Journal of Motor Behavior
ISSN: 0022-2895 (Print) 1940-1027 (Online) Journal homepage: http://www.tandfonline.com/loi/vjmb20
Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment Sheila de Melo Borges, Márcia Radanovic & Orestes Vicente Forlenza To cite this article: Sheila de Melo Borges, Márcia Radanovic & Orestes Vicente Forlenza (2015) Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment, Journal of Motor Behavior, 47:5, 378-385, DOI: 10.1080/00222895.2014.998331 To link to this article: https://doi.org/10.1080/00222895.2014.998331
Published online: 22 Jan 2015.
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Date: 10 December 2017, At: 18:02
Journal of Motor Behavior, Vol. 47, No. 5, 2015 Copyright © Taylor & Francis Group, LLC
RESEARCH ARTICLE
Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment rcia Radanovic, Orestes Vicente Forlenza Sheila de Melo Borges, Ma
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~o Paulo, Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, Faculty of Medicine, University of Sa Brazil. ABSTRACT. Motor disorders may occur in mild cognitive impairment (MCI) and at early stages of Alzheimer’s disease (AD), particularly under divided attention conditions. We examined functional mobility in 104 older adults (42 with MCI, 26 with mild AD, and 36 cognitively healthy) using the Timed Up and Go test (TUG) under 4 experimental conditions: TUG single task, TUG plus a cognitive task, TUG plus a manual task, and TUG plus a cognitive and a manual task. Statistically significant differences in mean time of execution were found in all four experimental conditions when comparing MCI and controls (p < .001), and when comparing MCI and AD patients (p < .05). Receiver-operating characteristic curve analyses showed that all four testing conditions could differentiate the three groups (area under the curve > .8, p < .001 for MCI vs. controls; area under the curve > .7, p < .001 for MCI vs. AD). The authors conclude that functional motor deficits occurring in MCI can be assessed by the TUG test, in single or dual task modality.
Verghese et al., 2007; Wait et al., 2005). According to Camicioli and Majumdar (2010) and Liu-Ambrose et al. (2010), older adults with mild cognitive impairment (MCI) are also at an increased risk for mobility decline and falls (Borges, Radanovic, & Forlenza, 2014; Puisieux, Pardessus, & Bombois, 2005). Therefore, evaluation of changes in gait may be useful for preventing falls, assessing functional decline, and detecting the early stages of cognitive decline (Gillain et al., 2009). Mobility in daily life often requires walking while simultaneously performing cognitive or motor tasks, such as talking with a friend or carrying a cup of coffee (Kelly, Eusterbrock, & Schmway-Cook, 2012). Thus, gait abnormalities may be magnified by divided attention tasks, also known as dual tasks (Hauer et al., 2002; Shumway-Cook, Woollacott, Kerns, & Baldwin, 1997). There is evidence that older people who demonstrate a slower gait during a dual task are more likely to develop cognitive impairment (Camicioli, Howieson, Oken, Sexton, & Kaye, 1998). However, there is no consensus as to whether patients with MCI exhibit similar performance to patients with AD dementia, or whether the evaluation of mobility during a divided attention task can differentiate older adults with MCI from those with AD (Muir et al., 2012). The timed “up and go” (TUG) test is widely utilized by professionals in gerontology to assess functional mobility in an ecological manner, as it simultaneously evaluates assesses gait, dynamic balance, and functional mobility. It is a useful tool for rehabilitation professionals to evaluate the risk of falls in older people, as well as motor deficits in MCI subjects (Ayan, Cancela, Gutierrez, & Prieto, 2013; Donoghue et al., 2012; Gillain et al., 2009; Herman, Giladi, & Hausdorff, 2011; McGough et al., 2011; Podsiadlo & Richardson, 1991; Shumway-Cook, Brauer & Woollacott, 2000). Impairment in this test has been associated with the occurrence of falls in elderly populations (Shumway-Cook, Brauer, & Woollacott, 2000) and early motor intervention should be prioritized in this population in order to prevent falls and ensure independence and autonomy. The aim of the present study was to evaluate whether
Keywords: functional mobility, divided attention task, cognitive impairment
F
