Step Test Scores Are Related to Measures of Activity and Participation in the First 6 Months After Stroke

Abstract

Background: The Step Test (ST) is a measure of dynamic standing balance and paretic–lower-extremity motor control in patients with stroke. Little is known about the extent to which impairments assessed by the ST relate to activity and participation during stroke recovery.

Objective: The purpose of this study was to determine relationships between ST scores and measures of activity and participation during the first 6 months after stroke.

Design: This was a prospective cohort study.

Methods: Thirty-three individuals (18 men, 15 women) with a diagnosis of a single, unilateral stroke participated in the study. Participants were tested one time per month from 1 to 6 months poststroke. The ST was considered an impairment-level measure. Self-selected gait speed and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) Physical Function Index (PFI) were used to assess physical function. Three domains (mobility, basic and instrumental activities of daily living, participation) of the Stroke Impact Scale were used to assess self-reported disability. Regression analyses were conducted to examine the bivariate associations between ST scores and each physical function and disability measure at each time point (1–6 months).

Results: The ST scores were positively associated with both physical function measures. The associations were stronger for self-selected gait speeds (R²=.60–.79) than for the PFI scores (R²=.32–.60). During the first 6 months after stroke, each additional step with the paretic lower extremity on the ST corresponded to a 0.07-m/s to 0.09-m/s increase in gait speed, and each additional step with the nonparetic lower extremity was associated with a 0.07-m/s to 0.08-m/s gait speed increase. The impairment-disability associations were weaker than the impairment-physical function associations.

Limitations: Limitations of the study include a relatively small sample size and lack of examiner blinding with regard to participant characteristics.

Conclusions: Impairments in balance and paretic–lower-extremity motor control, as measured by the ST, relate to physical function and disability during the first 6 months following stroke.

About 780,000 people in the United States experience a stroke each year.¹ Although some survivors of a stroke achieve a full recovery in physical function, approximately one half have long-term motor deficits, and between 25% and 50% require assistance with activities of daily living (ADL).^2,3 The economic burden is enormous, with indirect and direct costs of ischemic stroke from 2005 through 2050 expected to exceed $2.2 trillion.⁴ Loss of earnings and informal caregiving are the 2 largest contributors to overall costs.⁴

The World Health Organization's International Classification of Functioning, Disability and Health (ICF)⁵ provides a useful framework for understanding how stroke may affect health states from biological, personal, and social perspectives.⁶ The ICF model organizes the effects of health conditions such as stroke into the domains of “body structure and function” and “activity and participation.”⁵ Common effects of stroke on body structure and function include motor impairments such as hemiparesis and dyscoordination. Problems in the domain of activity and participation include reduced ability to perform daily tasks (also known as “activity limitations”) and difficulties with involvement in life situations or roles (also known as “participation restrictions”). Although activity and participation sometimes are viewed as 2 distinct concepts, recent analyses call into question the wisdom of trying to distinguish between them.⁷ “Disability” is a general term used to describe a decrement in the activity and participation domain.⁶

Previous researchers^8–12 have found statistically significant relationships between measures of motor impairment and measures of activity and participation following stroke. These relationships can be quite complex. Correlations tend to be modest in size because of the multitude of factors, in addition to severity of motor impairment, that can affect activity and participation after stroke.^9,10,13–15 For example, an individual with severe hemiparesis may use compensatory mechanisms to achieve relatively fast walking speeds.^13,16 On the other hand, an individual who regains adequate motor function may lack the social support he or she needs to achieve independence in self-care activities or participation.¹⁷

Better understanding of how impairments in body structure or function relate to activity limitations and participation restrictions is critical for clinical decision making and health policy.¹⁸ Such understanding will aid clinicians in identifying impairments that may contribute to problems in activity and participation after stroke and in tailoring their interventions to address these impairments. In previous studies of individuals poststroke, the motor abilities having the strongest associations with measures of activity or participation were balance, lower-extremity motor coordination or control, and muscle strength (force-generating capacity).^{9,10,12,14,16,19,20} A consistent finding from these studies was a stronger association of lower-extremity than upper extremity motor abilities with the occurrence of activity limitations and participation restrictions.^9,10,19 Adequate balance and lower-extremity motor abilities are prerequisites for independence in walking, which, in turn, may facilitate full participation in community, social, and civic life.^10,19

