Pai, Yi-Chung PhD; Wang, Edward PhD; Espy, Debbie D. MSPT; Bhatt, Tanvi PhD
The large number and variety of tools available for assessment of fall risk can make choosing the most appropriate tool challenging,1 and there is no clear evidence that any one screening tool is the most useful for identifying those at risk of falling.2 Clinical tools typically used for assessing fall risk comprise of various self-initiated, volitional activities. Many are practical because they are easy to perform, require little time, equipment, and training, and offer a quantifiable means of documenting patient progress and status. For example, the Timed Up and Go (TUG) test is an excellent instrument for fall prediction,3 with evidence of high sensitivity and specificity.4 However, certain evidence indicates poor association of TUG scores with patient provided history of falls.5 Another class of clinical tests of balance and stability, posturography, quantifies postural sway in standing using force platforms.6 Measuring volitional postural sway to test individuals' limits of stability has demonstrated potential to detect balance deficits and differentiate older individuals with a history of falling from those without7; however, its ability to predict future falls in community-dwelling older adults is to be demonstrated.8
One factor that can limit clinical tools in identifying community-dwelling individuals who are at risk for falls relates to the ceiling effect, in which the sensitivity of the measurement is compromised by a lack of variability in maximum-performance scores. Another potential limitation is that they are not designed to test reactive responses, which are most often one's critical defense against a fall. Efforts have been made to assess “dynamic” posturography,9 by introducing perturbations during quiet standing, as in the postural stress test10 or the motor control test.11 The validity of using “static,” “dynamic,” and “reactive” components of standing balance to identify healthy older adults, who are nonetheless at heightened risk of falling, has been questioned.12 Limitations may arise with such tests because they involve quiet standing, whereas most falls occur during dynamic activities (eg, walking, stair-climbing, sit-to-stand transfers).13 In addition, the perturbation magnitude may be insufficient to induce balance losses and falls in healthy older adults.
To address these issues, a series of experiments was conducted that mimics real-life conditions. In these studies, falls were induced experimentally with unannounced, large perturbations (ie, sufficient to induce balance loss or falls) during functional activities, in a well-protected laboratory environment.14,15,16,17 Furthermore, a previous study revealed that upon repeated slip exposure during sit-to-stand, participants adapted rapidly to reduce fall incidence from 73% initially to less than 5% by the fifth repeated slip.15 When they were subjected to another slip after a block of nonslip trials, only 41% of participants experienced a loss of balance (vs 100% for the first, novel slip) and 20% a fall.15 On the basis of these observations, a connection was hypothesized between poor adaptation and retention of fall-resisting skills in the laboratory17 (or clinical setting) and a greater risk for balance loss and falls in everyday living. Few studies address this essential question.18
The purpose of this study of community-dwelling older adults was to determine whether future risk of falls in everyday living could be predicted by (a) their initial reaction (ie, fall, loss of balance, or successful recovery) to an unannounced, novel slip induced during chair rise, (b) their subsequent adaptability to repeatedly induced slips, or (c) their functional status measured by the TUG. The ability to adapt to the slips was defined by how successfully and how rapidly throughout the session individuals reduced the incidence of backward losses of balance or falls. Operationally, “good” adaptation within a test session would involve fewer losses of balance and falls (ie, lower overall slip score) and/or a successful recovery upon the second slip (indicating rapid adaptation), which would be maintained through the last slip (indicating an adaptation plateau).17 In this preliminary study, it was postulated that all 3 measures (initial slip reaction, adaptability, and TUG score) would correlate with the likelihood of future falls, because each reflects a different aspect of a person's capacity for resisting falls.
The laboratory assessment session included 13 older adults (9 men; age mean (SD) = 72 (5) years, range = 65 to 85 years), who gave written informed consent and were paid to participate. Older adults were ambulatory, community-dwelling individuals, free of musculoskeletal, neurological, cognitive, or other systemic disorders, as assessed by a health questionnaire. Participants who were classified as osteopenic or osteoporotic19 scored less than 25 on the Folstein Mini-Mental State Examination, or demonstrated symptomatic postural hypotension were also excluded. Institutional review board approval was obtained.
For the TUG test, participants were seated in a chair and asked to rise and walk to a line on the floor (3 m ahead), turn around, return to the chair and sit, “at your normal pace.” One practice trial was given for each participant. They were made aware that they would be timed.3 Scores were the time, in seconds, to complete the task.3
Experimental slips were induced at seat-off during a sit-to-stand task by computer-controlled release of 2 sliding platforms beneath the participant's feet.15,20 Once released, the platforms were free to translate in the anterior direction on low-friction linear bearings until they reached the maximum slip displacement of 24 cm. Platform movement was terminated by a latch mechanism at the end of the low-friction tracks. All participants wore a full-body safety harness attached by ropes at the shoulders to a ceiling-mounted support. All participants wore their own comfortable walking shoes. Once the feet were in contact with the plate, there was very little relative movement between the plate and the participant's feet. Thus, the shoe characteristics could not influence the slip properties.21 Participants were informed that they would initially be performing trials of sit-to-stand “as fast as possible” and that “later on” a slip would take place. There were 4 nonslip trials before the first slip, during which participants were entirely unaware of any forthcoming trial condition. Following the first slip, participants were informed of the possibility of slipping on subsequent trials. It was emphasized that they should “try not to fall,” by remaining standing “still” after platform movement. After the first slip, participants underwent a block of 4 consecutive slipping trials, followed by a nonslip block of at least 3 consecutive unperturbed trials, and then 2 further slipping trials. Thus, there were a total of 7 slip trials (Figure 1).
