Athletic Training and Sports Health Care

Original Research 

Cognitive Loading Produces Similar Change in Postural Stability in Patients With Chronic Ankle Instability and Controls

Melanie L. McGrath, PhD, LAT, ATC; Jennifer M. Yentes, PhD; Adam B. Rosen, PhD, ATC

Abstract

Purpose:

To compare postural stability in patients with chronic ankle instability (CAI) to controls during a dual-task condition via sample entropy.

Methods:

Thirty participants (15 CAI, 15 healthy control) performed three trials of single-leg stance for 60 seconds each under two different conditions: single-task and dual-task (serial subtraction). Sample entropy (SampEn), a measure of pattern regularity, was calculated from the center of pressure excursion in the anteroposterior (AP) and mediolateral (ML) directions. A 2 × 2 mixed-model analysis of variance determined any differences by task or group (P = .05).

Results:

SampEn-AP decreased in the dual-task condition compared to single-task, single-leg balance across groups (F1,28 = 8.23, P = .008, d = 0.53). A significant interaction for group by task was found for SampEn-ML (F1,28 = 4.18, P = .05), but post hoc testing failed to reveal significant differences. Serial subtraction was completed with significantly fewer errors during the dual-task condition compared to the single-task condition (F1,27 = 12.75, P = .001, d = 0.66).

Conclusions:

Patients with CAI do not display differences in regularity of postural stability, even when attention is divided. However, the addition of serial subtraction increased the regularity of AP center of pressure motion. Increased regularity may suggest a change in motor control strategy, reducing natural fluctuations and flexibility within movement patterns during more challenging tasks. Clinicians could use dual-task situations during rehabilitation of patients with CAI to adequately restore stability and function when attention is divided.

[Athletic Training & Sports Health Care. 2020;12(6):249–256.]

Abstract

Purpose:

To compare postural stability in patients with chronic ankle instability (CAI) to controls during a dual-task condition via sample entropy.

Methods:

Thirty participants (15 CAI, 15 healthy control) performed three trials of single-leg stance for 60 seconds each under two different conditions: single-task and dual-task (serial subtraction). Sample entropy (SampEn), a measure of pattern regularity, was calculated from the center of pressure excursion in the anteroposterior (AP) and mediolateral (ML) directions. A 2 × 2 mixed-model analysis of variance determined any differences by task or group (P = .05).

Results:

SampEn-AP decreased in the dual-task condition compared to single-task, single-leg balance across groups (F1,28 = 8.23, P = .008, d = 0.53). A significant interaction for group by task was found for SampEn-ML (F1,28 = 4.18, P = .05), but post hoc testing failed to reveal significant differences. Serial subtraction was completed with significantly fewer errors during the dual-task condition compared to the single-task condition (F1,27 = 12.75, P = .001, d = 0.66).

Conclusions:

Patients with CAI do not display differences in regularity of postural stability, even when attention is divided. However, the addition of serial subtraction increased the regularity of AP center of pressure motion. Increased regularity may suggest a change in motor control strategy, reducing natural fluctuations and flexibility within movement patterns during more challenging tasks. Clinicians could use dual-task situations during rehabilitation of patients with CAI to adequately restore stability and function when attention is divided.

[Athletic Training & Sports Health Care. 2020;12(6):249–256.]

Ankle sprains are one of the most common musculoskeletal injuries in the United States, with approximately 2 million acute sprains occurring annually1 and an estimated $6.2 billion in health care costs.2 Approximately 88% of all ankle sprains occur to the lateral ankle and associated ligamentous structures.3 The risk of suffering a lateral ankle sprain increases threefold after suffering a primary lateral ankle sprain, making this one of the most common reinjuries in sport.4 Up to 70% of people who suffer a lateral ankle sprain will go on to develop chronic ankle instability (CAI), defined by repeated ankle sprains, subjective feelings of instability, and multiple episodes of “giving way.”2 CAI is a substantial concern for adolescent and collegiate-aged athletes, with 23% reporting symptoms of CAI.5 Patients with CAI are at increased risk of post-traumatic osteoarthritis,2 exhibit reduced levels of physical activity,6 and report poorer quality of life.7 Thus, identifying methods to reduce the incidence and overall burden of lateral ankle sprain and CAI is a critical area within musculoskeletal rehabilitation.

