypotheses. In contrast, chair rise test without arms protocol met only 2 hypotheses, failing to meet the hypotheses for physical activity, perceived fall risk and fall history. SLS using the maximum score from both legs met 4 of the 5 hypotheses. In contrast, SLS only using the preferred leg met 3 hypotheses, failing to discriminate based on physical function limitation and fall history. Gait speed over 4 meters and over 3 meters each met 4 out of the 5 validity hypotheses (Fig. 1 ). Discussion This study evaluated the convergent and known-groups validity of common protocol variations for the TUG, gait speed, chair-rise, and SLS tests in community-dwelling middle-aged and older adults. Based on the findings of the present study and our previous work on test-retest reliability,[29] we can now provide more comprehensive, evidence-based recommendations for protocol selection among different protocols for performance-based measures of mobility capacity. A discussion of our recommendations for each test in turn is provided below. Timed up and Go : Although previous systematic reviews suggested the TUG-fast offers no advantage over usual pace testing,[30, 31] our study challenges this assumption with a direct and head-to-head comparison. Although no measure met the threshold for identifying fallers, our validity results show the TUG-fast was the only TUG variant to meet the hypothesis for perceived fall risk and showed the most potential for discriminating fall history. The TUG-fast's better performance compared to the TUG-normal or cognitive variations suggests that measuring maximal physical capacity may more clearly show the decreased physiological reserve related to falls. This aligns with our reliability study, which also favored TUG-fast for younger adults.[29] Gait speed : Both the 3-meter and 4-meter gait speed tests showed identical validity, successfully discriminating based on physical function limitation and perceived fall risk. However, neither protocol was able to validly identify individuals with a history of falls. Given that there are no substantial validity differences between the two protocols, our previous finding that the 3-meter protocol has superior test-retest reliability makes it the preferred choice. Chair-rise test : The Chair rise test allowing use of the arms protocol demonstrates better validity than without arms. Although both protocols were valid for discriminating among those with physical function limitation, the "with arms allowed" version also met the validity hypothesis for physical activity, making it a more valid measure of real-world physical function and activity levels. This validity finding and our previous reliability analysis suggest the "allow using arms" protocol is the preferred choice, perhaps because the "arms-allowed" variant more closely mirrors the compensatory strategies people use in daily living.[29] Single Leg Stance : The choice of SLS protocol must take into account a trade-off between validity and reliability, particularly among older populations. The validity results indicate that the protocol using the maximum score derived from both legs met the hypothesis for physical function limitation but using the preferred leg protocol did not. However, our reliability findings indicated the preferred leg for adults aged 75 and over was needed to achieve acceptable reliability. Therefore, for most clinical and research assessments aiming to capture a complete picture of physical function, the SLS protocol assessing both legs is recommended. When consistency is the primary objective, using the more reliable preferred leg protocol may be considered. In general, lower correlations between performance-based measures and physical activity support that these tests measure locomotor capacity for mobility (what a person could do), whereas physical activity questionnaires like the PASE measure actual mobility (what a person does in daily life).[6] These are related but distinct mobility facets, and our results underscore the importance of using both types of measures to gain a complete picture of an individual's physical function. In addition, the failure of any single protocol to validly identify fall history underscores the well-documented difficulty in this area and highlights that fall risk is a multifactorial construct.[19, 32-34] Our findings suggest that a single performance measure is not sufficient. Future research should investigate whether a composite score, combining the most robust protocols identified in this study (e.g., TUG-fast) or integrating various measures such as TUG, gait speed and SLS, provide enhanced discriminative capability. Strengths and Limitations Strengths of our study include the direct comparison of common protocol variations within the same cohort. By integrating our analysis with prior reliability data,[29] we provide a uniquely comprehensive psychometric evaluation for performance-based measures with various protocols. Limitations of our study include the smaller sample size for the TUG-fast (n=113) than for other measures, leading to wider confidence intervals. Second, our gait speed protocols were administered from a static start within the timed distance using CLSA protocols. The absence of separate acceleration and deceleration zones may influence the validity of the measure.[35] Third, participants’ memory of their fall history may be imperfect, and to the extent this is true is likely to lead to underestimates of any relationship between our performance measures and actual falls. Further, sample size limitations prevented informative assessment of falls according to the degree of injury. Future longitudinal studies are needed to determine if these measures can prospectively identify individuals at risk of fall injuries and other adverse health outcomes. Conclusion This study provides a comprehensive validity assessment of commonly used performance-based measures among community-dwelling adults. Although most protocols are valid for assessing physical function and perceived fall risk, their ability to discriminate between individuals with and without a history of falls is limited. These findings, combined with our previous reliability work, offer evidence-based guidance for selecting the most appropriate measure protocols to assess physical function and mobility capacity in community-dwelling adults. Declarations Competing Interests and Funding: Marla Beauchamp holds a tier 2 Canada Research Chair in Mobility, Aging, and Chronic Disease. This research was conducted in collaboration with the Canadian Longitudinal Study on Aging (CLSA), specifically the Hamilton Site Data Collection Centre. Funding for the CLSA is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 94473 and the Canada Foundation for Innovation. The CLSA is led by Prof. Parminder Raina. Parminder Raina holds the Raymond and Margaret Labarge Chair in Research and Knowledge is the Director of the McMaster Institute for Research on Aging and the Labarge Centre for Mobility in Aging. Statement of contributor consent: All authors meet the criteria for authorship stated in the uniform requirements for manuscripts submitted to biomedical Journals. The corresponding author affirms that all individuals who contributed significantly to this work have been listed as authors. Author Contributions: MB, AK, GG, QH and PR conceived the study. MB secured funding for this study. QH conducted the data analysis and drafted the initial manuscript supervised by MB. MKB, PR, GG, and AK helped with data analysis and results of results. GG, AK, PR and LG gave critical feedback on the manuscript. All authors approved the final manuscript. No conflict of interest exists in the submission of this manuscript. Sponsor's Role: The sponsors of this research had no role in the study design, methods, subject recruitment, data collection, analysis, interpretation of data, or preparation of this paper. References Silva J, Reis LAD, Carvalho de Farias CA, Oliveira-Sousa SL, Morillas FL,Nobre TTX (2025) Assessment of functionality using the WHODAS 2.0 in community-dwelling elderly individuals: A scoping review. Medicine (Baltimore); 104(30): e43372.10.1097/md.0000000000043372 Musich S, Wang SS, Ruiz J, Hawkins K,Wicker E (2018) The impact of mobility limitations on health outcomes among older adults. Geriatric Nursing; 39(2): 162–169.https://doi.org/10.1016/j.gerinurse.2017.08.002 Greysen SR, Stijacic Cenzer I, Boscardin WJ,Covinsky KE (2017) Functional Impairment: An Unmeasured Marker of Medicare Costs for Postacute Care of Older Adults. Journal of the American Geriatrics Society; 65(9): 1996–2002.10.1111/jgs.14955 Florence CS, Bergen G, Atherly A, Burns E, Stevens J,Drake C (2018) Medical Costs of Fatal and Nonfatal Falls in Older Adults. Journal of the American Geriatrics Society; 66(4): 693–698.10.1111/jgs.15304 Moreland B, Kakara R,Henry A (2020) Trends in Nonfatal Falls and Fall-Related Injuries Among Adults Aged ≥65 Years - United States, 2012-2018. MMWR Morb Mortal Wkly Rep; 69(27): 875–881.10.15585/mmwr.mm6927a5 Beauchamp MK, Hao Q, Kuspinar A, et al. (2023) A unified framework for the measurement of mobility in older