A computer algorithm determined the outcomes on the basis of preset, objective criteria input from the collected kinematic and kinetic data. When the recovery heel marker was posterior to the slipping heel marker, as indicated by motion data collected at 60 Hz (Peak Performance Motion Capture System, Englewood, Colorado), the trial was classified as “loss of balance with recovery stepping.” Trials in which the participant stood without taking any step(s) were classified as “successful recovery.” A fall was identified if a line connecting the bilateral hip markers descended to within 5% body height of its initial seated height15 and was verified with readings from a load cell in series with the harness (average force exceeding 4.5% body weight over any 1-second period). Each slip outcome was as scored 0 (successful recovery), 1 (loss of balance), or 2 (fall). The slip outcome scores for the 7 trials were summed for each participant and identified as the “slip score,” ranging from 0 to 14. Higher “slip scores” indicated higher overall incidence of falls and loss of balance.
Follow-up Fall Experience Study
Participants were contacted by telephone between 29 and 32 months (mean (SD): 30.6 (1) months) after their initial laboratory tests (at which time they had not been informed about this future contact) to collect information about fall occurrences. They were informed, both verbally and in writing, that a fall should be considered any event in which they landed unintentionally (emphasized) on a lower surface such as a chair, the floor, or the ground. They were asked a series of open-ended questions as to the number of falls they had experienced in the 12 months immediately before the call. If falls had occurred, they were asked to provide details about the fall. The results were categorized and tallied as in previous studies.22
Data were summarized using descriptive statistics. Age, TUG, and slip scores between participants who reported falls in the follow-up interview and those who did not were compared using the Mann-Whitney U test; the slip outcome was compared using the Fisher exact test. Using an alpha level of .05, the sample size used would have an 80% power to detect a 1.7 standard deviation difference between participants with history of falls and participants with no history of falls using a 2-sided t test. A sensitivity, specificity, and likelihood ratio analysis was performed for each predictive variable between participants with history of falls and participants with no history of falls. Statistical significance was established at an alpha level of .05 throughout. All statistical analyses were performed using SAS 9.1 statistical software (SAS Inc, Cary, North Carolina).
Four of the 13 participants experienced a future fall (after their participation in the initial lab portion of the study, as reported when surveyed): 3 fell once and 1 person fell twice. Participants who fell on the first induced slip were no more likely to report a future fall than those who recovered on the initial slip (P > .05). Similar TUG scores were found for both groups, and they were not significantly associated with future falls (Table 1). In contrast, participants who reported falls on follow-up had significantly higher overall falls and loss-of-balance incidence during the initial assessment (higher slip scores) than those who did not experience any future falls (Table 1). In particular, participants who did not lose balance during the second reslip trial were significantly less likely to report falls experienced in the year preceding the survey than those who lost balance in that same trial (Table 2).
A higher overall slip score or having lost balance during the second reslip trial was associated with greater likelihood of future falls (P = .02; Table 3) than a lower slip score or not having lost balance during the second reslip trial. In comparison, a failed recovery (loss of balance or fall) on the first induced slip did not significantly increase the likelihood of future falls (P > .2) nor did a higher TUG score (P = .85) or the outcomes of any of the other slip trials (P > .2 for Slip 2 to 5 and reslip 1). The slip score and the second reslip outcome demonstrated a predictive ability of 85%. Overall slip score had both high sensitivity and specificity (75% and 89%, respectively; Table 3). A loss of balance on the second reslip correctly classified 2 of 4 participants with reported falls (50% sensitivity) and all 9 participants with no reported falls (100% specificity). Although the TUG had a similar sensitivity as the second reslip trial, it had a lower specificity (56%), affecting its predictive value (46%). Conversely, although failed recoveries on the first initial slip trials accurately classified all 4 participants with reported falls, it classified none of the participants with no reported falls.