Impaired balance is a well-known characteristic of patients with CAI.8 These individuals generally perform worse during dynamic balance tasks that are similar to movements during physical activity and sport.8–10 However, the impact of CAI on static, single-leg postural stability is more varied. Although these static balance tasks are simple to perform and assess in the laboratory and clinic, they only demonstrate moderate evidence for impairment in those with CAI.10 Knapp et al11 reported that only three force platform variables could discriminate between participants with CAI versus controls, and those variables accounted for small shifts in probability. Thus, many traditional time-series variables assessed via force platforms may not display impairment in patients with CAI despite subjective feelings of instability.12 However, non-linear analyses of postural stability may provide more sensitive, unique insights on balance during both static and dynamic tasks.13 Most of the traditional force platform measures (center of pressure [COP] range, sway, and area) only provide a “snapshot” of one aspect of balance performance. However, some non-linear analyses, such as sample entropy (SampEn), evaluate pattern fluctuations over time by evaluating the regularity or predictability of the movement.14 Knowledge of these qualities allows for a more robust interpretation of how CAI impacts postural stability because they complement traditional measures. Two recent studies found that CAI is associated with reduced complexity and increased regularity in COP path, which indicates that these individuals display a more rigid and less adaptable postural control system.9,15 However, another study did not find any differences in the regularity of COP velocity between healthy participants and those with CAI.16 Using movement pattern analyses to characterize postural stability in patients with CAI may provide more insight into the behavior of this particular biological system and allow for greater understanding of balance impairment in this population.

Although many studies on CAI use static balance tasks to analyze stability, fewer have introduced additional cognitive tasks or loads to investigate how these may affect performance.17 “Dual-tasking,” or the performance of a motor and cognitive task simultaneously, is designed to assess the influence that one task may have on the other. The intention is to better replicate what occurs in “real-life,” when patients must navigate the environment while simultaneously engaging in one (or more) cognitively demanding task.18 In addition, individuals with musculoskeletal injury need to devote more attentional resources toward simple motor tasks, including balance, which may influence both motor and cognitive performance during dual-task situations.19,20 Few studies have investigated how dual-tasking influences postural stability in patients with CAI, with two21,22 demonstrating poorer balance and compromised stability and one23 finding no difference in balance. These inconsistent results are similar to other studies with different musculoskeletal pathologies, which suggests that the interaction between cognitive load and postural stability is complex and may not be fully captured with more widely used force platform analyses.17 Investigating the impact of cognitive load on postural stability is important to most effectively understand the mechanisms underlying impaired stability in those with CAI. Using movement pattern analyses may assist in clarifying the regularity of patterns observed under these dual-task conditions, which will help further understand the complex interaction of injury, cognitive load, and stability. Thus, the purpose of this study was to assess COP pattern regularity during single- and dual-task conditions in patients with CAI compared to controls.

Methods

Study Design

A cross-sectional research design was used to compare dependent variables between two groups. The independent variables were: (1) group, which included individuals with CAI (CAI group) and individuals without CAI (control group); and (2) condition, which included single-limb standing with either no additional task or a secondary cognitive task. Dependent variables measured were SampEn in the anteroposterior (SampEn-AP) and mediolateral (SampEN-ML) directions and number of errors. These analyses were a secondary analysis of previously published research.24

Participants

Fifteen individuals with CAI and 15 control participants volunteered for the study (demographics provided in Table 1). Although no research has used the specific dependent variable of interest for the current study (SampEn, a non-linear analysis of pattern regularity), an a priori sample size calculation using prior research,22 using level 5 overall stability index during dual-tasking, healthy versus functional ankle instability, revealed a sample of 15 per group would yield an effect size of 0.95 or greater between groups in the dual-task condition with an alpha level of 0.05 and a beta level of 0.80.

