Many different net-step designs are possible and were employed during the study, each with specific instructions regarding the placement and use of the participants' feet (left vs right), number of steps, and grid order. Figure 2 shows a step design, One Two Three step, used on the third day of the 8-week NSE program. For this step design, participants had to perform 3 steps and 1 hand clap per square, as indicated by the feet and circles, respectively (see Video, Supplemental Digital Content 2, http://links.lww.com/JGPT/A4, which demonstrates the One Two Three step design). Illustrations of these step designs (Figure 2) were provided only to instructors, who demonstrated the step designs to the participants. All participants were required to repeat the step designs in exactly the same way as their instructors.
Every session of the 8-week NSE program consisted of 3 stages. The first was the warm-up step, conducted at the beginning of each session to assess the participants' physical condition. The second was the trial step, where participants learned the new step design to be performed during that session. The participants had to memorize each step design on the basis of the instructor's demonstration. After the demonstration, the participants practiced each step design twice. The instructors tried to encourage the participants, never mentioning their mistakes. Most participants showed improvement during the trial step, even if they made a mistake or tread on the net in the first trial. The third stage was the recreation step. The participants formed a line and step in the same rhythm while singing a children's song. They had to watch their steps and move in synchrony with the other participants while singing the song. The total time for actual walking by each participant was approximately 30 minutes in each session.
Throughout the 8-week NSE program, the difficulty of the step designs and the number of steps required in each session were gradually increased. Participants walked 216 steps per session during the first 4 weeks of the program and 240 steps per session from the fifth to eighth weeks (see Appendix, Supplemental Digital Content 1, http://links.lww.com/JGPT/A3, which shows the schedule of step designs used in the program).
Cognitive function, gait and balance function, and QOL assessments were performed at baseline (before the intervention period), and after the 8-week intervention period. To prevent potential bias and ensure that the study was single-blind, the staff responsible for data collection were blinded to the information about the groups to which the participants belonged.
Cognitive assessment was conducted using 2 touch panel computer screen devices: a Touch-M system and a Touch Panel-Type Dementia Assessment Scale (TDAS). The Timed Up and Go (TUG) test was used to measure gait function and balance (propensity to fall). The Medical Outcome Study Short Form-8 (SF-8) was used to assess changes in the participants' QOL.
Assessment of Cognitive Function
To reduce error or dispersion of subjective judgments, cognitive function in this study was assessed using 2 computer-based assessments: Touch-M and TDAS.
The Touch-M system evaluates visuospatial function in the lateral prefrontal area to assess cognitive function and diagnose early stages of Alzheimer disease. Hatakeyama et al13 reported that this system has 100% specificity and 75.9% sensitivity in the diagnosis of Alzheimer disease. The Touch-M system also shows a significant correlation with the Mini Mental State Examination (r = 0.53; P < .001).13
The Touch-M system runs on the Microsoft Windows Operation system and a touch-panel-type desktop PC. It employs single-color stimulation in a visuospatial task. Blue color signals are presented in a random order within the cells on the touch panel display, which is divided into 2, 3, 4, 5, or 6 cells, either vertically or horizontally. Subjects are instructed to memorize the sequence and location of signals in a series and reproduce the sequence by touching the cells on the display. The participants were scored on a 100-point scale, with 100 being the best possible score.
The TDAS is a modification of the Alzheimer's Disease Assessment Scale14 and its subscale, the Alzheimer's Disease Assessment Scale-Cognitive subscale,15 which is widely used to measure decline in cognitive function. The TDAS also runs on the Microsoft Windows Operation system and touch-panel-type desktop PC and shows a high correlation with the Alzheimer's Disease Assessment Scale-Cognitive subscale (r = 0.69; P < .001).16 The TDAS measures the level of cognitive decline using questions that test word recognition, one's ability to follow commands, visuospatial perception, accuracy of the order of a process, naming fingers, money calculations, orientation, object recognition, and clock time recognition. The accuracy of the order of a process examines whether the subject can recognize the process of writing a letter through to posting it. Naming finger examines whether the subject can remember the name of the finger correctly. Orientation examines the subject's identification of the year, month, day, and day of the week. In the TDAS, decreasing scores indicate improvements in cognitive function, with zero as the best possible score.