persons. Age Ageing; 52(Suppl 4): iv82–iv85.10.1093/ageing/afad125 Beauchamp M, Hao Q, Kuspinar A, et al. (2023) Measures of perceived mobility ability in community-dwelling older adults: a systematic review of psychometric properties. Age Ageing; 52(Suppl 4): iv100–iv111.10.1093/ageing/afad124 D'Amore C, Lajambe L, Bush N, et al. (2024) Mapping the extent of the literature and psychometric properties for the Physical Activity Scale for the Elderly (PASE) in community-dwelling older adults: a scoping review. BMC Geriatr; 24(1): 761.10.1186/s12877-024-05332-3 Beauchamp MK, Hao Q, Kuspinar A, et al. (2021) Reliability and Minimal Detectable Change Values for Performance-Based Measures of Physical Functioning in the Canadian Longitudinal Study on Aging. The journals of gerontology. Series A, Biological sciences and medical sciences; 76(11): 2030–2038.10.1093/gerona/glab175 Donoghue OA, Savva GM, Börsch-Supan A,Kenny RA (2019) Reliability, measurement error and minimum detectable change in mobility measures: a cohort study of community-dwelling adults aged 50 years and over in Ireland. BMJ Open; 9(11): e030475.10.1136/bmjopen-2019-030475 Ortega-Pérez de Villar L, Martínez-Olmos FJ, Junqué-Jiménez A, et al. (2018) Test-retest reliability and minimal detectable change scores for the short physical performance battery, one-legged standing test and timed up and go test in patients undergoing hemodialysis. PLoS One; 13(8): e0201035.10.1371/journal.pone.0201035 Raina P, Wolfson C, Kirkland S, et al. (2019) Cohort Profile: The Canadian Longitudinal Study on Aging (CLSA). International Journal of Epidemiology; 48(6): 1752–1753j.10.1093/ije/dyz173 %J International Journal of Epidemiology Studenski S, Perera S, Wallace D, et al. (2003) Physical Performance Measures in the Clinical Setting. 51(3): 314–322.https://doi.org/10.1046/j.1532-5415.2003.51104.x Hao Qea (2022) Measuring physical performance in later life: Reliability of different protocols for common functional tests. Submited Lee JE, Chun H, Kim YS, et al. (2020) Association between Timed Up and Go Test and Subsequent Functional Dependency. Journal of Korean medical science; 35(3): e25–e25.10.3346/jkms.2020.35.e25 Germain CM, Batsis JA, Vasquez E,McQuoid DR (2016) Muscle Strength, Physical Activity, and Functional Limitations in Older Adults with Central Obesity. Journal of aging research; 2016: 8387324–8387324.10.1155/2016/8387324 Dodds R, Kuh D, Aihie Sayer A,Cooper R (2013) Physical activity levels across adult life and grip strength in early old age: updating findings from a British birth cohort. Age Ageing; 42(6): 794–8.10.1093/ageing/aft124 Davis JW, Ross PD, Preston SD, Nevitt MC,Wasnich RD (1998) Strength, physical activity, and body mass index: relationship to performance-based measures and activities of daily living among older Japanese women in Hawaii. J Am Geriatr Soc; 46(3): 274–9.10.1111/j.1532-5415.1998.tb01037.x Blodgett JM, Hardy R, Davis D, Peeters G, Kuh D,Cooper R (2022) One-Legged Balance Performance and Fall Risk in Mid and Later Life: Longitudinal Evidence From a British Birth Cohort. Am J Prev Med; 63(6): 997–1006.10.1016/j.amepre.2022.07.002 Gafner SC, Allet L, Hilfiker R,Bastiaenen CHG (2021) Reliability and Diagnostic Accuracy of Commonly Used Performance Tests Relative to Fall History in Older Persons: A Systematic Review. Clin Interv Aging; 16: 1591–1616.10.2147/cia.S322506 Omaña H, Bezaire K, Brady K, et al. (2021) Functional Reach Test, Single-Leg Stance Test, and Tinetti Performance-Oriented Mobility Assessment for the Prediction of Falls in Older Adults: A Systematic Review. Phys Ther; 101(10).10.1093/ptj/pzab173 Blodgett JM, Ventre JP, Mills R, Hardy R,Cooper R (2022) A systematic review of one-legged balance performance and falls risk in community-dwelling adults. Ageing Res Rev; 73: 101501.10.1016/j.arr.2021.101501 Raina P, Wolfson C, Kirkland S, et al. (2019) Cohort Profile: The Canadian Longitudinal Study on Aging (CLSA). Int J Epidemiol; 48(6): 1752–1753j.10.1093/ije/dyz173 Raina PS, Wolfson C, Kirkland SA, et al. (2009) The Canadian longitudinal study on aging (CLSA). Can J Aging; 28(3): 221–9.10.1017/S0714980809990055 Beauchamp MK, Hao Q, Kuspinar A, et al. (2021) Reliability and minimal detectable change values for performance-based measures of physical functioning in the Canadian Longitudinal Study on Aging (CLSA). J Gerontol A Biol Sci Med Sci.10.1093/gerona/glab175 Jette AM, Haley SM,Kooyoomjian JT (2002) Late-life FDI manual. Boston, MA: Boston University; 73: 563 Cohen J, Statistical power analysis for the behavioral sciences . 2013: routledge. Hosmer Jr DW, Lemeshow S,Sturdivant RX, Applied logistic regression . 2013: John Wiley & Sons. Hao Q, Kuspinar A, Griffith L, et al. (2023) Measuring physical performance in later life: reliability of protocol variations for common performance-based mobility tests. Aging Clin Exp Res; 35(5): 1087–1096.10.1007/s40520-023-02384-0 Barry E, Galvin R, Keogh C, Horgan F,Fahey T (2014) Is the Timed Up and Go test a useful predictor of risk of falls in community dwelling older adults: a systematic review and meta-analysis. BMC Geriatr; 14: 14.10.1186/1471-2318-14-14 Beauchet O, Fantino B, Allali G, Muir SW, Montero-Odasso M,Annweiler C (2011) Timed Up and Go test and risk of falls in older adults: a systematic review. J Nutr Health Aging; 15(10): 933–8.10.1007/s12603-011-0062-0 Nguyen KT, Brooks D, Macedo LG, et al. (2024) Balance measures for fall risk screening in community-dwelling older adults with COPD: A longitudinal analysis. Respir Med; 230: 107681.10.1016/j.rmed.2024.107681 Beauchamp MK, Kuspinar A, Sohel N, et al. (2022) Mobility screening for fall prediction in the Canadian Longitudinal Study on Aging (CLSA): implications for fall prevention in the decade of healthy ageing. Age and Ageing; 51(5).10.1093/ageing/afac095 Saunders S, Speechley M, Griffith LE, et al. (2026) Prospective evaluation of balance and mobility tests as part of the World Falls Guidelines algorithm. Age Ageing; 55(2).10.1093/ageing/afag028 Stuck AK, Bachmann M, Füllemann P, Josephson KR,Stuck AE (2020) Effect of testing procedures on gait speed measurement: a systematic review. PloS one; 15(6): e0234200 Additional Declarations No competing interests reported. Supplementary Files AppendixTable.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 25 Apr, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviewers invited by journal 23 Apr, 2026 Editor assigned by journal 23 Apr, 2026 Submission checks completed at journal 14 Apr, 2026 First submitted to journal 13 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9407249","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633678562,"identity":"fadb1e52-7725-4a12-989b-099114c29370","order_by":0,"name":"Qiukui Hao","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Qiukui","middleName":"","lastName":"Hao","suffix":""},{"id":633678564,"identity":"23c81103-adda-4aa6-b1f2-cb6e0f7207ea","order_by":1,"name":"Ayse Kuspinar","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Ayse","middleName":"","lastName":"Kuspinar","suffix":""},{"id":633678566,"identity":"33ba9dcb-a03a-4d91-8cca-3c9f16cacf3d","order_by":2,"name":"Gordon Guyatt","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Gordon","middleName":"","lastName":"Guyatt","suffix":""},{"id":633678568,"identity":"9164db6c-7138-4f7b-ac24-efb02100840c","order_by":3,"name":"Parminder Raina","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Parminder","middleName":"","lastName":"Raina","suffix":""},{"id":633678571,"identity":"15346279-099a-423e-8a5c-82d218d30063","order_by":4,"name":"Lauren Griffith","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"","lastName":"Griffith","suffix":""},{"id":633678574,"identity":"bc70fa4e-3084-4c2d-9342-b83854ad0c69","order_by":5,"name":"Marla Beauchamp","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYBACAwglIUeyFgtjCJ1AvJaKxAaitZizNz+T+Jkjkb62/XTix58/bPIZ2A8/wKvFsueYmWTvNoncbWdyN0vzJKRZNvCkGeB32I0EM2lGkJYbvBukGRIOGzBIMBDQcv/5N5CWdLMbvJt//kj4D9TC/oGALTxgWxKAWrZJ8CQcAGrhwW+LZU9OsSXQL4ZAv2yz5klLNmDjySnAq8Wc/fjGGz+31cmbHT+7+eYPGzsDfvbjG/BqwQRsJKofBaNgFIyCUYAFAAB2o0JvgsoZSQAAAABJRU5ErkJggg==","orcid":"","institution":"McMaster University","correspondingAuthor":true,"prefix":"","firstName":"Marla","middleName":"","lastName":"Beauchamp","suffix":""}],"badges":[],"createdAt":"2026-04-13 17:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9407249/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9407249/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108537310,"identity":"1ccda154-9e17-43de-b965-ffc778323592","added_by":"auto","created_at":"2026-05-05 17:32:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6752,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of convergent and known-groups validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: SLS, Single-Leg Stance; TUG, Timed Up and Go.