unctional mobility, particularly gait, depends on several systems for the maintenance of postural stability. Cognitive functions (including executive function and attention) are important in the regulation of functional mobility (Montero-Odasso et al., 2009). Motor changes are associated with senescence and are more pronounced in the presence of cognitive decline (Hauer, Marburger, & Oster, 2002). Cognitive decline is the main clinical marker of dementia, and motor disorders are most commonly described at advanced stages of Alzheimer’s disease (AD; Beauchet et al., 2008). Over the last decade, several studies (Aggarwal, Wilson, Beck, Bienas, & Bennett, 2006; Beauchet et al., 2008; Scarmeas et al., 2005; Verghese, Wang, Lipton, Holtzer, & Wue, 2007; Wait et al., 2005) have shown that gait abnormalities may indeed precede the diagnosis of cognitive decline. This indicates that a deficiency in cortical control of gait, in addition to certain motor deficits (e.g., postural control and muscle strength), may be observed at early stages of AD and other dementias. Boyle, Buchman, Wilson, Leurgans, and Bennett (2010) suggested that measures of physical frailty, such as walking speed and grip strength, may facilitate the identification of individuals prone to developing cognitive dysfunction. Many other studies have indicated that decreased gait speed may accompany incipient cognitive decline in elderly populations (Aggarwal et al., 2006; Beauchet et al., 2008; Buchman, Wilson, Boyle, Bienas, & Bennett, 2007; Gillain et al., 2009;
Correspondence address: Sheila de Melo Borges, Laboratory of Neuroscience (LIM 27), Department and Institute of Psychiatry, Faculty of Medicine, University of S~ ao Paulo, Rua Dr. Ovıdio Pires de Campos 785, 05403–010, S~ ao Paulo, SP, Brazil. e-mail: [email protected] 378
Functional Mobility in a Divided Attention Task in the Elderly
functional mobility with or without divided attention is a useful test in differentiating MCI patients from cognitively healthy elderly controls and mild AD patients. Our hypothesis was that the examined groups would differ in functional mobility, particularly when performing divided attention tasks, and that the difference would be most pronounced when a cognitive task was associated with a basic motor task.
Method
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Participants Participants were recruited from a cohort of older adults with varying degrees of cognitive impairment, ranging from normal cognition to mild–moderate dementia, as part of an ongoing study on cognitive aging that has been conducted since 2002 in the memory clinic of the Institute of Psychiatry, University of S~ao Paulo. All participants or their representatives signed an informed consent prior to the enrollment in this study, which was approved by the local Ethics Committee. One hundred and four individuals between 60 and 88 years old, of both genders, with a minimum of four years of schooling were included in this study. Cognition was assessed using the Mini-Mental State Examination (MMSE; Brucki, Nitrini, Caramelli, Bertolucci, & Okamoto, 2003; Folstein, Folstein, & McHugh, 1975), Short Cognitive Test (SKT; Erzigkeit, 1991; Flaks et al., 2006), Executive Interview – Exit 25 (Matioli & Caramelli, 2010; Royal, Mahurin, & Gray, 1992), and verbal fluency, animals category (Isaacs & Kennie, 1973). Clinical diagnoses were established at consensus meetings taking into account all clinical and available laboratory information gathered by a multidisciplinary team including physicians (psychiatrists, a geriatrician, and a neurologist), neuropsychologists, physical therapists, speech therapists, occupational therapists, and gerontologists. Participants were rated according to the Brazilian version of the Clinical Dementia Rating Scale (CDR; Maia et al., 2006) and then classified into three groups: mild AD (CDR D 1) according to the NINCS-ADRDA criteria (McKhan et al., 1984; n D 26), MCI (CDR D 0.5; according to Petersen et al., 2001; n D 42); or controls (CDR D 0; i.e., no evidence of cognitive or functional impairment; n D 36). Subjects with symptomatic orthopaedic conditions (e.g., acute or chronic pain in the lower limbs, recent surgery on the lower limbs) or other neurological disorders (e.g., stroke, Parkinson’s disease, or other dementias) that could impair mobility were excluded from the study. Well-controlled clinical conditions (e.g., hypertension, diabetes, hypothyroidism) or visual or hearing impairment corrected by prosthesis were not regarded as exclusion criteria provided that their manifestations did not interfere with motor or cognitive function. 2015, Vol. 47, No. 5