Demographic Information (Mean ± SD)

Table 1:

Demographic Information (Mean ± SD)

All participants were physically active and engaged in 90 minutes or more of physical activity per week. Participants were included in the CAI group if they had: (1) a history of a moderate to severe ankle sprain including inflammatory symptoms (pain, swelling, and/or discoloration) and disruption of desired physical activity, (2) two or more episodes of giving way at the ankle in the previous 12 months, and (3) a Cumberland Ankle Instability Tool (CAIT) score of 24 or less, suggesting decreased ankle function.25 In individuals who indicated bilateral instability, the limb with the lower CAIT score was used for testing. Participants were eligible for the control group if they had (1) no history of lateral ankle sprain, (2) no complaints of their ankle giving way, and (3) a CAIT score of 28 or greater, indicating no deficits in ankle function.26 Participants who reported any history of lower extremity fracture or surgery, current signs of a lower extremity joint sprain, any health conditions that might affect the participant's safety or ability during single-leg balance (including pregnancy), prior diagnosis of a condition that impaired cognitive function, and/or any medication that may impair balance or stability were excluded from the study.

Procedures

Potential participants arrived at the biomechanics research laboratory for an initial screening and completed an informed consent document as approved by the University of Nebraska Medical Center Institutional Review Board. All potential participants completed an injury history questionnaire and the CAIT to determine eligibility. Eligible participants then stayed in the research laboratory for the first of two separate testing sessions. This first session consisted of two different tasks performed separately (single-task paradigms): the serial subtraction test and quiet single-leg standing. Each participant returned 1 week later to perform both the serial subtraction and quiet single-leg standing tasks simultaneously (dual-task paradigm).

A serial subtraction task was chosen for the cognitive task because it has been used in prior dual-task studies,21,23 and requires significant attentional focus while minimizing the perceptual (visual or auditory) input that may mask the effect of cognitive load on balance.18 Participants completed the serial subtraction task by counting aloud by 7s (100, 93, 86, etc), starting at 100, until they reached 2. Responses were recorded by a digital recorder.

Postural stability was assessed via quiet, single-leg stance on a force platform (Balance Master System 8.4; Neurocom) for 60 seconds. The limb with CAI was used as the stance leg; however, in individuals who indicated bilateral instability, the limb with the lower CAIT score was used as the stance leg. Data from both limbs were collected for control participants and their dominant limb was matched to the affected limbs of the CAI participants. During the single-task condition, participants were instructed to stand quietly, as naturally as they could on the one leg for the duration of the test. No restrictions or specific cues were provided regarding permissible amounts of body sway, arm motion, or visual focus. Three successful trials, defined as maintaining single-leg stance without falling or touching the opposite leg to the ground, were obtained with a minimum of 60 seconds of rest between each trial. COP location in the anteroposterior and mediolateral directions was collected from the force platform at 100 Hz and used for analysis.

During the dual-task session held 1 week after the single-task session, participants were instructed to stand quietly on the single leg while simultaneously performing the serial subtraction task. All other components of the testing environment were held as constant as possible, and no additional feedback or instruction was provided. Three successful trials were collected with a minimum 60-second rest between all trials, and COP location was obtained for analysis.

Data Analysis

SampEn was calculated from the COP data in the AP and ML directions to quantify the regularity of a time series.27 Mathematically, the calculation of SampEn involves taking a small segment of the data set and then statistically counting how many times the pattern is repeated in the data set. This is repeated for each segment of data, and the average is taken. Then the segment length is increased by one, and similar patterns are again counted for the longer segment length. The probability of finding similar patterns is then determined. If the data are totally random, there are fewer repetitions for the longer segment than for the shorter one, and the SampEn value nears a value of 3. In contrast, if the data are completely periodic (eg, regular and predictable), then the length of the segment makes little difference in how many repetitions are found, and the SampEn value nears zero. Thus, higher values indicate greater signal randomness, whereas smaller values indicate regularity.27 The calculation of the SampEn was performed using the AP and ML COP time series with the parameters m = 2, r = .2, and N = 6,000. Prior to the selection of these parameters, several parameter choices were checked to ensure the results were not an artifact of parameter choice.28

The digital recordings of the serial subtraction task were analyzed for errors, where a participant did not provide an accurate value. The total errors for each 60-second trial were recorded. The errors were then averaged across all three successful trials on day 1 (when the participant only performed the serial subtraction task), and then on day 2 (when the participant performed the task while balancing). In addition, the average time to completion of the serial subtraction task was calculated using all three successful trials on each day.