\u003c/p\u003e\n\u003cp\u003eNotes: (a) TUG-fast is the only TUG variation that validly identifies perceived fall risk; (b) allowing arm use during the chair rise better reflects self-reported physical activity than restricting arm use; and (c) assessing both legs provides better discrimination of functional limitation compared to using the preferred leg alone. Blue cells with a plus sign (+) indicate the predefined validity hypothesis was met; gray cells with a minus sign (-) indicate the hypothesis was not met. Bolded protocols highlight the optimal variations recommended for clinical and research use.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9407249/v1/9b0d491c420a2ab0f4d89a88.png"},{"id":108537311,"identity":"3ee30a41-775b-49b0-bb1d-727a859d9a05","added_by":"auto","created_at":"2026-05-05 17:32:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":459772,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9407249/v1/84dfc57a-8db5-4e0f-86f8-bc419dba267a.pdf"},{"id":108537309,"identity":"c0c9fade-6ad0-4460-8157-790891776d06","added_by":"auto","created_at":"2026-05-05 17:32:46","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16716,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-9407249/v1/9653e6e5bda684fb3677081f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Convergent and known-groups validity of common protocols for mobility measurement among community-dwelling adults","fulltext":[{"header":"Key points","content":"\u003cul\u003e\n \u003cli\u003eMost variations of common performance-based mobility tests demonstrate moderate to strong validity for assessing physical function and perceived fall risk in community-dwelling older adults.\u003c/li\u003e\n \u003cli\u003eNo single mobility test protocol met the acceptable threshold for discriminating individuals with a recent history of falls.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe Timed Up and Go performed at a fast pace (TUG-fast) emerged as the most robust protocol.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhy does this paper matter?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinicians and researchers frequently use mobility assessments such as the TUG and gait speed, but wide variations in administration protocols complicate the interpretation of patients\u0026rsquo; results. This study provides evidence and recommendations to help healthcare professionals select the most robust test protocols.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eMobility is fundamental to functional ability and plays a critical role in healthy aging.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] As individuals age, mobility declines can lead to adverse outcomes, including functional limitations, increased risk of falls, and higher healthcare utilization.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Functional limitations and disabilities significantly impact the quality of life of older adults and increase costs for the health care system.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Falls are the leading cause of injury-related morbidity and mortality among older adults and contribute significantly to health care costs.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Identifying individuals with limited mobility or those at risk of mobility impairment could help delay functional decline, prevent falls, and promote better overall health and healthy aging.\u003c/p\u003e \u003cp\u003eComprehensive mobility assessment frameworks consider three distinct facets: perceived mobility, actual mobility, and locomotor capacity for mobility.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Researchers commonly assess perceived and actual mobility using self-report instruments such as the Late-Life Function and Disability Instrument -Function Component (LLFDI-FC) and the Physical Activity Scale for the Elderly (PASE), with a higher score indicating better function or a higher physical activity level.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] These tools have demonstrated acceptable reliability and validity in evaluating physical function and activity levels in older adults.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] In contrast, performance-based tests conducted in controlled settings are widely used to assess locomotor capacity for mobility. These tests offer a more objective measure of mobility compared to self-reported assessments.\u003c/p\u003e \u003cp\u003eInvestigators and clinicians commonly use a range of performance-based measures, including the Timed Up and Go (TUG) test, gait speed, chair-rise test, and single-leg stance (SLS) test in both research and clinical settings. These tests have demonstrated moderate to excellent reliability for community-dwelling middle-aged and older adults. [\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] However, variations in administration protocols are common. For instance, TUG may be performed at a normal or fast walking pace; gait speed can be measured over different course lengths; the chair-rise test may allow or restrict arm use; and the single-leg stance can be assessed on either leg or the participant\u0026rsquo;s preferred leg.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] These protocol differences can affect the reliability of specific tests across different age groups of participants.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Such variations may also influence the validity of these measures.\u003c/p\u003e \u003cp\u003eAlthough individual studies have demonstrated associations between performance-based measures and outcomes such as physical activity, functional limitations, and fall risk, most have examined these relationships in isolation.[\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] For instance, the TUG predicts future functional dependency,[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and single-leg stance has been linked to functional limitations and fall risk.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Systematic reviews have found only low-quality evidence to support the use of these measures in identifying individuals at high risk of falling.[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Moreover, few studies have directly compared the construct validity of these measures or evaluated how protocol variations affect their ability to identify functional limitations and fall risk.\u003c/p\u003e \u003cp\u003eTo address these gaps, this study aims to examine the construct validity of four commonly used performance-based measures and their protocol variations for locomotor capacity for mobility: TUG, gait speed, chair-rise, and SLS, using data from a sub-study of the Canadian Longitudinal Study on Aging (CLSA). CLSA is a large-scale, national research initiative that follows approximately 50,000 Canadians aged 45 years and older, exploring the biological, medical, psychological, social, and economic dimensions of aging.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] The present study provides evidence regarding convergent construct validity using related measures of physical activity and functional limitations, as well as known-groups validity in relation to fall risk and functional limitations. By directly comparing these measures and their protocol variations, we provide evidence to guide the selection of appropriate performance-based measure protocols for assessing mobility capacity in community-dwelling adults aged 50 years or older.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eUsing data from a previously published sub-study of the CLSA focused on reliability, we examined the validity of TUG, chair-rise, gait speed, and SLS tests and their common protocol variations for physical limitations and physical activity levels [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Briefly, the study included consecutive participants who participated in a baseline assessment session during their routine CLSA visit (n\u0026thinsp;=\u0026thinsp;147). According to the CLSA protocol (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.clsa-elcv.ca/researchers/physical-assessments\u003c/span\u003e\u003cspan address=\"https://www.clsa-elcv.ca/researchers/physical-assessments\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and descriptions in the study data collection sheet, CLSA research staff or postgraduate students in Rehabilitation Science at McMaster University administered these measures. The research staff also completed physical function and physical activity questionnaires. The Hamilton Integrated Research Ethics Board approved the study (2018-5280-GRA).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePerformance-based measures and their common protocol variations\u003c/h2\u003e \u003cp\u003eFour commonly used physical performance-based measures were administered in accordance with the CLSA operating procedures, including TUG, gait speed, chair rise, and SLS. For the sub-study, we incorporated common administration protocol variations to these measures.