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ORIGINAL ARTICLE
Year : 2021  |  Volume : 69  |  Issue : 4  |  Page : 883--888

The interactive effect of cognitive and physical dual task interventions on obstacle negotiation while walking in healthy young, and older, adults

Kitchana Kaewkaen1, Tulaporn Chueathaeo2, Siwanart Angart2, Sirikul Chomkan2, Surapong Uttama3, Wilawan Chaiut2, Ploypailin Namkorn1, Chatchada Sutalangka2, Pratchaya Kaewkaen4,  
1 Department of Physical Therapy, School of Health Science, Mae Fah Luang University, Chang Wat Chiang Rai; Research Center in Back, Neck, Other Joint Pain and Human Performance (BNOJPH) Khon Kaen University, Nai-Muang, Muang District, Khon Kaen, Thailand
2 Department of Physical Therapy, School of Health Science, Mae Fah Luang University, Chang Wat Chiang Rai, Thailand
3 School of Information Technology, Mae Fah Luang University, Chang Wat Chiang Rai, Thailand
4 College of Research Methodology and Cognitive Science, Burapha University, Tambon Saen Suk, Amphoe Mueang Chon Buri, Chang Wat Chon Buri, Thailand

Correspondence Address:
Dr. Pratchaya Kaewkaen
Department of Physical Therapy, School of Health Science, Mae Fah Luang University, Chang Wat Chiang Rai - 57100
Thailand

Abstract

Context: Dual task performance affects obstacle crossing ability in older adults. Previous studies suggest that cognitive dual tasking can lead to changes in obstacle crossing performance in older adults, but there is a lack of evidence to support changes in obstacle crossing performance due to the influence of motor dual tasking. Aims: To investigate the interaction of cognitive and motor tasks, on obstacle crossing performance, in healthy young and older adults. Settings and Design: This is a cross sectional comparative study, conducted at Mae Fah Luang University, Thailand. Methods and Material: Sixty-four participants performed an obstacle crossing task under three conditions during a 4-meter walk test. These included walking at their normal speed with an obstacle in the middle of the walkway, followed by 2 further order-randomized walking conditions comprising a cognitive and a motor dual tasking walking condition. The spatio-temporal gait variables and obstacle crossing kinematic variables were measured using a Kinect three-camera system. Statistical Analysis Used: The means for each variable, and for each condition, were analyzed using a mixed model analysis of variance (ANOVA) with walking conditions as covariant factors. Results: A significant main interaction effect was found in gait speed (P < 0.001), step length (P = 0.046) and cadence (P = 0.011), but there was only a significant between-group difference in step length during obstacle crossing, while performing a cognitive dual task (P = 0.008) and a motor dual task (P < 0.001). Conclusions: Older adults adopted a conservative strategy, and walked with a shorter step length, when stepping over an obstacle while performing a dual task.



How to cite this article:
Kaewkaen K, Chueathaeo T, Angart S, Chomkan S, Uttama S, Chaiut W, Namkorn P, Sutalangka C, Kaewkaen P. The interactive effect of cognitive and physical dual task interventions on obstacle negotiation while walking in healthy young, and older, adults.Neurol India 2021;69:883-888


How to cite this URL:
Kaewkaen K, Chueathaeo T, Angart S, Chomkan S, Uttama S, Chaiut W, Namkorn P, Sutalangka C, Kaewkaen P. The interactive effect of cognitive and physical dual task interventions on obstacle negotiation while walking in healthy young, and older, adults. Neurol India [serial online] 2021 [cited 2021 Dec 8 ];69:883-888
Available from: https://www.neurologyindia.com/text.asp?2021/69/4/883/325349


Full Text



Cognitive function is one of most important components of human postural control. Decision making and performance control are regulated by higher brain functions. There is strong evidence that in older adults, cognitive impairment is associated with increased risk of falls.[1] All human activities require minimum cognitive attention in order to perform each task autonomously, and the efficiency of this ability can be assessed by dual tasking tests. Dual task performance, such as performing numerical calculations while walking, can disrupt cognitive function, and result in impaired postural control in both young and older adults.[2] These phenomena can be explained by the theory that the brain cannot share its attentional resources to control two tasks at the same time, as there is a cognitive capacity limitation which occurs in the prefrontal cortex.[3] Thus, due to the ageing process, the changes in performance under dual task testing are associated with a potential risk of falling in older adults, suggesting the importance of cognitive attention on ambulatory safety in diverse environments.[4]

