Daily life often requires the ability to divide one's attention between tasks such as walking and talking concurrently. In rehabilitation literature, the term dual-task (DT) refers to the addition of a concurrent secondary task to a postural control or gait task and requires one to divide attention between the 2 tasks. The secondary task is often cognitive in nature or requires upper extremity manipulation of an object. Single task (ST) refers to the performance of a gait or postural task alone, without the secondary task. In older adults, motor performance degrades under DT compared with ST conditions, suggesting that balance and gait require attentional and cognitive resources.1–4 Furthermore, difficulty with DT performance has been linked to fall risk,5 making consideration of DT performance clinically relevant. In fact, some research is beginning to consider the effects of DT training to reduce the impact of dual-tasking on motor performance.6–11
Impaired balance and gait are certainly concerns for adults with dementia, as gait deviations are more prevalent,12 and fall rates are greater13 in this population than for individuals with intact cognition. In addition, investigators have found that older adults with cognitive impairment (CI) have a greater DT cost (DTC—the decline in an individual's motor performance under DT conditions relative to ST conditions) when compared with older adults without CI.14–16 These studies provide additional evidence that balance and gait require cognitive resources, because the presence of CI appears to further degrade an individual's motor performance during DT conditions.
In addition to group differences in DT performance between individuals with and without CI, some investigators have considered whether a linear relationship exists between cognition and DT performance; that is, does DTC steadily increase as cognition decreases? Various investigators who have considered this question found correlation coefficients ranging in magnitude from 0.05 to 0.74,17–22 with the variation possibly due to differences in tasks and variables used in the studies, as well as in subject characteristics. In some of the studies considering a linear relationship, samples included only individuals with higher cognitive levels and the homogeneity of these subjects could have limited the potential to discover a linear relationship between cognition and DT performance.19–21 In 3 studies, researchers used simple DT performance (motor performance during DTs not adjusted for ST motor performance) in their correlation analysis rather than DTC.17,19,22 Considering whether or not ST motor performance has a confounding influence on the strength of the relationship between DTC and cognition would be important, because a decline in quality and velocity of gait even as an ST is typical for individuals with cognitive decline.12 Finally, in 2 studies, only 1 DT was used as an outcome measure, preventing the ability to determine whether the strength of the relationship varied with the difficulty of the DTs.18,22 Task difficulty may be an important concept to consider in DT research, because of the potential impact of task difficulty on quality of movement and safety, but also when considering how to improve DT performance through intervention. For individuals who may have difficulty learning new tasks, extremely difficult tasks may exceed their capacity for performance and therefore hinder learning, a concept suggested by Guadagnoli and Lee's23 challenge point framework. Thus, when designing DT training programs, it would be important to understand the influence of DT difficulty as it relates to the skill level of the learner.
The purpose of this cross-sectional study was 2-fold: (1) to explore the relationship between cognitive level and DTC in a sample of individuals with varying cognitive levels and (2) to determine how the difficulty of the combined tasks impacts this relationship. We hypothesized that (1) the relationship between cognitive ability and DTC would be linear and (2) the level of difficulty of the combined tasks in a DT condition would impact the strength of the relationship between cognitive ability and DTC.
We sought to improve upon other studies considering the relationship between cognitive level and DT performance17–22 by incorporating the following aspects into our design: (1) using a sample with diverse cognitive levels, (2) using DTC rather than simple DT performance so that older adults motor performance during DTs was expressed relative to their ST motor performance, and (3) utilizing various DTs so that we could determine whether the strength of the relationship varied on the basis of difficulty of the motor and cognitive components of the DTs.
This study was a cross-sectional exploratory study to determine the relationship between DTC and cognitive level as measured with the Mini-Mental State Examination (MMSE).
A convenience sample of participants was recruited from a local health system that consists of a continuum of care for older adults, including assisted living, residential memory support units, adult day services, and wellness programs for community-dwelling older adults. Therefore, it provided a diverse population in terms of cognitive level. Inclusion criteria for the participants were (1) age 65 years or older and (2) ability to walk 10 m or more independently with or without an assistive device. Exclusion criteria for the participants were as follows: (1) Parkinson's disease, as attentional strategies are already often used by individuals with this diagnosis to compensate for motor impairments24 and (2) currently receiving physical therapy for balance or gait limitations, as this could impact safety of the participants as they performed the experimental tasks.
The study protocol was approved by the University of Nebraska Medical Center institutional review board. Participants or their legally authorized representative provided written informed consent for participation in this study.