Several tools exist for measuring impairments in balance and lower-extremity motor abilities in individuals with stroke. The Berg Balance Scale (BBS)^21,22 and the balance subscale of the Fugl-Meyer Assessment (FMA)²³ commonly are used to assess balance in people poststroke, and the lower-extremity motor function subscale of the FMA is considered the gold standard for assessing paretic–lower-extremity motor abilities. Although both the BBS^24,25 and the FMA²⁶ have been shown to be psychometrically sound for use with individuals poststroke, a major drawback is the length of time required for administration. The BBS requires approximately 20 minutes to complete,²⁷ and a mean (SD) time of 58 (16.6) minutes has been reported for administration of the balance, motor, and sensation subscales of the FMA.²⁸ The length and relative complexity of these measures may place a considerable burden on clinicians and patients, especially patients in the early stages of stroke recovery.^26,29 A tool that combines measurement of balance and lower-extremity motor control and can be administered quickly and easily is more amenable to clinical use.

In our view, the Step Test (ST)³⁰ is such a tool. Originally developed as a test of dynamic standing balance after stroke, the ST requires the individual to repeatedly place one foot on and off a step as quickly as possible.³⁰ The ST, in addition to requiring balance during lower-extremity movement in standing, reflects lower-extremity motor control and coordination. When the individual steps with the paretic foot, the paretic lower extremity must move quickly in flexion and reverse movement direction. When the individual steps with the nonparetic foot, the paretic lower extremity must be stable in extension, supporting full body weight. The ST has evidence of test-retest reliability,³⁰ can be completed in less than 5 minutes, correlates with other measures of balance and mobility after stroke,³⁰ and is responsive to change during stroke recovery.³¹

The overall purpose of this study was to further our understanding of relationships between balance and lower-extremity motor control, as measured by the ST, and measures of activity and participation in survivors of stroke. We sought to address some of the limitations of previous studies by choosing a wide range of suitable measures of activity and participation and by testing at multiple time points after stroke onset. Many previous researchers^8,22,32–34 have used gross measures of ADL, such as the Barthel Index or the Functional Independence Measure, which lack sensitivity and may demonstrate ceiling effects in individuals with mild stroke.²⁵ Duncan and colleagues^18,35 have emphasized the importance of including measures of higher levels of activity and participation, such as instrumental activities of daily living (IADL), as benchmarks of recovery in patients with mild to moderate stroke. With these issues in mind, we chose self-selected gait speed^36,37 and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) Physical Function Index (PFI)³⁸ to assess key aspects of physical function (activity domain of the ICF model). Three domains (mobility, ADL/IADL, and participation) of the Stroke Impact Scale (SIS)^39,40 were used to assess self-reported disability (activity and participation domains of the ICF model).

The specific aim of the study was to determine cross-sectional relationships between ST scores and measures of physical function and self-reported disability during the first 6 months of recovery from mild to moderate stroke. We expected that ST scores for both the paretic and nonparetic lower extremities would be positively associated with physical function and self-reported disability. Because of the multiple social and environmental factors affecting self-reported disability, we expected that ST scores would have weaker associations with SIS scores than with measures of physical function.

Method

Study Design

This was a prospective cohort study. Individuals were identified during an acute hospitalization for stroke and were assessed at monthly intervals for 6 months.

Participants

Adults who had sustained a unilateral noncerebellar stroke were enrolled as part of a larger study of paretic–lower-extremity loading after stroke. Power analysis was based on the ability to detect a linear association, or correlation, in the data. We determined that a sample size of 30 participants was needed to enable us to identify correlations of size .40 or better at an 80% level of power and .05 level of significance. Participants were recruited by posted flyers and by nursing and therapist contacts at University of North Carolina (UNC) Hospitals in Chapel Hill, North Carolina, and WakeMed Rehab, a rehabilitation hospital in Raleigh, North Carolina. All participants had lower-extremity motor impairment, as indicated by a score of ≤28 of the 34 points possible on the lower-extremity motor scale of the FMA.²³ Other inclusion criteria were: (1) being medically stable and free of major cardiovascular or musculoskeletal problems, as indicated by physician's approval for participation in the study; (2) being able to understand and read English; (3) being able to follow 3-step commands; (4) being able to reach in all directions to touch a target with the nonparetic hand while sitting without support; (5) having adequate vision and hearing for completing the study protocol, as indicated by the ability to follow written and oral instructions during screening; and (6) residing within an 80-km (50-mile) radius, with willingness to return to UNC for testing every month from 1 to 6 months poststroke.