Procedures The TUG test was administered to all participants in four different ways: (a) TUG single task (performance of the TUG test alone), (b) TUG cognitive (TUG test combined with a verbal fluency task, animal category), (c) TUG manual (performing the TUG test while carrying a full cup of water), and (d) triple TUG test (TUG test in association with both the cognitive and manual task; i.e., performing the verbal fluency test while carrying a full cup of water). The sequence of administration of the four TUG tests was randomized according to Shumway-Cook et al. (2000). In this study, we used a standard manual task in combination with the TUG test (“holding a full cup of water”; Pettersson, Olsson, & Wahlund, 2005; Shumway-Cook, Brauer, & Woollacott, 2000). For the cognitive task, the most commonly used are counting backwards or the verbal fluency task. We used the verbal fluency task, animal category, as it is a widely used test that requires attention and executive function (Montero-Odasso, Muir, & Speechley, 2012). In accordance with Podsiadlo and Richardson (1991), a demonstration of how the test should be executed was performed by the current authors and all questions raised by the subjects were answered before starting the test. After this demonstration, participants were instructed to stand up from a chair, walk 3 m at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again to ensure that they were able to perform the task. For the manual task (holding a cup full of water), subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will be holding this cup of water.
For the cognitive task (animal fluency), subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will do it while naming as many animals as you can remember.
For the triple task (manual plus cognitive task) subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will do it as you hold this cup of water and name as many animals as you can remember. 379
S. de Melo Borges, M. Radanovic, & O. V. Forlenza
No physical assistance was allowed during the performance of the tasks. The physical therapist stood next to the chair and accompanied the participant when required for safety reasons, such as risk of falling. During the performance of the tasks, no additional verbal cues (e.g., “turn around” or “sit down”) were provided.
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Statistical Analysis One-way analysis of variance (ANOVA) was used to compare means for demographic data and cognitive assessment scores respecting Gaussian distribution (age and scores on verbal fluency). The Kruskal-Wallis test was used to compare means for demographic data and cognitive assessment scores that did not respect Gaussian distribution (schooling and scores on GDS-15, MMSE, SKT, and Exit25). Pearson’s chi-square test was used to compare categorical data (gender) between groups. Bonferroni post hoc correction was used to perform pairwise comparisons. Two-way repeated measures ANOVA was used to compare the mean time of execution (in seconds) in the four modalities of the TUG test between test groups. The Huynh-Feldt correction was applied to overcome violation of sphericity found in the data covariance matrix. Tukey HSD post hoc correction was used to perform pairwise comparisons. Spearman’s correlation (r) was used to evaluate a possible relationship between scores on verbal fluency (as performed in the initial cognitive assessment) and performance in TUG 1–4. The effect size of the scores obtained in each TUG modality was determined by multivariate global linear model. Receiver-operating characteristic (ROC) curve analyses were employed to identify the cutoff scores in each TUG test that best discriminated MCI versus Control and MCI versus AD. For each variable, the SPSS program (version 20.0) provided a list of cutoff points with a value of sensitivity and specificity (which was later calculated by 1 [specificity]). We considered as the best cutoff scores those yielding the highest values for sensitivity and specificity. Results Table 1 displays the demographic and cognitive characteristics of the sample. No significant differences were observed between groups for age and gender. Patients in the AD group were less educated. As expected, the AD group performed worse than MCI and control groups in all cognitive tests (MMSE, SKT, Exit 25, and verbal fluency). The MCI group exhibited intermediate scores when compared to controls and AD patients. All participants were able to perform all four TUG modalities. The three groups differed with respect to the mean time required to complete each task (Table 2). The MCI group performed worse than the control group, yet better than the AD group in all four TUG tests, with higher 380