Participants took part in 1 testing session. They first completed the MMSE and then practiced 2 cognitive tasks while seated: (1) counting forward by 1's from a randomly selected 2-digit number between 10 and 20 for 30 seconds and (2) counting backward by 3's from a randomly selected 2-digit number between 70 and 90 for 30 seconds. Participants then performed 2 motor tasks as STs: (1) the Timed Up and Go (TUG) and (2) a 6-m walk for which self-selected walking speed (SSWS) was calculated. Participants performed one practice trial for the TUG and 6-m walk; a second trial was used in data analysis. The cognitive and motor tasks were then combined into 4 DT conditions: the motor tasks plus counting forward by 1's (TUG1 and SSWS1) and the motor tasks plus counting backward by 3's (TUG3 and SSWS3). Different starting numbers were used for counting in the various conditions. We chose our motor and counting tasks because of their expected level of difficulty, with the TUG more challenging than the 6-m walk because the TUG includes a sit-to-stand transfer plus a turn, and counting backward by 3's more difficult than counting forward by 1's. Therefore, we believed that the TUG3 would be the most difficult combination of tasks, SSWS1 would be the easiest, and the TUG1 and SSWS3 would be moderately difficult relative to the other DTs. Further information about the tests follows below.
The Mini-Mental State Examination
The MMSE (Psychological Assessment Resources Inc, Lutz, Florida) is a commonly used test of cognitive performance that requires 10 to 15 minutes to administer. It tests an individual's orientation, attention, memory, and language. A maximum score is 30 points and scores of fewer than 24 are considered indicative of CI.25
The Timed Up and Go
The TUG is a reliable and valid test of functional mobility for older adults.26 Its reliability has also been established for individuals with dementia.27 This test required the participant to stand up from a chair with arms, walk 3 m to a line marked on the floor, turn, walk back, and sit down. Participants were instructed to walk at their normal pace, and their performance was timed in seconds to 2 decimal places. If they typically used an assistive device for gait, this was allowed. Verbal cues were used as needed during the TUG, as was also done by Nordin et al.28
Self-Selected Walking Speed
Self-selected walking speed, promoted as the “sixth vital sign,”29 is a reliable30,31 and valid32 measure of functional mobility, with reliability also noted in those with dementia.27 A distance of 6 m was marked on the floor, with approximately 3 m on either side to allow for acceleration and deceleration. Participants were instructed to walk at a normal pace across the room, until they were told to stop. The time to walk the center 6 m was recorded in seconds to 2 decimal places, and SSWS was then calculated in meters per second. If participants typically used an assistive device for gait, this was allowed.
No instruction was given to prioritize either the motor or counting task during performance of the DTs. If participants stopped either the motor or counting task during the DT trial, they were verbally prompted to continue. The order in which the DTs were performed was randomized for each subject to avoid any order effects. The time it took to complete the TUG and 6-m walk under DT conditions was measured in seconds to 2 decimal places. Self-selected walking speed under DT conditions was calculated for the 6-m walk. The types of DTs used in this study have been successfully used by other researchers to investigate the impact of DT conditions on locomotion in individuals with and without CI.8,33–35 Reliability of SSWS during DTs has been established for older adults with mild CI.36
We defined DTC as the percent decline in motor performance in DT conditions relative to ST conditions. Motor performance was measured in seconds for the TUG and in meter per second for SSWS. The DTC was calculated for each DT condition using the following equation: DTC = [(difference between DT and ST motor performance)/ST motor performance] × 100. A negative number would indicate that performance under DT conditions was slower than that under ST conditions. The more negative the value of DTC, the slower the individual performed the motor task under DT conditions relative to ST conditions.
IBM SPSS Statistics Version 19 (International Business Machines Corp, Armonk, New York) was used for statistical analysis. Because our data were not normally distributed, we used Spearman rank correlation coefficients to determine the linear relationship between the MMSE and the DTC. We also calculated descriptive statistics for subject characteristics and created box plots to illustrate the distribution of DTC for the various DTs. To compare the difficulty of the DTs, the Friedman 2-way analysis of variance on ranks was used to determine whether the magnitude of DTC differed among the 4 DT conditions, with the Wilcoxon signed ranks test used for post hoc pairwise comparisons. The significance level for all tests was set at α ≤ 0.05.
All individuals who expressed interest in the study, either personally or through their legally authorized representative, were found to be eligible and completed the study. Twenty-three individuals with MMSE scores ranging from 7 to 30 participated. Three of the 23 individuals used an assistive device for gait. See Table 1 for descriptive statistics on participant characteristics.