Exclusion criteria were: (1) a history of previous strokes or other neurologic diseases or disorders; (2) inability to ambulate or live independently in the community prior to the stroke; (3) terminal illness; and (4) pain, limited motion, or weakness in the nonparetic lower extremity that affected performance of daily activities (by self-report). Informed consent was obtained from all participants prior to testing.

Procedure

Baseline testing was performed at the facility in which the participant was hospitalized and was completed during the time period from hospital admission to 1 month poststroke. At baseline, we examined motor function of the paretic lower extremity using the FMA lower-extremity motor scale. From 1 to 6 months poststroke, participants were tested at monthly intervals at the Center for Human Movement Science at the University of North Carolina at Chapel Hill. Impairments in body structure and function were tested by use of a single measure, the ST. Several measures were used to assess activity and participation, including 2 physical function measures, gait speed and the PFI, and a measure of self-reported disability, the SIS. All tests were administered monthly by the same examiner, with the exception of the SIS, which was administered at 1, 3, and 6 months only. The examiner used new data forms at each session and avoided access to the participant's previous test scores until after data collection was completed.

Step Test.

The ST assesses an individual's ability to place one foot onto a 7.5-cm-high step and then back down to the floor repeatedly as fast as possible for 15 seconds.³⁰ The score is the number of steps completed in the 15-second period for each lower extremity. Participants were permitted to wear any customary orthoses but, in accordance with published procedures for standardized administration,³⁰ were not permitted to use an assistive device during testing. Both sides were tested, with participants completing the test first with the nonparetic foot and then with the paretic foot. Scores for each lower extremity were recorded separately, as well as the sum of these 2 scores. Participants who were unable to stand unsupported were given a score of 0 for both lower extremities. Test-retest reliability of the ST is high, with intraclass correlation coefficients (ICCs) greater than .88 in people undergoing inpatient rehabilitation after stroke.³⁰ The ST has evidence of validity, in that ST scores correlate with other clinical tests of balance and mobility,³⁰ and scores for ST performance with the nonparetic limb as the stepping limb correlate with force platform measures of paretic–lower-extremity loading.⁴¹ The ST also has evidence of responsiveness. Following a 4-week period of stroke rehabilitation, the standardized response means (SRMs)^42,43 of the ST for the nonparetic and paretic lower extremities were 0.92 and 0.95, respectively.³¹

Gait speed.

Self-selected gait speed was determined from a 10-m walk, which was administered according to standardized procedures.⁴⁴ A digital stopwatch was used to measure to the nearest hundredth of a second the time required for each participant to walk a 10-m distance at his or her “usual, comfortable pace” using any customary assistive devices and orthoses. An additional 5 m was measured and marked at the beginning and end of the 10-m distance to allow the participant enough distance to accelerate and decelerate. The average speed for 2 test trials was recorded. Test-retest reliability of walking speed is high, even in people with stroke or other neurological disorders.^36,45 Self-selected walking speed correlates with a number of other measures of walking ability in people with hemiparesis after stroke and has been recommended as an outcome measure for stroke rehabilitation.⁴⁶

SF-36 Physical Functioning Index.

The PFI is a self-report instrument consisting of 10 questions about limitations in higher-level physical activities (eg, vigorous and moderate activities such as pushing a vacuum cleaner, carrying groceries, climbing stairs).³⁸ The score ranges from 0 to 100, with 100 indicating full independence. The PFI was administered by personal interview. Brazier et al⁴⁷ reported a test-retest reliability coefficient of .81 for the PFI, as well as high internal consistency (Cronbach alpha=.93). The SF-36 has been validated for patients with stroke.⁴⁸

Stroke Impact Scale.