Previous studies have reported that tripping is the main cause of falling in older adults,[5] and report the prevalence of falls occurring outside the home.[6] This is because outdoor ambulation is complex and requires cognitive attention resources to rapidly adapt the gait parameters, by changes in postural control strategies, and to adapt gait characteristics in order to negotiate objects on the floor.[7] Begg et al., 2007 showed that older adults are found to have a reduced minimum foot clearance height which increases the risk of tripping.[8] Similarly, a previous systematic review also found that older adults have reduced internal hip and ankle moments while obstacle crossing, resulting in decreased minimum foot clearance.[9] In addition it has been shown that older adults have increased cognitive demands while performing a dual task while obstacle crossing during ambulation, which compromises the available attentional resources, thus resulting in increased risk of falling.[10] It has also been found that older adults frequently have significant kinematic asymmetries during obstacle crossing in dual task performance. Da Rocha et al., 2013, suggest that they also use additional compensatory kinematic adjustments after stepping over the obstacle while performing a dual task.[11]

Stepping over an obstacle is an important requirement for outdoor ambulatory tasks. Many factors affect obstacle crossing performance including walking speed, lower limb muscle strength, dynamic balance, and cognitive function.[12],[13] In addition, visual information is an important resource in order to plan foot placement before and after stepping over the obstacle, and could result in the need for increased visual attention to the obstacle in the elderly with impaired vision.[14]

Several studies of dual task walking while obstacle crossing have shown it is affected by both obstacle dimensions and spatio-temporal parameters.[15] This is supported by Soma et al. who reported toe clearance was influenced by cognitive dual tasking.[16] There are however 2 types of dual tasking, namely cognitive and motor. Each type is associated with a different brain mechanism that controls the postural task.[17] Thus, both types of dual tasking could disrupt brain control, but motor dual tasking also affects the trunk and pelvis and balance biomechanics while performing a task such as carrying a tray while walking.[18]

Ideally outdoor community ambulation, while performing a dual task, should be performed safely and autonomously. A previous study showed that the minimum toe clearance decreases in older adults while performing a dual task, thus indicating a risk of tripping, especially during cognitive dual tasking.[16] Plummer et al., 2012 reported the effect of motor dual tasking on timed obstacle crossing in healthy older adults.[19] Based on available knowledge, there is limited evidence to support the effect of motor dual tasking on obstacle crossing kinematics. There is therefore a need to further investigate the interacting effect of both cognitive and motor dual tasking on obstacle crossing performance. This will inform fall prevention programs in older adults.

 Materials and Methods



Participants

The interactive effect of cognitive and physical dual task interventions on obstacle negotiation while walking was investigated in healthy young, and older, adults. Thirty-two young adults aged between 20 and 30 years (mean 20.50 ± 0.72 years, males n = 4, females n = 28), and 32 healthy older adults aged between 65 and 73 years (mean 68.34 ± 2.96 years, males n = 7, females n = 25), recruited from Nanglae district, Chiang Rai, Thailand, participated in this study. G*power 3.0.10 software was used to calculate an ANOVA with repeated measures, within subjects for sample size estimation. The effect size was based on a previous study of trail foot clearance in dual tasking.[16] All participants were able to walk independently for at least 8 meters.

Participants were excluded if they scored less than 23 in the Thai Mental State Examination (TMSE), if they could not numerically calculate backwards in 3's, if they scored more than 23 in the Thai Falls Efficacy Scale-International (Thai FES-I), if they had any problems with dynamic balance with a Timed Up and Go test (TUG) of more than 12 seconds, any demonstrated lower limb muscle weakness in that they were unable to perform the 5 Timed Sit to Stand Test (FTSST) in less than12 seconds, or problems with the vestibular-ocular reflex as shown by a positive head impulse test. Patients were also excluded with any past medical history which may have affected their ambulation such as Stroke, Parkinson's disease, Vestibular disease, Cerebellar disease or Rheumatoid arthritis. In addition, participants were excluded who had pain in any part of the body self-rated at more than 5 from 10 on a visual-analog scale. Participants who had consumed alcohol within 24 hours prior to testing were also excluded.

The study protocol was approved by Mae Fah Luang University Ethics Committee on December 9, 2016. All participants signed an informed consent form before participating in this study.

Procedure

A cross sectional comparative study was conducted at Mae Fah Luang University, Thailand. The obstacle crossing performance of participants who met with the inclusion criteria were asked to perform a simple walking test under three conditions. First, they were asked to walk in a straight line, and at their preferred normal walking speed, along an 8-meter walkway, in which a wooden obstacle had been placed half way along at 4 m. The size of the obstacle was based on a previous study[16] (depth × width × height = 0.15 m × 0.8 m × 0.2 m). Chou et al., 1998 reported that an obstacle height as low as only 0.02 meters could affect trail toe clearance.[20] This was followed by, two further walking tests along the same walkway. These consisted of a motor dual task walking condition and cognitive dual task walking condition. The order of these two tests was determined by a random lottery system. Participants were not allowed to practice the obstacle negotiation before testing. All participants were rested for 2 minutes between testing conditions to prevent fatigue effects.