Balance and Propensity to Fall
The TUG test was used to assess the participants' gait and balance function at baseline and 8-week follow-up.17 The relative reliability of the TUG test between test sessions reached 0.92 (95% confidence interval, 0.85-0.95).18 The TUG test also shows a high correlation with the Berg Balance Scale (r = −0.81), gait speed (r = −0.61), and Barthel index of activities of daily living (r = −0.78)19.
We assessed the participants' QOL using composite scores from the SF-8 health survey. This form has a population norm of 50 points, with lower scores indicating worsening QOL. In this study, physical component summary scores (PCS) and mental component summary scores (MCS) were used. The SF-8 evaluates changes in subjective health perception and is useful for estimating the effectiveness of medical intervention from the subject's viewpoint.20 We focused on only 2 scores from this survey, the PCS and MCS, to evaluate changes in participants' QOL during the experimental period. The relative reliability of the PCS and MCS is 0.77 and 0.73, respectively.20 The relative validity of the PCS and MCS is 0.82 (P < .001) and 0.03, respectively.20
The data were analyzed using SPSS 21.0 for Windows. For baseline comparison between the NSE and control groups, the Pearson method was used to analyze categorical data (sex). For normally distributed variables, t tests were used to analyze basic characteristics between the 2 groups.
The repeated-measures procedure was used in an analysis of covariance (ANCOVA). The 2 time points (baseline and 8-week) were treated as a within-participant factor (effect over time). The difference between the NSE and control groups was treated as a between-participant factor. Covariates, such as age and sex, were included in the multivariate model. All statistical tests were 2-sided, and P ≤ .05 was considered statistically significant.
Participants' Characteristics at Baseline
Table 1 shows the participants' baseline characteristics. The mean age did not differ (t test, P = .22) between the NSE group (76.8 ± 4.4 years) and the control group (75.5 ± 3.7 years). The sex ratios of the 2 groups showed a difference. Thirteen (43.3%) participants in the NSE group and 20 (66.7%) participants in the control group were female, but this difference was not significant (P = .07).
Effect of the NSE on Gait and Cognitive Performance
Table 2 shows the mean difference from the baseline in the TUG test, cognitive test scores, and QOL over 8 weeks by group. The results from the repeated-measures ANCOVA showed a significant effect for the within-participant interaction in the TUG test (P < .001). The time in the TUG test significantly improved (by 0.98 second, 11.5%; P < .001) in the NSE group relative to the baseline assessment. The TUG times of the control group significantly deteriorated (by 0.4 second, 0.05%; P < .02) relative to the baseline.
The mean difference from baseline in the Touch-M cognitive test score was 4.9 times higher in the NSE group than in the control group (ANCOVA, P = .04). The total score of the Touch-M significantly improved by 5.4 points (6.8%; P = .04) from the baseline in the NSE group.
Because the participants scored almost full marks at the baseline assessment on 7 of the 9 items of the TDAS, significant differences between participants and within participants were not observed in these items. Naming fingers improved significantly in the control group. Accuracy of the order of a process showed a significant difference between participants.
Neither group experienced a significant change in QOL, indicating that the participants' physical and mental health condition remained constant during the course of the program.
The present study results demonstrate that NSE may have a positive influence on gait and cognitive performance in older adults. In our study, the cognitive performance of participants in the NSE group improved by more than 4.9-fold relative to that of the control group participants in terms of the mean difference from baseline in the total Touch-M score. The gait performance of participants in the NSE group showed a significant improvement from the baseline in the time required for the TUG test. Although this study has limitations, these results suggest that the NSE program has potential applications for maintaining or improving gait and cognitive function in the older population. In contrast, significant deterioration of gait performance was observed in the control group. Although the degree of this deterioration (0.05%) was not clinically significant, the decline seemed to result from the inactivity of the control group relative to the NSE group, and it reflected the natural transformation of gait and physical performance in older populations.21
Cognitive performance improved significantly after 8 weeks of NSE. This finding is consistent with previous research, which suggests that physical activity can improve cognitive function in older adults.2,3,22 The NSE group also showed improvement in gait and balance function. These results are consistent with research suggesting that cognitive function is an indicator of gait and balance function.12,23 Gait is no longer considered to be merely an automated motor activity; rather, it is understood to involve a higher level of cognitive function.24 Accordingly, studies that have reported improvements in gait in older adults after a dual-task intervention also observed improvements in cognitive function.9,12 Multifaceted neuropsychological influences on walking and interactions with mobility control are increasingly reported in studies of dual-task exercise25 and emphasize the link between cognitive and motor functions.26,27
A novel finding of this study is that by using dual-task NSE, it is possible to reduce the duration and frequency of physical activity required to particularly improve the cognitive and gait performance for older adults. To promote cardiovascular function and maintain health, older adults are recommended to participate in moderate-intensity aerobic activity for at least 30 minutes on 5 days of the week, or vigorous aerobic activity for at least 20 minutes on 3 days of the week.4,5 The dual-task NSE, which primarily focuses on the cognitive health, offers an easier type of physical activity that employs complex cognitive tasks requiring attention and concentration. For example, when participants try to avoid stepping on a net, they must keep their attention on both the net and their feet. They must also remember the step design correctly and reproduce it exactly. They have to simultaneously concentrate on clapping their hands and completing the step design. These cognitive tasks indicate NSE as a new type of physical exercise. In addition, because the step design is changed every time, NSE enables fresh cognitive tasks to be performed each time. Although many cognitive tasks have been attempted in dual-task studies previously, most of them, for example, subtracting 7s10 or talking while walking,28 seemed easier than NSE and monotonous. We believe that NSE requires a higher level of coordination, and because the step design is changed every time, participants are less likely to become bored with the exercise.