The SIS, version 3.0, is a stroke-specific, comprehensive measure of health status.³⁹ For each item, the respondent indicates on a scale of 1 (unable) to 5 (no difficulty at all) the degree of difficulty he or she has had with the item during the past week. Aggregate scores ranging from 0 to 100 are generated for each of the 8 SIS domains. Three domains—mobility, ADL/IADL, and participation—were selected for use in this study as measures at the level of activity and participation. The SIS was administered during face-to-face interviews with the participant or a proxy. A proxy was used for participants with aphasia who were unable to respond in interview or written formats. The same family member acted as a proxy at each administration. The SIS has high test-retest reliability, concurrent validity, and responsiveness to change.^39,49 Rasch analysis has revealed that the 3 domains used in the present study are among those having the most robust psychometric characteristics.⁵⁰

Data Analysis

All analyses were conducted using Stata version 9.2.^* Descriptive statistics were generated for the baseline characteristics of the sample and for the measurements collected at each session. We conducted t tests and chi-square tests of differences in means or proportions to compare the characteristics of participants who completed all 6 test sessions with those of participants who did not complete all test sessions.

Bivariate ordinary least squares (OLS) regression analyses were conducted to examine the relationships between the ST measures and physical function and disability. Separate regression analyses were conducted for each session. In addition, for each relationship we examined, a regression analysis was conducted with the data from all sessions combined.

The data for each session and for the sessions combined were plotted to visually examine the relationships between the measures and to verify that linear models were appropriate. Statistical tests were conducted to confirm that the assumptions for OLS analysis were not violated.⁵¹ The standard errors for the parameter estimates (ie, slopes of regression equations) were corrected if heteroscedasticity was present.⁵² For the analyses with the data from all sessions combined, the standard errors were corrected to account for the nonindependence of measures within individuals.⁵² When dealing with data that consist of repeated measures within subjects, one must account for the correlation of measures within subjects when estimating regression parameters. If this nonindependence is unaccounted for, the standard errors of the parameter estimates (eg, the measure of slope in linear regression) may be underestimated, thereby increasing the likelihood of statistically significant findings. One approach to account for the nonindependence of measures within subjects is to use OLS regression and correct the standard errors using the Huber/White/sandwich estimator of variance.⁵³ This is an acceptable approach when the data are balanced (ie, no missing data) and the variables are normally distributed,⁵⁴ as was the case with our data. Another advantage of using OLS is that the regression parameters enable prediction of the effect of changing one or more components of X (ie, independent variables) on a given individual (ie, dependent variable for a given individual).

Another acceptable approach to deal with the correlation of data within subjects is to use generalized estimating equations (GEEs).^54,55 Generalized estimating equations were developed as an extension of the general linear model (eg, OLS regression analysis) to analyze longitudinal and other correlated data, especially when the dependent variable is not normally distributed.^54,55 Unlike OLS regression parameters that enable prediction on a given individual, GEEs estimate the average response over the population.^43,56 For the GEE models, we specified an identity link function and a normal distribution for the dependent variable because our data were continuous and normally distributed.⁵⁴ For the analyses examining the relationships between the ST and the functional measures (ie, PFI and gait speed) at the 6 different time points, we specified an autoregressive correlation structure, which is appropriate for within-subject data that are repeated over time.⁵⁴ For the analyses examining the relationships between the ST and the disability measures (ie, SIS mobility, ADL/IADL, participation) that had only 3 different time points, we specified an unstructured correlation structure.⁵⁴

Role of the Funding Sources

This study was supported by the National Institutes of Health/National Institute of Child Health and Human Development grant R03HD43907. Partial support was provided by National Institutes of Health/National Institute of Child Health and Human Development grant 5K01HD049593 and National Institutes of Health/National Institute on Aging grant 5P30AG028716 to Dr Purser.

Results

During a recruitment period lasting 2 years 4 months, 112 individuals were contacted regarding possible participation in the study (Figure). Approximately 215 adults with a primary diagnosis of cerebral artery occlusion were discharged from our facility each year during this time frame. Thirty-three participants were enrolled in the study and tested. Their baseline characteristics are presented in Table 1. Two individuals with aphasia required proxy administration of the SIS. All participants received usual medical care and rehabilitation during their participation in the study. Fourteen participants were undergoing inpatient rehabilitation when tested at 1 month poststroke. The number receiving physical therapy decreased from 25 at 1 month poststroke to 11 at 6 months poststroke. Study attrition was relatively low, with 3 individuals (9%) dropping out, all after their third test session (Figure). Four participants missed one test session, and one individual missed 2 test sessions. The 25 participants who completed all 6 test sessions (“completers”) were similar to noncompleters in regard to all baseline characteristics (P>.05) except sex, with a greater proportion of female participants not completing all sessions. Completers and noncompleters also were similar in regard to ST, PFI, gait speed, and SIS scores at the first test session.