Statistically significant correlations between the MMSE and DTC were found for SSWS3, TUG1, and TUG3 (Table 2). A moderately strong correlation was found for TUG1 and the MMSE, while the strength of the relationships between the MMSE and the TUG3 or SSWS3 was fair.37 Scatterplots of the data for the relationship of DTC and MMSE are shown in Figure 1 for SSWS1 and SSWS3 and in Figure 2 for TUG1 and TUG3. The relationships between DTCs and the MMSE were positive, as DTC became less negative as the MMSE score increased.
Figure 3 provides box plots of DTCs for each DT, with the median DTC being largest for the TUG3, while SSWS1 had the smallest median DTC and the least amount of variability. The results of the Friedman 2-way analysis of variance on ranks indicated a statistically significant difference in DTC among the 4 DT conditions, χ2(3) = 47.09, P ≤ .001. Post hoc analysis with Wilcoxon signed ranks tests resulted in a nonsignificant difference between TUG1 and SSWS3 (P = .09), but significant differences between all other pairs (P = .02 for TUG1 and SSWS1, P ≤ .001 for the remaining pairs).
The purposes of this study were to determine whether there was a linear relationship between cognition and DTC, and to determine whether the strength of this relationship varied on the basis of the difficulty of the DTs. Our study expanded upon previous research in this area by ensuring that our sample had a broad range of cognitive levels, normalizing each participant's DT performance by expressing it as DTC rather than simple DT performance, and utilizing DTs with a range of difficulty. Our hypothesis that the relationship between cognitive ability and DTC would be linear was partially supported. We found fair to moderate linear relationships between cognition and DTC for 3 of the 4 DTs used in this study (Table 2). Our hypothesis that the level of difficulty of the combined tasks in a DT condition would impact the strength of the relationship between cognitive ability and DTC was also supported. The weakest and only nonsignificant linear relationship between cognition and DTC was found for SSWS1, the easiest DT. The more difficult DTs had statistically significant and stronger linear relationships (Table 2, Figure 3).
Participant Characteristics and Use of DTC
One of the strengths of this study relative to other work in this area was the fact that we studied participants with a wide range of cognitive levels (MMSE scores of 7-30). Other studies that reported correlations of similar magnitude also tested individuals with varying cognition,17,18 while studies that reported some of the weakest correlations studied individuals who were more homogenous and excluded individuals with CI.20,21 Because we included individuals with a variety of cognitive levels and found that DTC increases as the MMSE score decreases, this study provides further support that motor performance requires cognitive resources, especially in individuals with CI.
In addition, it was important to control for individuals' ST motor performance by using DTC in our analysis rather than simple DT performance, particularly because motor disorders typically accompany cognitive decline.12 Studies that used simple DT performance (not DTC) in their analysis reported correlation coefficients of similar17,19 or even greater22 magnitude to ours. However, the strength of the relationships in those studies may be inflated because the underlying motor performance as an ST may be contributing to the relationship. To assess the potential for ST motor performance to confound the relationship in our data, we also conducted a correlation analysis using simple DT performance and the MMSE. Using simple DT performance, we found correlation coefficients slightly higher (ranging from 0.45 to 0.59) than those for DTC as shown in Table 2. Thus, we feel that adjusting for ST motor performance by expressing DT ability as a cost rather than using unadjusted DT performance data is an important step when expressing the impact of secondary tasks on motor performance.
Impact of Task Difficulty
One of the purposes of our study was to determine whether and how task difficulty impacts the linear relationship between DTC and cognition. We found the weakest relationship for SSWS1, the task with the least amount of difficulty (Table 2; Figure 3). Other studies that utilized DTs of varying difficulty also found that the strength of the relationship was reduced for the easier task.17,19 On the contrary, in 2 studies, there was no discernible pattern of strength of relationship based on DT difficulty.20,21 However, both of those studies tested only individuals without CI, which may have limited the ability to determine the influence of task difficulty on the relationship.