\u003c/p\u003e \u003cp\u003eThe TUG test evaluates functional mobility and balance by asking participants to rise from a chair 46 cm in height, walk three meters, turn around, return to the chair, and sit down. Participants were allowed to use their usual assistive devices or gait aids. The test was conducted in three variations: TUG-normal, where participants were instructed to \u0026ldquo;walk at your comfortable or normal pace\u0026rdquo;; TUG-fast, with the instruction to \u0026ldquo;walk as quickly and as safely as possible\u0026rdquo;; and TUG-cognitive, which involved walking while counting backward by ones or threes at a comfortable and safe pace. Of the 147 participants, all completed the TUG-normal and TUG-cognitive protocols. A subset of 113 individuals performed the normal-fast protocol.\u003c/p\u003e \u003cp\u003eThe chair rise test, also known as the Five-Times-Sit-to-Stand test, measures lower limb strength and balance. Participants were instructed to stand up and sit down five times as quickly as possible after the evaluator said \u0026ldquo;Go,\u0026rdquo; with timing starting at that cue and ending when the participant was fully standing for the fifth time. Two protocol variations were used: one without arm use, where participants crossed their arms over their chest, and one with arm use, where participants were told, \u0026ldquo;you may use your arms to rise from the chair.\u0026rdquo; For the chair rise test, 144 participants completed the protocol without arm use, and 143 completed the protocol that allowing the arm use.\u003c/p\u003e \u003cp\u003eGait speed was assessed by measuring the time it took participants to walk either 3 or 4 metres at their usual pace from a static start. The standardized instruction was: \u0026ldquo;After I say, \u0026lsquo;ready, set, go,\u0026rsquo; please walk at your usual walking pace until I say to stop.\u0026rdquo; Both distances were used to accommodate different testing environments while maintaining consistency in administration. All participants competed both protocols for gait speed test.\u003c/p\u003e \u003cp\u003eThe SLS test evaluates static balance by timing how long participants can stand on one leg, up to a maximum of 60 seconds. Timing began when the foot left the ground and ended when the foot touched the ground again or balance was lost. Two protocol variations were included: one recording time for both the right and left legs, and another using the participant\u0026rsquo;s preferred leg for two trials. Both the mean and maximum durations were recorded to assess balance performance. For the chair rise test, 142 participants completed the preferred-leg protocol and 141 completed the both-legs protocol.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison measures\u003c/h3\u003e\n\u003cp\u003eWe used the self-reported PASE to quantify physical activity levels over the previous seven days. The PASE scores are derived by weighting leisure, household, and occupational tasks, starting with 0 and no theoretical maximum, and with higher scores representing greater physical activity. Previous studies indicated that the PASE has acceptable reliability and validity for measuring physical activity.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] To measure physical function limitations, we used the LLFDI-FC, which provides a scaled score from 0 to 100, with higher scores reflecting better physical function.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] The LLFDI-FC showed good test-retest reliability (ICC\u0026thinsp;=\u0026thinsp;0.77 to 0.98) and sensitivity to change in older adults.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] In the absence of a standardized cutoff for defining functional limitation using the LLFDI-FC, we used our cohort's median score of 70 as the threshold. This approach considers that the reported mean scores for adults with slight and no functional limitations are 65.6 and 75.6, respectively.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWe defined a fall as \"when you find yourself suddenly on the ground, without intending to get there, after you were in either a lying, sitting, or standing position.\" We asked patients, \"How many times in the past year did you fall?\" and recorded their response. Participants were categorized as non-fallers (without falls) or fallers (with at least one fall). Participants' perceptions of their own fall risk were collected by asking, \"In general, how would you rate your risk of falling?\" with the following response options: extremely low, low, medium, high, and extremely high. The participants were categorized into either a low-risk group (who responded \u0026ldquo;extremely low\u0026rdquo;, \u0026ldquo;low\u0026rdquo; or \"medium\") or a high-risk group (who responded \"high\" and \u0026ldquo;extremely high\u0026rdquo;).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe performed all statistical analyses using R version 4.2 in RStudio, setting the significance level at α\u0026thinsp;=\u0026thinsp;0.05. To assess the distribution of continuous variables, we applied the Shapiro-Wilk test. For performance-based measures, most data were non-normally distributed, so we reported medians and interquartile ranges. To standardize the interpretation across all variables, time-based performance measures (e.g., TUG, chair-rise time, SLS) were converted to their reciprocals (1/s). To avoid the high risk of type II error associated with a small sample, we did not formally compare the correlation strengths or discriminative performances of related protocols within the same test (e.g., TUG-normal vs. TUG-fast).\u003c/p\u003e \u003cp\u003eTo evaluate convergent validity, we assessed the association between each performance-based measure and the total scores of the LLFDI-FC and PASE. Given most performance-based measure data were non-normally distributed, we calculated Spearman's correlation coefficients to quantify these associations. We assessed known-groups validity by testing whether each performance-based measure could differentiate participants based on physical function limitation (no or mild limitation versus moderate or severe limitation), fall history (non-fallers versus fallers), and perceived fall risk (low risk versus high risk). To quantify the discriminative ability of each measure, we used the Area Under the Receiver Operating Characteristic (ROC) curve (AUC).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eValidity hypotheses\u003c/h3\u003e\n\u003cp\u003eWe hypothesized that all performance-based measures would moderately to strongly correlate with physical function (LLFDI-FC) and weakly to moderately with physical activity (PASE). The strength of the correlations was interpreted as strong (ρ\u0026thinsp;\u0026ge;\u0026thinsp;0.50), moderate (ρ\u0026thinsp;=\u0026thinsp;0.30\u0026ndash;0.49), or weak (ρ\u0026thinsp;=\u0026thinsp;0.10\u0026ndash;0.29).[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] We hypothesized that the performance-based measures would adequately discriminate between participants based on physical function limitation, fall history, and perceived fall risk. We set a threshold of AUC of 0.70 for acceptable discrimination.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eA total of 157 community-dwelling adults 50 years and older (mean age 69.4 years) of whom 115 proved \"Non-fallers\" and 42 \"Fallers\" (n\u0026thinsp;=\u0026thinsp;42, 27%) were included in the analysis. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic and clinical characteristics of both groups. Compared to non-fallers in the past year, participants who experienced at least one fall had a higher number of medications, lower median scores for physical function as assessed by LLFDI-FC, a greater likelihood of using a gait aid, and having a higher perceived risk of falling.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAge (years), mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-fallers\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;115\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFallers\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;42\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.2 (10.3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.1 (9.3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge groups, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (28.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (34.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (37.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (43.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (56.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeight (cm), mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169.5 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.9 (10.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight (Kg), mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.4 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI(kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e), mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.8 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.9 (6.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of medications, mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePASE, median [IQR]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136 [99, 174]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140[118, 181]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLLFDI-FC, median [IQR]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 [66, 81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 [56, 72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUse of Gait Aid, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (18.