Figure.

Schematic illustrating the recruitment process for the study.

Table 1.

Baseline Participant Characteristics (n=33)

^aLower-extremity motor scale only.

Descriptive data for the ST, PFI, gait speed, and SIS are presented in Table 2. Eight participants received the lowest possible score on the ST (score of 0) for both lower extremities at all time points. As suggested by Hill et al,³⁰ participants were classified into 3 groups based on whether they had “considerably greater difficulty stepping” with one lower extremity compared with the other lower extremity. “Considerably greater difficulty stepping” was defined as ≥3 steps difference between lower-extremity scores at ≥2 time points. Twenty-one participants had similar performance with both lower extremities, 10 had greater difficulty stepping with the paretic lower extremity, and 2 had greater difficulty stepping with the nonparetic lower extremity.

Table 2.

Descriptive Statistics of Body Structure and Function and Activity and Participation Variables^a

^aSIS=Stroke Impact Scale, ADL=activities of daily living, IADL=instrumental activities of daily living.

^bn=32.

The results of regression analyses are presented in Tables 3 and 4. At all time points, ST scores were positively associated with both physical function measures. The relationships between ST scores and measurements of gait speed were stronger than those between ST and PFI scores, with R² values ranging from .60 to .79 for the former relationship and from .32 to .60 for the latter relationship (Tab. 3). The strengths of the relationships were similar regardless of whether ST performance was assessed using scores for the paretic or nonparetic lower extremity or the sum of the scores for both extremities.

Table 3.

Relationships Between Step Test Scores and Physical Function Measures^a

^aCI=confidence interval, GEE=generalized estimating equation, N/A=not applicable.

Table 4.

Relationships Between Step Test Scores and Self-Reported Disability Measures^a

^aSIS=Stroke Impact Scale, CI=confidence interval, GEE=generalized estimating equation, N/A=not applicable.

When examining the results of the OLS regression analyses, each additional step with the paretic lower extremity on the ST corresponded to a 3.5- to 4.4-point increase in the PFI score (P<.001 at all time points) and a 0.07- to 0.09-m/s increase in gait speed (P<.001 at all time points). Each additional step with the nonparetic lower extremity was associated with a 2.7- to 4.1-point increase in the PFI score (P<.001 at all time points) and a 0.07- to 0.08-m/s increase in gait speed (P<.001 at all time points).

The results of the GEE models examining the relationship between the ST and the PFI were similar to OLS models examining all of the data. The 95% confidence intervals for the parameter estimates tended to be slightly wider for the GEE models versus the OLS models. The parameter estimates of the GEE models examining the relationship between the ST and gait speed were slightly smaller relative to the OLS models, but still indicated a significant increase in gait speed with each additional step on the ST measures.

Step Test scores also were positively associated with the mobility and ADL/IADL domain scores of the SIS at 1, 3, and 6 months poststroke and with the SIS participation scores at the 1- and 3-month time points (Tab. 4). At 6 months, the 95% confidence interval for the beta coefficients (ie, slope) for the ST and SIS participation relationship crossed 0 (eg, ST paretic limb and SIS participation at months), indicating no linear association between the 2 variables.

The results of the GEE models examining the relationship between the ST and the SIS measures were similar to OLS models examining all of the data. Although the parameter estimates were slightly different with the 2 models, the 95% confidence intervals overlapped. For example, the OLS parameter estimate for the ST (performed with the paretic leg as the stepping leg) and SIS mobility relationship was 4.07 (2.81–5.33), and the GEE parameter estimate was 3.80 (2.84–4.77).

The strongest relationships between the ST scores and the self-reported disability measures were between the paretic–lower-extremity ST scores and the SIS mobility domain scores. This relationship also tended to become a little stronger at the 3- and 6-month time points (R² values of .52 and .49) relative to the 1-month time point (R² value of .34). The weakest relationships were between the ST scores and SIS participation scores, with a majority of the R² values below .20.