When comparing the magnitude of DTC between tasks, we found that DTC was greater for more cognitively demanding tasks, reinforcing the concept that individuals utilize cognitive resources for motor performance. We also found that all individuals, even those with CI, could at least attempt all of the tasks, regardless of the level of task difficulty. If the DTs, particularly the more difficult ones, exceeded the capability of our most cognitively impaired subjects, we do not anticipate seeing the steady decline in their performance relative to the other individuals (Figures 1 and 2). If they were unable to even attempt the DTs used in our study, we believe that we would have seen weaker relationships between DTC and the MMSE, or perhaps a sharp increase in DTC at a certain cognitive level, rather than a linear relationship. Our findings suggest that patients with CI may be able to engage in more challenging tasks than might be assumed, which could inform future studies of DT training for individuals with CI, a patient population for whom to date there are limited studies about the efficacy of DT training.8,10
The impact of task difficulty on motor performance has important implications for motor learning, including motor learning in DT training programs. Traditional motor learning theory suggests that challenging practice conditions are superior for long-term retention of motor skills, at least for individuals without CI.38 However, studies of motor learning involving individuals with Alzheimer's disease suggest that easier practice conditions are best for these individuals.39,40 Other work has shown that more demanding practice conditions are less beneficial for learners who are relative novices at the tasks to be learned, or when the task difficulty is great.41–44 These findings are consistent with the challenge point framework proposed by Guadagnoli and Lee.23 Their framework suggests that the cognitive and motor skill levels of learners impact how they respond to practice conditions; thus, the difficulty of the task being practiced needs to be considered. Consequently, the ability of the learner and the difficulty of the task must intersect at a point where practice invokes a learner-appropriate level of challenge. If the task is either too easy or too hard for the learner, learning will be impeded. We found that even individuals with considerable CI were able to at least engage in performance of more challenging DTs. It is still unknown whether training under more challenging DT conditions would result in long-term retention of skills for individuals with CI.
We used the MMSE in this study because it is a simple and widely used clinical test of general cognitive ability, with scores easily interpreted to describe the overall cognitive function of our participants. However, it is typically used as a screen for dementia and, as such, may not be useful at identifying specific CIs that may relate to DT ability. It has been reported that executive function and attention are distinct domains of cognitive function important for dual-tasking3,4; thus, more sophisticated measures of cognitive function that capture these domains may be useful in future studies.
For the individuals in our study with CI, we did not recruit on the basis of any specific medical diagnosis leading to their CI, but rather simply used the MMSE to describe their degree of CI. As such, our results can be generalized to older adults with CI of any etiology. However, specifying a medical diagnosis as the basis for their CI may have helped identify specific domains of cognitive function that were impaired in that portion of our sample, so that we could have examined how these specific domains, rather than general cognitive function, related to DT ability. Similarly, we did not collect data on medications taken by our subjects. Because medications can impact both mobility and cognition, this would have been useful information to collect, as it could have impacted DT ability.
We used fairly simple measures of motor function with the TUG and SSWS. These measures allowed us the ease of testing participants in their familiar environments, which was especially important for individuals in the lower cognitive ranges. The TUG and SSWS are also very applicable to a range of clinical environments. On the contrary, our examination of motor performance was limited to measures of time and speed. It is possible that more advanced methods of gait analysis, such as through the use of a portable gait analysis system, would have yielded more comprehensive findings.
In an effort to reduce burden on our participants, we allowed for one practice trial for the motor and cognitive STs but did not do the same for the DTs. However, the variability of DTC might have been reduced if we had allowed for a practice trial, particularly for the more difficult DT combinations (Figure 3). Future studies could consider allowing for practice trials of DTs, or having participants perform more than 1 repetition of each DT and using an average value in the analysis.
We found that DTC increased both as cognition declined and as task difficulty increased. Physical therapists should be aware that motor performance will worsen under DT conditions more so for older adults with CI, and particularly when more challenging combinations of tasks are used. As such, physical therapists may need to educate other caregivers about the impact DTs may have on the safety of patients with CI during mobility. On the contrary, if a physical therapist wants to assess a patient's DT ability, more complex combinations of tasks might be more informative, as excessively easy combinations of tasks may not produce much challenge to motor performance relative to ST performance. In fact, for patients with CI, our data suggest that physical therapists should not underestimate these patients' ability to engage in harder DTs, such as the TUG3 used in this study.
We found that a fair to moderate linear relationship exists between cognition and DTC, and the strength of this relationship is greater for more challenging tasks. We also found that all of our subjects, regardless of cognitive level, had the capacity to engage in DTs of varying levels of difficulty. These findings have implications for future research, as intensity is a parameter that should be considered in the design of DT training programs for older adults of all cognitive levels.
The authors thank the administration and staff at Hillcrest Health Systems for their interest in our study and assistance with recruitment; the clients and residents of Hillcrest Health System for their participation; the families of study participants for their interest and support; the School of Allied Health Professions of the University of Nebraska Medical Center for funding, and Robin High, MBA, MA, for assistance with statistical analysis.
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