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (95.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (81.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived fall risk, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111 (96.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (84.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh Risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (15.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFunction limitations, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo/Mild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (28.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate/Severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (71.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving alone, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (28.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (88.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (71.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eIQR= Interquartile Range; SD= Standard Deviation; PASE\u0026thinsp;=\u0026thinsp;Physical Activity Scale for the Elderly; LLFDI-FC\u0026thinsp;=\u0026thinsp;Late-Life Function and Disability Instrument-Function Component\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe present the descriptive statistics for the performance-based measures and their variations in the Appendix Table. In the TUG test, participants showed the fastest median time when instructed to move quickly, at 7.53 seconds (the median time of normal pace: 10.25 seconds). For the chair rise tests, participants were slower when not permitted to use their arms compared to when the use of arms was allowed (12.02 vs. 10.50 seconds). Gait speed was slightly faster over a shorter distance (3 meters: 0.91 m/s vs. 4 meters: 0.84 m/s). For the SLS test, the median time (max) from both legs was longer than using only the preferred leg (28.28 vs. 27.45 seconds).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eConvergent Validity\u003c/h3\u003e\n\u003cp\u003eAll mobility protocols showed moderate to strong correlations with physical function as assessed by the LLFDI-FC (ρ\u0026thinsp;=\u0026thinsp;0.39 to 0.57; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The TUG-fast (ρ\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.46 to 0.70), TUG-normal protocol (ρ\u0026thinsp;=\u0026thinsp;0.57 95% CI: 0.45 to 0.67), 4-meter (ρ\u0026thinsp;=\u0026thinsp;0.53, 95% CI: 0.46 to 0.70) and 3-meter gait speed tests (ρ\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.46 to 0.70) all showed strong correlations with physical function. The chair-rise protocol allowing arm use (ρ\u0026thinsp;=\u0026thinsp;0.44, 95% CI: 0.29 to 0.56) and protocol without arm use (ρ\u0026thinsp;=\u0026thinsp;0.39, 95% CI: 0.24 to 0.52) showed moderate correlations with physical function. The SLS test assessing both legs (ρ\u0026thinsp;=\u0026thinsp;0.50, 95% CI: 0.37 to 0.62) had a strong correlation with physical function, whereas using only the preferred leg had a moderate correlation (ρ\u0026thinsp;=\u0026thinsp;0.42, 95% CI: 0.27 to 0.54).\u003c/p\u003e \u003cp\u003eAs hypothesized, nearly all performance-based measures demonstrated weak to moderate correlations with physical activity (Spearman's ρ\u0026thinsp;=\u0026thinsp;0.18 to 0.32); the chair rise test without allowing use of arms did not have a statistically significant correlation with physical activity (ρ\u0026thinsp;=\u0026thinsp;0.18, 95% CI: -0.01 to 0.31, p\u0026thinsp;=\u0026thinsp;0.067). TUG-normal, TUG-fast, and SLS assessing both legs had moderate correlations with physical activity (ρ\u0026thinsp;=\u0026thinsp;0.31 to 0.32), while other performance-based measure protocols had low correlations with physical activity (ρ\u0026thinsp;=\u0026thinsp;0.15 to 0.26, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConvergent validity with physical function and physical activity levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003erho (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57 [0.45\u0026ndash;0.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; fast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60 [0.46\u0026ndash;0.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 1-task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57 [0.45\u0026ndash;0.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 3-task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55 [0.43\u0026ndash;0.66]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; without arms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39 [0.24\u0026ndash;0.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise\u0026ndash;allow using arms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44 [0.29\u0026ndash;0.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 4 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53 [0.41\u0026ndash;0.64]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 3 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57 [0.45\u0026ndash;0.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS both legs (max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.50 [0.37\u0026ndash;0.62]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS \u0026ndash; preferred leg (max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42 [0.27\u0026ndash;0.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity levels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31 [0.15\u0026ndash;0.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; fast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31 [0.14\u0026ndash;0.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 1-task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23 [0.07\u0026ndash;0.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 3-task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18 [0.02\u0026ndash;0.34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; without arms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15 [-0.01\u0026ndash;0.31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; allow using arms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23 [0.07\u0026ndash;0.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 4 m walk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22 [0.06\u0026ndash;0.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 3 m walk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26 [0.10\u0026ndash;0.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS both legs (max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32 [0.17\u0026ndash;0.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS \u0026ndash; preferred leg (max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28 [0.12\u0026ndash;0.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSLS= Single-Leg Stance; TUG= Timed Up and Go.\u003c/p\u003e\n\u003ch3\u003eKnown-Groups Validity\u003c/h3\u003e\n\u003cp\u003eWe evaluated the ability of each measure to discriminate between clinical subgroups or outcomes against the known-groups validity hypotheses. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the mean scores, mean difference, and AUC values of each mobility measure protocol.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePhysical function limitation\u003c/h2\u003e \u003cp\u003eIn line with our hypothesis for physical function, nearly all performance measures demonstrated acceptable ability to discriminate between participants with and without functional limitations, with AUC values ranging from 0.71 to 0.80. The only measure that did not meet the acceptable discrimination threshold was the SLS test on the preferred leg (AUC\u0026thinsp;=\u0026thinsp;0.69, 95% CI: 0.60 to 0.77). The TUG-normal and TUG-fast protocols both exceeded the AUC threshold (AUC\u0026thinsp;=\u0026thinsp;0.80, 95% CI: 0.72 to 0.87 and AUC\u0026thinsp;=\u0026thinsp;0.79, 95% CI: 0.70 to 0.87) and so did the chair-rise protocol with and without using arms (AUC\u0026thinsp;=\u0026thinsp;0.75, 95% CI: 0.66 to 0.83 vs. AUC\u0026thinsp;=\u0026thinsp;0.71, 95% CI: 0.63 to 0.81). Only the SLS protocol using both legs met the AUC threshold (AUC\u0026thinsp;=\u0026thinsp;0.76, 95% CI: 0.68 to 0.84 vs. AUC\u0026thinsp;=\u0026thinsp;0.69, 95% CI: 0.60 to 0.77 for preferred leg). Both the 3-meter and 4-meter gait speed test protocols exceeded the AUC threshold (AUC\u0026thinsp;=\u0026thinsp;0.79 for both, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePerceived fall risk\u003c/h2\u003e \u003cp\u003eMost measures showed acceptable discrimination between individuals with \"Low\" versus \"High\" perceived fall risk; TUG normal, and TUG cognitive dual tasks proved exceptions. The TUG-fast protocol (AUC\u0026thinsp;=\u0026thinsp;0.80, 95% CI: 0.70 to 0.91) proved superior to other TUG variations for meeting the AUC threshold of 0.7 (e.g., TUG-normal: AUC 0.66; 95% CI: 0.51 to 0.80). Both the SLS protocols and the gait speed protocols showed acceptable discrimination, but neither of the chair-rise protocols showed acceptable discrimination (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFall history\u003c/h2\u003e \u003cp\u003eNo performance measures achieved the threshold for acceptable discrimination between fallers and non-fallers in the past year, with all AUCs below 0.7. The TUG-fast protocol had the highest point estimate for identifying fallers, with an AUC of 0.68 (95% CI: 0.56 to 0.80). No substantial differences in discriminative ability were found between the different protocols (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKnown-groups validity of different mobility protocol variations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (Ref.)