Discussion

Results of this study provide support for relationships between impairments measured by the ST and measures of activity and participation during the first 6 months after stroke. The magnitude of the relationships between ST scores and measurements of gait speed speaks to the importance of dynamic balance or paretic–lower-extremity motor control or the combination of both abilities for walking. In addition, strong relationships between ST scores and SIS mobility domain scores suggest that these abilities may play a role in broader aspects of home and community mobility.

Adequate balance is a prerequisite for achieving a non-zero score on the ST. Although use of an assistive device can compensate to some extent for balance impairments during walking, previous researchers have reported that balance (measured using the BBS) is a predictor of walking speed and 6-minute walk distance in individuals with chronic stroke^14,57 and is the strongest predictor of these outcomes in people with moderate to severe stroke.¹⁴ To the extent that the ST is viewed as a measure of balance, our results can be considered to extend these findings to the post–acute phase of stroke recovery. The developers of the ST reported strong correlations between ST scores assessed an average of 54 days poststroke and walking speed in individuals undergoing inpatient rehabilitation.³⁰ These findings are consistent with our results, with ST scores accounting for up to 79% of the variance in walking speed in our participants.

The effects of balance and strength on walking function often are difficult to separate.¹⁴ Perhaps the pattern of ST results for individual patients can help clinicians identify key impairments and design appropriate interventions.³⁰ The 8 participants in our study who scored 0 for both lower extremities on the ST at all time points may have lacked the ability to maintain standing balance or may have had severe deficits in paretic–lower-extremity motor control, or both. Further assessment using the BBS and the FMA lower-extremity motor scale, for example, would be needed to identify specific impairments in these individuals. The 12 participants who had considerably greater difficulty stepping with one lower extremity compared with the other lower extremity apparently had at least minimal balance abilities, but may have had difficulty supporting weight through or performing coordinated movement of the paretic lower extremity.

As expected, relationships between ST scores and self-reported disability, as measured by the SIS, were generally lower than those between ST scores and the physical function measures of gait speed and the PFI. Of the 3 SIS domains examined in this study, ST scores explained the largest amount of variance in the mobility domain, presumably reflecting the importance of walking for home and community mobility. Positive associations between ST scores and the ADL/IADL domain of the SIS are consistent with previous reports of correlations in post–acute stroke between measures of balance and lower-extremity motor control and measures such as the Barthel Index or the Functional Independence Measure.^19,22,24,32 The magnitudes of the correlations in our study generally were somewhat lower than in previous work, possibly because of the inclusion of items reflecting higher-level IADL performance on the SIS.

Weak associations between ST scores and the SIS participation domain are indicative of the influence of multiple environmental and personal factors, beyond the individual's physical function, in determining social roles and quality of life after stroke. The balance and motor control abilities measured by the ST may have figured more prominently in participation in the first few months of stroke rehabilitation, when a majority of the participants were receiving physical therapy and many were in inpatient rehabilitation. By 6 months poststroke, participants had been reintegrated into long-term living environments, and family and other social supports most likely increased in importance. In a study by Desrosiers et al,⁵⁸ a discharge measure of lower-extremity motor coordination (LEMOCOT) requiring subjects to move the paretic foot alternately between 2 targets was a significant predictor of participation at 6 months and 2 to 4 years poststroke. These associations were similar in strength to our ST-SIS participation relationships, despite the fact that the LEMOCOT is performed in a sitting position and, therefore, lacks a standing balance component. The importance of balance relative to upper- or lower-extremity motor control in determining level of participation may decrease in more chronic stages of recovery after stroke.¹⁵

An important strength of this study was collection of data from the same participants at multiple time points, beginning less than 1 month after stroke and continuing at 6 subsequent time points. One limitation of the study was the relatively small sample size. In addition, the examiner was not blinded with regard to participant characteristics, thereby introducing the possibility of bias in testing. We attempted to minimize bias by adhering to standard testing protocols and by avoiding examiner access to previous test scores.

Conclusion

Impairments in balance and lower-extremity motor abilities, as measured by the ST, were associated with measures of activity and participation from 1 to 6 months poststroke. The strongest associations were between ST scores and measures of physical function and mobility, such as gait speed. Associations between ST scores and scores on the participation domain of the SIS were weakest and tended to decrease over time. The ST is a simple and quick assessment that can provide important information for clinical decision making.