effect size associated with the cognitive task (TUG 2 and 4; p < .001). Spearman’s correlation showed a mild negative correlation between the verbal fluency tests in TUG 2 (r D –.432; p < .001) and TUG 4 (r D –.422; p < .001) in the AD group only (data not shown). The two-way repeated measures ANOVA with HuynhFeldt correction revealed significant differences in the mean of time of execution between the three groups for all TUG modalities: TUG 1 vs. TUG 2, F(2,101) D 15.580, p < .001; TUG 1 vs. TUG 3, F(2,101) D 7.638, p D .001; TUG 1 vs. TUG 4, F(2,101) D 22.204, p < .001; TUG 2 vs. TUG 3, F(2,101) D 12.432, p < .001; TUG 3 vs. TUG 4, F(2,101) D 17.434, p < .001; except for TUG 2 vs. TUG 4, F(2,101) D 0.429, p D .65 (Figure 1). Table 3 shows the output of ROC analyses, including the area under the curve (AUC) and the cutoff scores (in seconds) that best discriminated the three groups for each TUG modality. The four TUG modalities provided an accurate differentiation between the MCI and control groups (area under the curve > .8, p < .001), while discrimination between the MCI and AD groups was less accurate (TUG 1: AUC D .67, p D .02; TUG 2–4: AUC > .7, p D .001). All TUG modalities provided optimal accuracy in discriminating between AD and control groups (AUC > .9, p < .001). Comparison of AUCs using DeLong’s method revealed that the four TUG modalities were equally accurate in discriminating between MCI and controls, as well as between MCI and AD. In discriminating between controls and AD patients, TUG 1 was less accurate than other modalities (TUG 1 vs. TUG 2: p D .0129; TUG 1 vs. TUG 3: p D .0061; TUG 1 vs. TUG 4: p D .0219). Discussion In our study, MCI patients displayed more difficulty in performing the functional mobility task alone (TUG 1), as well as associated with motor and/or cognitive tasks (TUG 2–4) when compared to controls, as represented by increased time to perform the tasks. Conversely, MCI patients performed better in all tasks when compared to AD patients. This data is in agreement the notion that MCI represents a clinical entity that is distinct from normal aging, with the potential for further progression to AD or other dementias (Petersen et al., 2001). There is a substantial body of evidence that a divided attention task impairs gait performance, especially in the cognitively impaired elderly (Gillain et al., 2009; MonteroOdasso et al., 2009; Montero-Odasso, Muir & Speechley, 2012; Muir et al., 2012; Pettersson, Olsson, & Wahlund, 2005; Suttanon et al., 2012; Taylor, Delbaere, Mikolaizak, Lord, & Close, 2013; Theill, Martin, Schumacher, Bridenbaugh, & Kressig, 2011). The three groups exhibited impaired performance, particularly on functional mobility associated with cognitive tasks (TUG 2 and TUG 4), Journal of Motor Behavior
Functional Mobility in a Divided Attention Task in the Elderly
TABLE 1. Demographic and Cognitive Characteristics of the Diagnostic Groups Variable
Control (n D 36)
MCI (n D 42)
AD (n D 26)
p
72.6 §5.4 12.7 § 4.4b 27 (75%) 28.6 § 1.4b,e 1.7 § 2.4b,e 3.89 § 2.2b,e 19.6 § 4.9b,e
75.5 § 5.3 10.6 § 4.9 32 (76%) 27.4 § 2.1e,f 4.9 § 3.7e,f 8.9 § 4.2e,f 14.7 § 3.5e,f
74.3 § 5.6 9.3 § 4.6b 17 (65%) 22.6 § 3.0b,f 10.0 § 5.4b,f 15.5 § 5.8b,f 9.3 § 2.8b,f
.68a .02c .59d < .001c < .001c < .001c < .001c
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Age* Years of education* Gender, women# MMSE* SKT* Exit25* Verbal fluency*
Note. MCI D mild cognitive impairment; AD D Alzheimer’s disease; MMSE D Mini Mental State Examination; SKT D Short Cognitive Test; Exit25 D executive interview. a Analysis of variance for differences between diagnostic groups. b Significant difference between control and AD groups (Bonferroni correction, p < .05). c Kruskal-Wallis test for differences between diagnostic groups. d Chi-square test for differences between diagnostic groups. e Significant difference between control and MCI groups (Bonferroni correction, p < .05). f Significant difference between MCI and AD groups (Bonferroni correction, p < .05). *indicates mean § SD; #n(%).