Normal walking speed condition: The participants walked at their preferred walking speed, without shoes. Participants were videoed over the central 4 meters of the walkway by three Kinect cameras (50 Hz), and the obstacle crossing kinematics, and spatio-temporal parameters, were analyzed using bespoke MFU gait analysis software (the 4 meter walk test) The 4 meter walk test is a commonly used tool for analyzing gait parameters in older adults.[21] Furthermore, Kinect cameras have been shown to be a valid and reliable tool in the assessment of gait parameters and kinematic variables.[22]

Motor dual task walking condition: The participants again walked 8 meters at their preferred walking speed, however, this time they were required to carry a tray full of water. They were instructed to pay equal attention to both the motor task and walking task, with instructions to “please walk at your preferred speed during obstacle crossing while carrying a tray.”

Cognitive dual task walking condition: The participants again walked at their preferred walking speed. They were also instructed to verbally count backwards in threes from a random number allocated from between 300 and 500. In addition, to avoid prioritization in any task, they were instructed to pay equal attention to both the cognitive task and walking task, with instructions to “please walk at your preferred speed during obstacle crossing while counting backward in threes from the given number.”

The obstacle crossing parameters in this study were the same as in a previous study.[16] Self-adhesive red markers were attached to the big toe of each foot. One Kinect camera recorded the obstacle crossing parameters, including the horizontal distance between the toe of the trail limb and the front of the obstacle (Toe-obstacle distance), the horizontal distance between heel of the lead limb and the back of the obstacle (Heel-obstacle distance), the vertical distance between the tip of big toe of the lead limb and the obstacle, when it passed the foremost edge of the obstacle (Lead toe clearance), and the vertical distance between the tip of big toe of trail limb and the obstacle when it passed the foremost edge of the obstacle (Trail toe clearance) were also recorded. Two more Kinect cameras simultaneously recorded spatio-temporal parameters including gait speed, step length, and cadence.

Statistical analysis

A Shapiro-Wilk test was applied to determine the normal distribution of the experimental data. Descriptive statistics were obtained for all demographic data and variables. An Independent t-test was used to compare the difference between groups for education, BMI, TMSE, TUG, FTST, and FES data. A Chi-square was used to compare the gender data.

A mixed-design ANOVA with “age” and “gait” as factors was used to analyze the obstacle crossing parameters and spatio-temporal parameters. Independent t-tests with Bonferroni corrections were then applied to examine the effects of age and gait interaction. A partial eta square (n2p) was used to estimate the effect size of the interaction. An alpha level for the statistical significance was set at 0.05. All data were analyzed using SPSS 20.0 statistical software.

 Results



Baseline characteristics

There were no differences in baseline characteristics between groups as shown in [Table 1]. There was no significant difference in the gender split between groups, or in the BMI, but the comparative analysis did find a difference between groups in education (P < 0.001), Timed Up and Go test (P < 0.001) and the Five Timed Sit to Stand Test (P = 0.018).{Table 1}

Dual task effect on the obstacle crossing parameters while obstacle crossing

The results concerning the obstacle crossing parameters are shown in [Table 2]. No main effect for age x gait interaction were found for any variable, but age factors and gait factors were both found to effect the obstacle crossing parameters; a significant effect was found between trail foot clearance and age {F (1,33) = 6.293, P = 0.015, n2p = 0.092}, and between lead foot clearance and age {F (1,33) = 40.425, P < 0.001, n2p = 0.395}. Significant effects were also found between toe obstacle distance and gait {F (2,34) = 16.194, P < 0.001, n2p = 0.207}, heel obstacle distance and age {F (1,33) = 57.062, P < 0.001, n2p = 0.479} and heel obstacle distance and gait {F (2,34) = 14.278, P < 0.001, n2p = 0.187)}.{Table 2}

Dual tasking effect on the spatio-temporal parameters while obstacle crossing

On examination of the spatio-temporal parameters, a main effect was found for age x gait interaction for all variables; gait speed {F (2,34) = 5.690, P < 0.001, n2p = 0.084}, step length {F (2,34) = 3.152, P = 0.046, n2p = 0.048}, and cadence {F (2,34) = 4.707, P = 0.011, n2p = 0.071}. Further, the independent t-tests, with Bonferroni corrections, found a significantly decreased step length distance in healthy older adults compared to young adults for both the cognitive dual tasking walking condition (mean difference = 0.048 m, P = 0.008), and motor (mean difference = 0.089m, P < 0.001), dual task walking conditions. In addition, a significantly slower gait speed was found in healthy older adults compared to young adults, for the normal walking condition (mean difference = 0.190 m/s, P < 0.001), and cognitive (mean difference = 0.106 m/s, P = 0.002) and motor (mean difference = 0.199 m/s, P < 0.001) dual task conditions, but no significant difference was found between groups in cadence variables for all walking conditions.