Statistical Analysis

SPSS software version 25 (IBM Corporation) was used to calculate all statistics. Descriptive statistics were calculated for demographic and dependent variables and Kolmogorov-Smirnov tests were used to confirm normality. Two 2 × 2 mixed-model analyses of variance (between-subjects: control vs CAI; repeated measures: single-task vs dual-task) were calculated to determine differences between groups and tasks for SampEn-AP and SampEn-ML. An additional 2 × 2 mixed-model analysis of variance (between-subjects: control vs CAI; repeated measure: day 1 vs day 2) was conducted to determine differences in the number of errors committed during the serial subtraction task, as well as the average time to completion. Statistical significance was set a priori at a P value of less than .05 for all tests. Post hoc testing was performed on any statistically significant result using t tests. Effect sizes (Cohen's d) were calculated for all main effects and any significant interaction, and interpreted as weak (d < 0.40), moderate (0.40 ≤ d ≤ 0.80), and strong (d > 0.80).29

Results

Independent t tests confirmed no differences in age, height, or mass between groups (P > .35). Kolmogorov-Smirnov tests confirmed normality for all dependent variables (P > .05). A main effect for task was found for SampEn-AP (F1,28 = 8.23, P = .008, d = 0.53). SampEn-AP decreased in the dual-task condition (0.52 ± 0.12, 95% CI: 0.48 to 0.57) compared to single-task single-leg balance (0.58 ± 0.11, 95% CI: 0.53 to 0.62) (Figure 1). There was no main effect for group (F1,28 = 0.42, P = .520, d = 0.22) and no group by task interaction (F1,28 = 1.42, P = .243). A significant interaction for group by task was found for SampEn-ML (F1,28 = 4.18, P = .05). Post hoc analyses indicated non-significant differences between single-task and dual-task conditions in SampEn-ML for the CAI group (t14 = −1.28, P = .221, d = 0.42) and non-significant difference between single-task and dual-task in SampEn-ML for the control group (t14 = 1.60, P = .133, d = 0.33) (Figure 2).

Box plots demonstrating the main effect for task in the anteroposterior direction. The dual-task condition resulted in a lower sample entropy in the anteroposterior direction (SampEn) compared to a single-task, regardless of group. Both groups (chronic ankle instability [CAI] and control) are presented to better visualize the data.

Figure 1.

Box plots demonstrating the main effect for task in the anteroposterior direction. The dual-task condition resulted in a lower sample entropy in the anteroposterior direction (SampEn) compared to a single-task, regardless of group. Both groups (chronic ankle instability [CAI] and control) are presented to better visualize the data.

Significant interaction for task and group for sample entropy in the mediolateral direction (SampEn). Post hoc testing did not reveal significant changes between tasks in either the chronic ankle instability [CAI] or control groups, despite the visual interaction. The lines represent the CAI (dashed) and control (solid) groups on each task (standard deviation error bars).

Figure 2.

Significant interaction for task and group for sample entropy in the mediolateral direction (SampEn). Post hoc testing did not reveal significant changes between tasks in either the chronic ankle instability [CAI] or control groups, despite the visual interaction. The lines represent the CAI (dashed) and control (solid) groups on each task (standard deviation error bars).

A main effect for day (F1,27 = 12.75, P = .001, d = 0.66) was found when analyzing errors committed during the serial subtraction task. Fewer errors were committed on day 2 (0.62 ± 0.83), during performance of the dual task, compared to day 1 (1.47 ± 1.52) (Table 2). There was no significant interaction (F1,27 = 0.14, P = .712) or main effect for group (F1,27 = 1.50, P = .231) for errors. A main effect for day (F1,27 = 28.35, P < .001, d = 1.01) was found when analyzing time to completion during the serial subtraction task. The task was completed faster on day 2 (27.8 ± 16.8 seconds), during performance of the dual-task, compared to day 1 (41.9 ± 21.1 seconds) (Table 2). There was no significant interaction (F1,27 = 0.04, P = .843) or main effect for group (F1,27 = 0.12, P = .735) for time to completion.