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (case)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ePhysical Function Limitation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; normal (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e147\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9.60\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11.52\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.92\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.80 [0.72\u0026ndash;0.87]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; fast (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.70\u0026ndash;0.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 1-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.72\u0026ndash;0.86]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 3-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.72\u0026ndash;0.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; without arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71 [0.63\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; allow using arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75 [0.66\u0026ndash;0.83]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 4 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.72\u0026ndash;0.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 3 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.71\u0026ndash;0.86]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS both legs (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-20.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76 [0.68\u0026ndash;0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS \u0026ndash; preferred leg (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-17.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69 [0.60\u0026ndash;0.77]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh perceived fall risk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; normal (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66 [0.51\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; fast (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80 [0.70\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 1-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61 [0.43\u0026ndash;0.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 3-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69 [0.53\u0026ndash;0.85]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; without arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52 [0.36\u0026ndash;0.67]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; allow using arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68 [0.56\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 4 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75 [0.63\u0026ndash;0.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 3 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77 [0.69\u0026ndash;0.86]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS both legs (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e141\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e33.91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-26.94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.86 [0.76\u0026ndash;0.97]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS \u0026ndash; preferred leg (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-26.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 [0.68\u0026ndash;0.89]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;1 fall in the past year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; normal (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57 [0.45\u0026ndash;0.69]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; fast (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e113\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.68 [0.56\u0026ndash;0.80]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 1-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.60 [0.49\u0026ndash;0.72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUG \u0026ndash; cognitive 3-task (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62 [0.50\u0026ndash;0.73]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; without arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65 [0.54\u0026ndash;0.76]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair rise \u0026ndash; allow using arms (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59 [0.46\u0026ndash;0.72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 4 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.58 [0.46\u0026ndash;0.71]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait speed \u0026ndash; 3 m walk (m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61 [0.50\u0026ndash;0.72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS both legs (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-9.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61 [0.50\u0026ndash;0.71]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLS \u0026ndash; preferred leg (max, s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59 [0.48\u0026ndash;0.69]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAUC= area under the curve; SLS= Single-Leg Stance; TUG= Timed Up and Go.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSummary of validity against hypotheses\u003c/h2\u003e \u003cp\u003eAmong the four TUG variations, the TUG\u0026ndash;fast protocol met 4 out of 5 hypotheses. The TUG \u0026ndash; normal, TUG cognitive with counting backwards by ones and threes performed similarly, each meeting 3 of the 5 hypotheses. Only the TUG-fast protocol met the hypothesis for perceived fall risk (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe chair rise test with arms protocol successfully met 3 of the 5 hypotheses. In contrast, chair rise test without arms protocol met only 2 hypotheses, failing to meet the hypotheses for physical activity, perceived fall risk and fall history. SLS using the maximum score from both legs met 4 of the 5 hypotheses. In contrast, SLS only using the preferred leg met 3 hypotheses, failing to discriminate based on physical function limitation and fall history. Gait speed over 4 meters and over 3 meters each met 4 out of the 5 validity hypotheses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion ","content":"\u003cp\u003eThis study evaluated the convergent and known-groups validity of common protocol variations for the TUG, gait speed, chair-rise, and SLS tests in community-dwelling middle-aged and older adults. Based on the findings of the present study and our previous work on test-retest reliability,[29] we can now provide more comprehensive, evidence-based recommendations for protocol selection among different protocols for performance-based measures of mobility capacity. A discussion of our recommendations for each test in turn is provided below.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTimed up and Go\u003c/strong\u003e: Although previous systematic reviews suggested the TUG-fast offers no advantage over usual pace testing,[30, 31] our study challenges this assumption with a direct and head-to-head comparison. Although no measure met the threshold for identifying fallers, our validity results show the TUG-fast was the only TUG variant to meet the hypothesis for perceived fall risk and showed the most potential for discriminating fall history. \u0026nbsp;The TUG-fast's better performance compared to the TUG-normal or cognitive variations suggests that measuring maximal physical capacity may more clearly show the decreased physiological reserve related to falls. This aligns with our reliability study, which also favored TUG-fast for younger adults.[29]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGait speed\u003c/strong\u003e: Both the 3-meter and 4-meter gait speed tests showed identical validity, successfully discriminating based on physical function limitation and perceived fall risk. However, neither protocol was able to validly identify individuals with a history of falls. Given that there are no substantial validity differences between the two protocols, our previous finding that the 3-meter protocol has superior test-retest reliability makes it the preferred choice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChair-rise test\u003c/strong\u003e: The Chair rise test allowing use of the arms protocol demonstrates better validity than without arms. Although both protocols were valid for discriminating among those with physical function limitation, the \"with arms allowed\" version also met the validity hypothesis for physical activity, making it a more valid measure of real-world physical function and activity levels. This validity finding and our previous reliability analysis suggest the \"allow using arms\" protocol is the preferred choice, perhaps because \u0026nbsp;the \"arms-allowed\" variant more closely mirrors the compensatory strategies people use in daily living.