In addition to these components of cognitive tasks, NSE offers the benefits associated with other dual-task exercises. For example, Erickson et al29 observed a correlation between the activation of brain regions involved in dual-task performance and improved performance on the task. Bherer et al30 suggested that dual-task skills can be substantially improved in older adults and that cognitive plasticity in attention control is still possible in old age. The brain regions involved in attention control and task coordination during dual-task processing have been investigated using functional magnetic resonance imaging and positron emission tomography. These studies demonstrate the possible physiological basis underlying improvements in cognitive function by dual-task performance. In addition, Low et al31 proposed that the dorsolateral prefrontal cortex is important for executive function and dual-task performance. Specifically, they postulated that different task processing streams are represented in different processing units within this region, with attention control being implemented through the differential activation of the units associated with each processing stream. According to this view, they suggested that dual-task conditions involve the selective activation and inhibition of different units within the dorsolateral prefrontal cortex.31
Possible evidence for Low's hypothesis may be observed in the NSE participants. When the participants were practicing NSE, they would miss the hand clapping if they were concentrating on stepping over the net. However, if the participants were concentrating on hand clapping, their feet would stop involuntarily and they would step incorrectly. Consequently, the NSE participants had to simultaneously pay attention to hand clapping, stepping in the right square, and watching the net to perform the exercise correctly. Dux et al32 found that improvement in dual-task performance is achieved by increasing the speed of information processing in the brain region, thereby allowing multiple tasks to be processed in rapid succession. The improved cognitive function observed here is likely a result of these various dual-task influences on the brain.
Our results demonstrate that a dual-task NSE is able to improve gait and cognitive performance in a group of apparently healthy, community-dwelling, older adults. The frequency and intensity (ie, once in a week and <300 steps per session) of NSE may make physical activity easier for older adults. Accordingly, NSE offers an option for the older adults who may want to participate in physical activity to gain improvement of cognitive and gait function.
This study has some limitations. First, we focused on the effects of NSE on gait and cognitive function but did not evaluate carryover effects. It would be helpful to know whether the beneficial effects of NSE persist by conducting several follow-up assessments. In addition, a randomized control trial with a double-blind study design was not possible, as it was necessary for the participants to know whether they belonged to the intervention or control group. Further research is necessary to compare the dual-task NSE group and a single-task, walking group.
Another limitation of the study is that the physical activity/inactivity and social activity of the participants were not controlled or monitored. In addition, NSE is a group therapy during which the participants can talk to and encourage each other. This social interaction may have psychological influences on the participants. Thus, further research is needed to evaluate both the influence of physical activities in daily life outside of the intervention and psychological influences in participants who perform NSE.
This study shows that dual-task NSE is capable of improving cognitive and gait performance in healthy older adults. Our results indicate that NSE offers an option for a large segment of the older population who need an easier way to maintain their cognitive health and gait function.
We thank the dedicated staff at the nonprofit organization for community health in Hokkaido and the volunteers who shared their lives and experiences with us.
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dementia prevention; executive function; older adults; physical exercise
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Copyright © 2015 the Section on Geriatrics of the American Physical Therapy Association