Mean ± SD of Balance and Serial Subtraction Results

Table 2:

Mean ± SD of Balance and Serial Subtraction Results

Discussion

The results of this study confirm that dual-tasking changes postural control in the AP direction, regardless of group. This agrees with prior research that the introduction of a cognitive task changes postural stability.17 Although dual-task conditions have a more variable effect on the postural control of healthy participants,30 the effect of cognitive tasks on balance in those with low back pain, anterior cruciate ligament injury, and CAI is more consistent and generally supports a decrease in single-leg stability.17 A decrease in SampEn indicates that the introduction of a cognitive task increases the regularity of the COP pattern. This suggests a change in motor control strategy to constrain the systems responsible for postural stability when performing two simultaneous tasks. This increase in regularity may compromise the ability to respond to unexpected challenges and lead to loss of balance.

The decrease in SampEn during dual-task conditions indicates that the COP motion pattern in the AP direction became more regular when participants performed the serial subtraction task. Prior research investigating the effect of dual-tasking on postural control found different results, with a decrease in regularity (increased SampEn) when performing a cognitive task during quiet standing.31,32 Both authors hypothesized that this increased irregularity reflects an “automatization” of postural control, where the participants shifted attention away from maintaining balance and allowed the body's innate control mechanisms to take over. However, both studies used healthy participants and performed double-leg quiet stance, rather than a more challenging single-leg stance. Populations with known balance impairment (older adults and patients with stroke) generally display a more regular pattern of postural sway,15,32,33 and balance training produces an increase in irregularity of postural control.34,35 This suggests that impaired balance is related to an increase in regularity of postural sway. The effect of a concurrent cognitive task in the current study, which involved both healthy participants and those with CAI, was to increase regularity during single-leg stance, particularly in the AP direction. This may reflect increased attention given to postural control in this particular set of tasks. The devoted attention to maintaining stability leads to a loss of flexibility in the postural control pattern that would allow them to respond to numerous unexpected challenges that may occur in the environment.

Interestingly, participants committed fewer errors, and completed the task faster, in the serial subtraction task when simultaneously balancing on a single leg compared to quietly sitting. A significant practice effect occurs with many neurocognitive tasks associated with attention, including serial subtraction.36 This practice effect is apparent in the current study, because participants performed better on the second day of testing (which corresponded with the day of dual-task performance). This practice effect may have altered the relative attentional demand of the task, allowing participants to dedicate less attention to the serial subtraction on day 2. Thus, the influence of a cognitive task on postural control is likely influenced by the relative difficulty of both the cognitive task and the balance task. Huxhold et al37 proposed an inverse “U” relationship between cognitive demands and postural stability, with easier levels of cognitive activity associated with improved balance (compared to balance with no cognitive task), but more challenging cognitive activities negatively impacted balance performance. Thus, if the serial subtraction task in the current study had become “easier,” it may have had less of an impact on balance performance.

Despite a significant interaction for SampEn in the ML direction, no differences were found between groups in the different tasks. This is likely due to an underpowered interaction, despite a moderate effect size for the CAI group. This result is similar to that found by Terada et al,16 who noted no differences in COP SampEn between CAI, control, and ankle sprain “copers.” Terada et al16 reported a similar pattern of CAI participants having greater SampEn in both the AP and ML directions, with slightly larger effect sizes than reported in the current study. Thus, although neither study found a statistically significant difference in the regularity of the COP during single-leg stance, Terada et al's results mirror the pattern seen between groups. Future studies should use larger sample sizes or explore dynamic movements such as gait that are more discriminative between groups or tasks.17