Table 3Sensitivity, ...Image Tools
These findings partially support the hypotheses that responses to a series of slips induced experimentally during a sit-to-stand task would serve as a good predictor of future fall risk. Specifically, adaptability to repeated slips, as indicated by a lower slip score (ie, fewer overall balance losses or falls over repeated slips) and a successful recovery on the second reslip were indeed associated with a lower likelihood of future falls. The initial response to the novel slip and the TUG scores, however, did not yield similar predictions of future falls. The positive findings from the test would be especially important as many falls occur during transitions such as sit-to-stand13 and this task has often been a key component of fall risk assessment.23,24
The reason that the behavioral outcome on the first, novel slip proved to be a poor predictor of future fall risk may be that in this trial, all the participants lost balance and exhibited a failed recovery. Thus, the ability to predict those who would not fall in the future was poor (0% specificity), although the sensitivity was high. Previous studies have indicated that in just 1 or 2 trials of repeated slip exposure, participants can reach a steady state characterized by improved stability and drastically reduced falls incidence.15,25 Just as the recovery outcome of the first slip depends on a person's reaction to an unexpected perturbation, the outcome of later slips reflects participants' ability to adapt. The falls incidence of 31% (4/13) in the previous year reported in our study is about the median of the range reported in previous studies.26,27
Such adaptation may occur through recalibration of an individual's internal representation of stability limits as a result of sensorimotor feedback inputs received from the repeated perturbation experience. These findings concur with previous findings that older adults with a history of greater fall incidence may also have greater difficulty adapting to different sensory environments8,28,29 and have difficulty adapting to repeated stance perturbations.28,30 As the second reslip was induced after a block of nonslip trials, the performance on this trial signifies that the participants' adaptive changes had reached a steady state under unpredictable conditions (slip or nonslip); likewise, this may also indicate a better capacity for short-term retention of the acquired adaptation. Typically, the most dramatic improvements in the rate of performance are seen from the first to second and the second to the third repeated slip trials 15,31,32; hence, the expectation was that the second slip outcome would have been a critical fall risk predictor. A future study with a larger sample size may show this to be the case. Nonetheless, this study still provides preliminary evidence to support the idea that a person's ability to adapt to perturbations could be a key in identifying and reducing fall risk.
Adaptation to repeated perturbations was a better predictor of future falls among community-dwelling older adults than the functional mobility assessment based on the performance of a volitional task (the TUG). The control of balance and stability during volitional movements can be fundamentally different from that required during responses to perturbations.33 For instance, the loading-unloading pattern seen with anticipatory control in volitional stepping can be drastically altered during perturbation-induced (reactive) protective stepping.34 Moreover, although feed-forward controlled proactive adjustments and changes in reactive control of dynamic stability have been shown to contribute to the successful recovery from a slip during walking,31 it was proposed that experiencing specific sensory inputs through perturbation was key to modifying the future motor response35 and improving the outcome of the slip. In line with these findings, recent evidence has raised questions about the ability of clinical balance tests to predict fall risk in a community-dwelling, older adult population.36 Furthermore, the results are in accordance with previous literature in which the TUG scores for community-dwelling older adults have been relatively low (ie, less than 12 seconds), with poor specificity and responsiveness.5,36
The present study has its limitations; the first is, obviously, the small sample size. On the basis of the assumption that fall incidence among older adults in real-life is about 30% annually, a sample size of 200 participants would be needed (adjusted for the estimated annual attrition rate of 35%) to provide adequate statistical power to assess this paradigm that would predict healthy older adults' annual fall risk. Second, older adults may have over-or underreported the actual incidence of falls in telephone interviews.37 The participants did not keep a fall diary; thus, the results depended on their memory. The effects of inaccurate recall and recall bias could be mitigated in a prospective study by using a variety of tools such as falls calendars or periodic telephone interviews.38,39 If a retrospective, self-report design is to be used, on the other hand, a longer recall period, namely 1 year, is preferable to a shorter period.40,41 For this study, because the participants were healthy older adults with no other neuromuscular or systemic disorders, their reporting could be quite accurate. Furthermore, on the basis of the screening of their cognitive ability and memory at the time of the laboratory test, it was assumed that participants would be cognitively able to recall major events (such as a fall) that occurred in the last 12 months. Third, because the participants were community-dwelling, they constituted a more active and fit sample of the population of older adults. In fact, in this population, more typical clinical tools have been shown to encounter ceiling effects and the current paradigm may be relatively more challenging. Fourth, the study examined only slip-related falls because recovery from slip-related falls is very challenging and the resulting fall itself dangerous, causing debilitating injuries (hip fractures) in older adults. However, the prospective study correlated forward slip-related falls induced in the laboratory to all types of falls experienced in daily living. Finally, an assessment that requires inducing perturbations during a daily activity will likely be more costly to conduct than volitional performance tests without perturbation. The added cost associated with assessments on the basis of reaction and adaptation to external perturbations would be justified, however, if such tests can accurately demonstrate, in a safe environment, the future risks of falls among community-dwelling older adults. Yet, despite these limitations, the rationale for this innovative conceptual framework, per se, of using one's adaptability to predict his or her future falls risk, may be sufficiently attractive to warrant further investigation.
In summary, the present study provided direct yet preliminary evidence that links adaptation to perturbations with falls risk assessment among older adults. This lends credence to a new theoretical framework on the basis of using measures of how quickly and effectively a person is able to adapt to potentially life-threatening perturbations in determining the future likelihood of falls induced by similar perturbation in everyday living.
The initial laboratory tests were conducted at the Programs in Physical Therapy at Northwestern University Medical School and funded by NIH 2R01-AG16727 (Y.C.P.) and a grant from the Whitaker Foundation (Y.C.P.). The participants were recruited from the database established by Buehler Center on Aging at Northwestern University Medical School. The authors appreciate the invaluable comments provided by Mike Pavol, PhD.
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adaptation; assessment; reaction; Timed Up and Go; volitional performance