[29]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle Leg Stance\u003c/strong\u003e: The choice of SLS protocol must take into account a trade-off between validity and reliability, particularly among older populations. The validity results indicate that the protocol using the maximum score derived from both legs met the hypothesis for physical function limitation but using the preferred leg protocol did not. However, our reliability findings indicated the preferred leg for adults aged 75 and over was needed to achieve acceptable reliability. Therefore, for most clinical and research assessments aiming to capture a complete picture of physical function, the SLS protocol assessing both legs is recommended. When consistency is the primary objective, using the more reliable preferred leg protocol may be considered.\u003c/p\u003e\n\u003cp\u003eIn general, lower correlations between performance-based measures and physical activity support that these tests measure locomotor capacity for mobility (what a person could do), whereas physical activity questionnaires like the PASE measure actual mobility (what a person does in daily life).[6] These are related but distinct mobility facets, and our results underscore the importance of using both types of measures to gain a complete picture of an individual's physical function. In addition, the failure of any single protocol to validly identify fall history underscores the well-documented difficulty in this area and highlights that fall risk is a multifactorial construct.[19, 32-34] Our findings suggest that a single performance measure is not sufficient. Future research should investigate whether a composite score, combining the most robust protocols identified in this study (e.g., TUG-fast) or integrating various measures such as TUG, gait speed and SLS, provide enhanced discriminative capability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStrengths and Limitations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStrengths of our study include the direct comparison of common protocol variations within the same cohort. By integrating our analysis with prior reliability data,[29] \u0026nbsp; we provide a uniquely comprehensive psychometric evaluation for performance-based measures with various protocols. Limitations of our study include the smaller sample size for the TUG-fast (n=113) than for other measures, leading to wider confidence intervals. Second, our gait speed protocols were administered from a static start within the timed distance using CLSA protocols. The absence of separate acceleration and deceleration zones may influence the validity of the measure.[35] Third, participants’ memory of their fall history may be imperfect, and to the extent this is true is likely to lead to underestimates of any relationship between our performance measures and actual falls. Further, sample size limitations prevented informative assessment of falls according to the degree of injury. Future longitudinal studies are needed to determine if these measures can prospectively identify individuals at risk of fall injuries and other adverse health outcomes.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides a comprehensive validity assessment of commonly used performance-based measures among community-dwelling adults. Although most protocols are valid for assessing physical function and perceived fall risk, their ability to discriminate between individuals with and without a history of falls is limited. These findings, combined with our previous reliability work, offer evidence-based guidance for selecting the most appropriate measure protocols to assess physical function and mobility capacity in community-dwelling adults.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests and Funding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMarla Beauchamp holds a tier 2 Canada Research Chair in Mobility, Aging, and Chronic Disease. This research was conducted in collaboration with the Canadian Longitudinal Study on Aging (CLSA), specifically the Hamilton Site Data Collection Centre. Funding for the CLSA is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 94473 and the Canada Foundation for Innovation. The CLSA is led by Prof. Parminder Raina. Parminder Raina holds the Raymond and Margaret Labarge Chair in Research and Knowledge is the Director of the McMaster Institute for Research on Aging and the Labarge Centre for Mobility in Aging.\u003c/p\u003e\n\u003cp\u003eStatement of contributor consent: All authors meet the criteria for authorship stated in the uniform requirements for manuscripts submitted to biomedical Journals. The corresponding author affirms that all individuals who contributed significantly to this work have been listed as authors.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions: MB, AK, GG, QH and PR conceived the study. MB secured funding for this study. QH conducted the data analysis and drafted the initial manuscript supervised by MB. MKB, PR, GG, and AK helped with data analysis and results of results. GG, AK, PR and LG gave critical feedback on the manuscript. All authors approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo conflict of interest exists in the submission of this manuscript.\u003c/p\u003e\n\u003cp\u003eSponsor\u0026apos;s Role: The sponsors of this research had no role in the study design, methods, subject recruitment, data collection, analysis, interpretation of data, or preparation of this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSilva J, Reis LAD, Carvalho de Farias CA, Oliveira-Sousa SL, Morillas FL,Nobre TTX (2025) Assessment of functionality using the WHODAS 2.0 in community-dwelling elderly individuals: A scoping review. Medicine (Baltimore); 104(30): e43372.10.1097/md.0000000000043372\u003c/li\u003e\n \u003cli\u003eMusich S, Wang SS, Ruiz J, Hawkins K,Wicker E (2018) The impact of mobility limitations on health outcomes among older adults. Geriatric Nursing; 39(2): 162\u0026ndash;169.https://doi.org/10.1016/j.gerinurse.2017.08.002\u003c/li\u003e\n \u003cli\u003eGreysen SR, Stijacic Cenzer I, Boscardin WJ,Covinsky KE (2017) Functional Impairment: An Unmeasured Marker of Medicare Costs for Postacute Care of Older Adults. Journal of the American Geriatrics Society; 65(9): 1996\u0026ndash;2002.10.1111/jgs.14955\u003c/li\u003e\n \u003cli\u003eFlorence CS, Bergen G, Atherly A, Burns E, Stevens J,Drake C (2018) Medical Costs of Fatal and Nonfatal Falls in Older Adults. Journal of the American Geriatrics Society; 66(4): 693\u0026ndash;698.10.1111/jgs.15304\u003c/li\u003e\n \u003cli\u003eMoreland B, Kakara R,Henry A (2020) Trends in Nonfatal Falls and Fall-Related Injuries Among Adults Aged \u0026ge;65 Years - United States, 2012-2018. MMWR Morb Mortal Wkly Rep; 69(27): 875\u0026ndash;881.10.15585/mmwr.mm6927a5\u003c/li\u003e\n \u003cli\u003eBeauchamp MK, Hao Q, Kuspinar A, et al. (2023) A unified framework for the measurement of mobility in older persons. Age Ageing; 52(Suppl 4): iv82\u0026ndash;iv85.10.1093/ageing/afad125\u003c/li\u003e\n \u003cli\u003eBeauchamp M, Hao Q, Kuspinar A, et al. (2023) Measures of perceived mobility ability in community-dwelling older adults: a systematic review of psychometric properties. Age Ageing; 52(Suppl 4): iv100\u0026ndash;iv111.10.1093/ageing/afad124\u003c/li\u003e\n \u003cli\u003eD\u0026apos;Amore C, Lajambe L, Bush N, et al. (2024) Mapping the extent of the literature and psychometric properties for the Physical Activity Scale for the Elderly (PASE) in community-dwelling older adults: a scoping review. BMC Geriatr; 24(1): 761.10.1186/s12877-024-05332-3\u003c/li\u003e\n \u003cli\u003eBeauchamp MK, Hao Q, Kuspinar A, et al. (2021) Reliability and Minimal Detectable Change Values for Performance-Based Measures of Physical Functioning in the Canadian Longitudinal Study on Aging. The journals of gerontology. Series A, Biological sciences and medical sciences; 76(11): 2030\u0026ndash;2038.10.1093/gerona/glab175\u003c/li\u003e\n \u003cli\u003eDonoghue OA, Savva GM, B\u0026ouml;rsch-Supan A,Kenny RA (2019) Reliability, measurement error and minimum detectable change in mobility measures: a cohort study of community-dwelling adults aged 50 years and over in Ireland. BMJ Open; 9(11): e030475.10.1136/bmjopen-2019-030475\u003c/li\u003e\n \u003cli\u003eOrtega-P\u0026eacute;rez de Villar L, Mart\u0026iacute;nez-Olmos FJ, Junqu\u0026eacute;-Jim\u0026eacute;nez A, et al. (2018) Test-retest reliability and minimal detectable change scores for the short physical performance battery, one-legged standing test and timed up and go test in patients undergoing hemodialysis. PLoS One; 13(8): e0201035.10.1371/journal.pone.0201035\u003c/li\u003e\n \u003cli\u003eRaina P, Wolfson C, Kirkland S, et al. (2019) Cohort Profile: The Canadian Longitudinal Study on Aging (CLSA). International Journal of Epidemiology; 48(6): 1752\u0026ndash;1753j.10.1093/ije/dyz173 %J International Journal of Epidemiology\u003c/li\u003e\n \u003cli\u003eStudenski S, Perera S, Wallace D, et al. (2003) Physical Performance Measures in the Clinical Setting. 