Limitations within the study design warrant discussion, particularly concerning the practice effect. First, every serial subtraction trial started at 100 and a practice effect was observed and confirmed by the decrease in errors, number of individuals without any errors, and faster time to completion (Table 2). There is a possibility that a practice effect also was present for the single-limb stance trials. Single-limb stance may have been a unique task for the participants and they may have improved balance performance across the trials. Further, the single task was always presented on day 1 and dual task on day 2. This may have prevented greater differences in dual-task performance from being observed. Future studies may want to minimize this effect by selecting tasks less prone to practice effects, or ensure the practice effect has “worn off” prior to data collection. Second, the length of each trial was 60 seconds. Most participants completed the serial subtraction task (reached zero) prior to the end of the 60-second balance trial. Thus, COP recorded during the dual-task conditions may not reflect dual task over the entire trial. Third, the only indicator of serial subtraction performance was the number of errors. Several participants completed the task without error, representing approximately 30% to 70% of trials without error (Table 2). Future studies may want to consider the amount of time between responses, because this may be a better indicator of cognitive load and processing time. Fourth, this was a secondary analysis of previously published literature in which brain imaging data were collected (reported elsewhere).24 Although having participants perform single-leg stance for 60 seconds was deemed necessary for the assessment of cortical activation,24 it was a challenging length of time for patients with CAI. The possible differences between CAI and controls may have been minimized because only participants who could successfully complete 60 seconds were included in the study, which may indicate that those CAI participants had excellent static single-leg stability. Fatigue may have also been present because a 60-second, single-limb stance with short rests between trials may have been more taxing on the CAI group compared to the controls. Exploring other variables that describe pattern complexity or regularity, or performing different postural control tasks, may provide different insights into the organization of postural stability. The fifth and last potential consideration is the underpowered interactions. The study by Terada et al16 was published after data collection had concluded for this study, and would have likely provided a more accurate sample size calculation for the variables of interest.

Implications for Clinical Practice

CAI is a prevalent and disabling condition among the physically active.2,5 Understanding the impacted postural control strategies in these patients, particularly under situations where their attention is divided between a motor and cognitive task, may help develop more effective interventions to improve stability and function, and perhaps decrease the risk of reinjury. Based on the results of this study, dual-task performance increases the regularity of single-leg balance, which may be associated with poorer overall stability under these conditions. However, the impact of dual-tasking is highly reliant on the types of tasks being performed.37 Thus, clinicians should explore methods of increasing the cognitive demands placed on patients during rehabilitation exercises, both static balance and dynamic postural control tasks.17,19

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Demographic Information (Mean ± SD)

Characteristic CAI (n = 15) Control (n = 15)
Gender 9 F, 6 M 9 F, 6 M
Age (years) 22.7 ± 3.4 22.7 ± 2.3
Height (m) 1.70 ± 0.08 1.71 ± 0.10
Mass (kg) 70.2 ± 15.4 74.9 ± 12.6
CAIT score 17.5 ± 5.7 29.9 ± 0.4
Number of prior ankle sprains 3.7 ± 3.3 0
Months since most recent sprain 28.4 ± 29.5 0

Mean ± SD of Balance and Serial Subtraction Results

Task CAI (n = 15) Control (n = 15)


Single-taska Dual-task Single-task Dual-task
Balance
  SampEn-AP (bits)b 0.60 ± 0.13 0.52 ± 0.14 0.55 ± 0.09 0.52 ± 0.10
  SampEn-ML (bits)c 0.73 ± 0.12 0.68 ± 0.15 0.70 ± 0.08 0.73 ± 0.11
Serial subtraction
  Average errors (number)b 1.8 ± 1.5 0.8 ± 0.9 1.2 ± 1.5 0.4 ± 0.7
  Participants with at least one trial without errors (number) 7 10 10 12
  Total trials without errors (number) 16/42 24/45 21/45 32/45
  Average amount of time to completion (seconds)b 42.8 ± 21.5 29.2 ± 16.7 41.0 ± 21.4 26.4 ± 17.4
Authors

From the School of Integrative Physiology and Athletic Training, College of Health, University of Montana, Missoula, Montana (MLM); and the Department of Biomechanics (JMY) and School of Health and Kinesiology (ABR), College of Education, Health, and Human Sciences, University of Nebraska at Omaha, Omaha, Nebraska.

Supported in part by the National Institutes of Health (P20 GM109090; MLM, ABR, and JMY) and by SPiRE Award #I21RX003294 (JMY) from the United States Department of Veterans Affairs.

The authors have no financial or proprietary interest in the materials presented herein.

The authors thank research assistants William Smith and Nicholas Than for their assistance with this project.

Correspondence: Melanie L. McGrath, PhD, LAT, ATC, School of Integrative Physiology and Athletic Training, University of Montana, McGill Hall 239, 32 Campus Drive, Missoula, MT 59812. Email: melanie.mcgrath@umontana.edu

Received: January 31, 2020
Accepted: June 08, 2020

10.3928/19425864-20200610-02

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