The influence of age and gait factors on the spatio-temporal parameters were also investigated; and a significant effect of gait speed on gait {F (2,34) = 58.201, P < 0.001, n2p = 0.484} and age {F (1,33) = 56.370, P < 0.001, n2p = 0.476} was found. A significant effect was also found of step length on gait {F (2,34) = 4.293, P = 0.016, n2p = 0.065} and age {F (1,33) = 13.626, P < 0.001, n2p = 0.180}. In addition, a significant effect of cadence on gait was found {F (2,34) = 7.057, P < 0.001, n2p = 0.102}.

 Discussion



The purpose of this study was to investigate the interacting effect of dual tasking and obstacle crossing performance in young adults and healthy older adults. When considering the baseline characteristics, there was no difference between groups although there were statistically significant differences between groups in the number of years in full time education, Timed Up and Go test and the Five Timed Sit to Stand test. These differences, however, did not affect the experimental outcome for although older adults had fewer years in full time education, all of the participants could competently count backwards in threes according to the exclusion criteria. In addition, although the older adults took longer in the Timed Up and Go test, and the Five Timed Sit to Stand Test, than young adults, the difference was not considered to be clinically important (Timed Up and Go test ≥12 seconds and Five Timed Sit to Stand Test ≥12 seconds indicating risk of falling).[23]

The main finding of this study demonstrated that for both cognitive and motor dual tasking, while obstacle crossing, healthy older adults adapted their walking performance with a shortened step length. This may increase the risk of obstacle contact because this causes foot placement to be closer to the obstacle before, and after, crossing.[14] Indeed this study did find that older adults placed their feet closer to the obstacle, as demonstrated by a reduced toe obstacle distance and heel obstacle distance, in both motor and cognitive dual task conditions, than young adults although this was not found to be a significant difference. This is similar to the findings of Chen et al. 1994 who reported that older adults employed a short-step strategy while obstacle crossing because it enables a shorter response time.[15] Espy et al. 2010 also state that decreasing the step length could enhance the postural stability while walking slowly.[24] As a result of this adaptation, older adults may employ increased caution while performing a dual task, through employing conservative postural strategies, and foot placement, while negotiating the obstacle.

Dual tasking while walking across the obstacle may have also affected the older adults performance more than young adults because the older adults required more attention during obstacle crossing while performing a secondary task.[10] In addition, motor dual tasking, such as walking while holding a tray or water, may affect the exproprioception which is the capacity to modify the visual information of their foot position relative to the obstacle.[14] Since it is necessary to use visual feedback to enhance coordination during obstacle avoidance, carrying an object may have compromised the view of the foot position relative to the obstacle, thus reducing the visuomotor information for determination of optimum trail foot placement.[14]

The older adults walked more slowly than young adults in all walking conditions. A previous study reported that walking more slowly is associated with instability and falls.[24] Chen et al., 1991 found that older adults employed a conservative strategy with a slower obstacle crossing speed, shorter obstacle-heel distance, and shorter step length.[25] This study did not however, compare walking speed between groups performing either cognitive or motor dual tasking, which would affect normal kinematics. Adaptations to gait and posture while obstacle crossing, for all conditions, may however all be a function of the normal ageing process, and the decline in optimal functioning in older adults; including changes to the musculoskeletal system, cardio-respiratory system and nervous system. These systems affect postural stability and result in impaired dynamic balance while obstacle crossing in older adults.[5]

The influence of age and gait factors were however present for both the obstacle parameters, and the spatio-temporal parameters, although the main interaction was found only in the spatio-temporal parameters. Thus, age and gait factors affect both the obstacle crossing performance of both young adults and healthy older adults. The results revealed that the age factor influenced trail foot clearance, lead foot clearance, heel-obstacle distance, gait speed and step length, while the gait factor influenced toe-obstacle distance, heel-obstacle distance, gait speed, step length and cadence. Trail foot clearance was a main parameter of interest in this study; however, no main interaction effect was found. These results demonstrate a strong consistency with Soma et al., 2010 who also found that trail foot clearance was not influenced by a dual task.[16] There was only an age factor effect on trail foot clearance, but there was decreased heel obstacle distance in older adults. This indicates that older adults used a conservative strategy during obstacle crossing while performing a dual task.

Limitation of this study

The size of the obstacle was the same for all walking conditions, thus, the effect of different obstacle heights and widths is unknown while performing a motor dual task. Future studies should investigate the effect of obstacle dimensions as this would be more representative of the real-life environment.

 Conclusion



Older adults walked with shorter step lengths when stepping over an obstacle while performing both motor and cognitive dual tasks. This finding should inform fall prevention programs.

Acknowledgements

This project was supported by Mae Fah Luang University research grant 2016. The authors would like to thank Dr. Su Stewart, from England, in proofreading the article.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Mae Fah Luang University research grant 2016.

Conflicts of interest

There are no conflicts of interest.

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