51(3): 314\u0026ndash;322.https://doi.org/10.1046/j.1532-5415.2003.51104.x\u003c/li\u003e\n \u003cli\u003eHao Qea (2022) Measuring physical performance in later life: Reliability of different protocols for common functional tests. Submited\u003c/li\u003e\n \u003cli\u003eLee JE, Chun H, Kim YS, et al. (2020) Association between Timed Up and Go Test and Subsequent Functional Dependency. Journal of Korean medical science; 35(3): e25\u0026ndash;e25.10.3346/jkms.2020.35.e25\u003c/li\u003e\n \u003cli\u003eGermain CM, Batsis JA, Vasquez E,McQuoid DR (2016) Muscle Strength, Physical Activity, and Functional Limitations in Older Adults with Central Obesity. Journal of aging research; 2016: 8387324\u0026ndash;8387324.10.1155/2016/8387324\u003c/li\u003e\n \u003cli\u003eDodds R, Kuh D, Aihie Sayer A,Cooper R (2013) Physical activity levels across adult life and grip strength in early old age: updating findings from a British birth cohort. Age Ageing; 42(6): 794\u0026ndash;8.10.1093/ageing/aft124\u003c/li\u003e\n \u003cli\u003eDavis JW, Ross PD, Preston SD, Nevitt MC,Wasnich RD (1998) Strength, physical activity, and body mass index: relationship to performance-based measures and activities of daily living among older Japanese women in Hawaii. J Am Geriatr Soc; 46(3): 274\u0026ndash;9.10.1111/j.1532-5415.1998.tb01037.x\u003c/li\u003e\n \u003cli\u003eBlodgett JM, Hardy R, Davis D, Peeters G, Kuh D,Cooper R (2022) One-Legged Balance Performance and Fall Risk in Mid and Later Life: Longitudinal Evidence From a British Birth Cohort. Am J Prev Med; 63(6): 997\u0026ndash;1006.10.1016/j.amepre.2022.07.002\u003c/li\u003e\n \u003cli\u003eGafner SC, Allet L, Hilfiker R,Bastiaenen CHG (2021) Reliability and Diagnostic Accuracy of Commonly Used Performance Tests Relative to Fall History in Older Persons: A Systematic Review. Clin Interv Aging; 16: 1591\u0026ndash;1616.10.2147/cia.S322506\u003c/li\u003e\n \u003cli\u003eOma\u0026ntilde;a H, Bezaire K, Brady K, et al. (2021) Functional Reach Test, Single-Leg Stance Test, and Tinetti Performance-Oriented Mobility Assessment for the Prediction of Falls in Older Adults: A Systematic Review. Phys Ther; 101(10).10.1093/ptj/pzab173\u003c/li\u003e\n \u003cli\u003eBlodgett JM, Ventre JP, Mills R, Hardy R,Cooper R (2022) A systematic review of one-legged balance performance and falls risk in community-dwelling adults. Ageing Res Rev; 73: 101501.10.1016/j.arr.2021.101501\u003c/li\u003e\n \u003cli\u003eRaina P, Wolfson C, Kirkland S, et al. (2019) Cohort Profile: The Canadian Longitudinal Study on Aging (CLSA). Int J Epidemiol; 48(6): 1752\u0026ndash;1753j.10.1093/ije/dyz173\u003c/li\u003e\n \u003cli\u003eRaina PS, Wolfson C, Kirkland SA, et al. (2009) The Canadian longitudinal study on aging (CLSA). Can J Aging; 28(3): 221\u0026ndash;9.10.1017/S0714980809990055\u003c/li\u003e\n \u003cli\u003eBeauchamp MK, Hao Q, Kuspinar A, et al. (2021) Reliability and minimal detectable change values for performance-based measures of physical functioning in the Canadian Longitudinal Study on Aging (CLSA). J Gerontol A Biol Sci Med Sci.10.1093/gerona/glab175\u003c/li\u003e\n \u003cli\u003eJette AM, Haley SM,Kooyoomjian JT (2002) Late-life FDI manual. Boston, MA: Boston University; 73: 563\u003c/li\u003e\n \u003cli\u003eCohen J, \u003cem\u003eStatistical power analysis for the behavioral sciences\u003c/em\u003e. 2013: routledge.\u003c/li\u003e\n \u003cli\u003eHosmer Jr DW, Lemeshow S,Sturdivant RX, \u003cem\u003eApplied logistic regression\u003c/em\u003e. 2013: John Wiley \u0026amp; Sons.\u003c/li\u003e\n \u003cli\u003eHao Q, Kuspinar A, Griffith L, et al. (2023) Measuring physical performance in later life: reliability of protocol variations for common performance-based mobility tests. Aging Clin Exp Res; 35(5): 1087\u0026ndash;1096.10.1007/s40520-023-02384-0\u003c/li\u003e\n \u003cli\u003eBarry E, Galvin R, Keogh C, Horgan F,Fahey T (2014) Is the Timed Up and Go test a useful predictor of risk of falls in community dwelling older adults: a systematic review and meta-analysis. BMC Geriatr; 14: 14.10.1186/1471-2318-14-14\u003c/li\u003e\n \u003cli\u003eBeauchet O, Fantino B, Allali G, Muir SW, Montero-Odasso M,Annweiler C (2011) Timed Up and Go test and risk of falls in older adults: a systematic review. J Nutr Health Aging; 15(10): 933\u0026ndash;8.10.1007/s12603-011-0062-0\u003c/li\u003e\n \u003cli\u003eNguyen KT, Brooks D, Macedo LG, et al. (2024) Balance measures for fall risk screening in community-dwelling older adults with COPD: A longitudinal analysis. Respir Med; 230: 107681.10.1016/j.rmed.2024.107681\u003c/li\u003e\n \u003cli\u003eBeauchamp MK, Kuspinar A, Sohel N, et al. (2022) Mobility screening for fall prediction in the Canadian Longitudinal Study on Aging (CLSA): implications for fall prevention in the decade of healthy ageing. Age and Ageing; 51(5).10.1093/ageing/afac095\u003c/li\u003e\n \u003cli\u003eSaunders S, Speechley M, Griffith LE, et al. (2026) Prospective evaluation of balance and mobility tests as part of the World Falls Guidelines algorithm. Age Ageing; 55(2).10.1093/ageing/afag028\u003c/li\u003e\n \u003cli\u003eStuck AK, Bachmann M, F\u0026uuml;llemann P, Josephson KR,Stuck AE (2020) Effect of testing procedures on gait speed measurement: a systematic review. PloS one; 15(6): e0234200\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Geriatric assessment, falls, Physical functional performance, Timed Up and Go","lastPublishedDoi":"10.21203/rs.3.rs-9407249/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9407249/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and aim: \u003c/strong\u003ePerformance-based measures, including the Timed Up and Go (TUG), gait speed, chair-rise, and Single-Leg Stance (SLS), are important assessments for mobility. However, the comparative psychometric strength of their various protocols remains poorly defined. This study evaluated the validity of these measures to guide evidence-based selection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis cross-sectional analysis of 157 community-dwelling adults (mean age: 70 years) assessed convergent validity by correlating different protocol measures with self-reported physical function and physical activity. We defined convergent validity as Spearman’s correlations (ρ) exceeding 0.1 for weak, 0.3 for moderate and 0.5 for strong association. To determine each measure's ability to discriminate between groups, we calculated the Area Under the ROC Curve (AUC), with an AUC of 0.70 considered acceptable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Most protocols demonstrated moderate to strong convergent validity with self-reported physical function (ρ: 0.39 to 0.57) and weak or moderate validity for physical activity, except for the chair rise without arm use. Although most protocols could discriminate physical functional limitation, discriminative abilities were mixed for perceived fall risk; gait speed, SLS, and TUG-fast proved valid, but TUG-normal, TUG-cognitive, and the chair rise test were not. No single protocol met the pre-specified threshold (AUC = 0.70) for discriminating fall history, although the TUG-fast approached it (AUC = 0.68, 95% CI: 0.56–0.80).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e While common mobility protocols validly assess physical function and perceived fall risk, their utility in identifying fall history is limited. TUG-fast emerged as a particularly robust tool for discriminating physical function limitation and fall history.\u003c/p\u003e","manuscriptTitle":"Convergent and known-groups validity of common protocols for mobility measurement among community-dwelling adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 17:32:30","doi":"10.21203/rs.3.rs-9407249/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-28T12:08:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198911257269356494280597289893299509458","date":"2026-04-25T17:25:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132435889415702185935468289906573522684","date":"2026-04-24T06:27:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-23T16:58:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T12:48:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T11:44:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2026-04-13T17:36:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"88f921e8-8bf0-451c-9ac6-7eae1dcf8226","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T17:32:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 17:32:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9407249","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9407249","identity":"rs-9407249","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}