however this effect was more pronounced in the MCI and AD groups (Table 2). Intragroup interaction analysis showed an expressive difference between mean time of execution for TUG 2 and TUG 4, when compared to TUG 1 and TUG 3 for the MCI and AD groups. This data, added to our findings of very similar mean time of execution for TUG 2 and TUG 4 (Figure 1 and Table 2), highlights the role of the cognitive task as the highest demanding factor in the divided attention task. Gait requires more attention with aging, and attentional resources are limited (according to the capacity-sharing theory), thus performing a second task while walking may result in a slower gait or delayed performance on the second task (i.e., cognitive and/or manual task; Yogev-Seligmann, Hausdorff, & Giladi, 2008). This is especially true for the elderly (Muir et al., 2012; Tseng, Cullum, & Zhang, 2014). In our study, the TUG test associated to the manual and cognitive task (TUG 4) did not prove to be more demanding than TUG associated to the cognitive task alone (TUG 2). This is probably due to the fact that functional motor dual
tasks may be more familiar and easier to comprehend than cognitive dual tasks, even in subjects with cognitive impairment (Wittwer, Webster, & Hill, 2014). We observed that TUG 2 and TUG 4 were more impaired than the TUG 1 and TUG 3 among examined groups. These data suggest that cognitive tasks interfere more with functional mobility than motor tasks. The performance of such tasks while walking poses an extra challenge in the attentional abilities of cognitively impaired elderly (Beaunieux, Desgranges, & Eustache, 1998), which is mediated by central mechanisms (prefrontal cortex activity and executive functions; Al-Yahya et al., 2011). According to Tseng et al. (2014), MCI patients are more prone to motor dysfunction than cognitively normal elderly under dual task conditions where competitive demands challenge cognitive functions while simultaneously performing a motor task. To Hausdorff, Yogev, Springer, Simon, and Giladi (2005), a possible explanation for the observed decline in gait performance relates to the concept of prioritization. When asked to walk and perform any other
TABLE 2. Mean Time to Perform Each TUG Task (in Seconds) According to Diagnostic Group Variable TUG 1 TUG 2 TUG 3 TUG 4
Control (n D 36) 8.90 10.54 9.56 11.05
§ 1.47 § 2.12a,b § 1.55a,b § 2.34a,b a,b
MCI (n D 42) 11.08 15.33 12.07 16.21
§ 2.01 § 3.78a,c § 2.06a,c § 3.77a,c a,c
AD (n D 26) 12.29 20.09 13.99 20.31
§ 2.37 § 8.17b,c § 3.61b,c § 5.52b,c b,c
h2 (effect size)
p
.328 .417 .366 .465
< .001 < .001 < .001 < .001
Note. Values are mean § SD (range). All p values were generated from a two-way repeated measures analysis of variance. TUG D timed up and go; MCI D mild cognitive impairment; AD D Alzheimer’s disease; TUG 1 D TUG simple task; TUG 2 D TUG plus cognitive task; TUG 3 D TUG plus manual task; TUG 4 D TUG plus cognitive and manual task. a Significant difference between control and MCI groups (Tukey HSD post hoc, p < .001). b Significant difference between control and AD groups (Tukey HSD post hoc, p < .001). c Significant difference between MCI and AD groups (Tukey HSD post hoc, p < .05).
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S. de Melo Borges, M. Radanovic, & O. V. Forlenza
FIGURE 1. Mean time of execution for timed up and go (TUG) test 1–4 with standard deviations in controls (n D 36), mild cognitive impairment (MCI; n D 42), and mild Alzheimer’s disease (AD; n D 26).
task, a person may give inappropriate prioritization to the concurrent task, sacrificing attention resources needed for gait (Bloem, Grimbergen, van Dijk, & Munneke, 2006; Hausdorff et al., 2005). In the present study, participants were not given explicit instructions regarding which task to prioritize (similar to what happens during normal daily life activities), yet gait was clearly affected in all dual tasks. We found a negative, albeit low correlation between scores
on the verbal fluency test and mean time of execution for TUG 2 and TUG 4 in the AD group, but not in the MCI or control groups. This finding may indicate impairment in prioritization abilities during the secondary (cognitive) task. In our sample, ROC curve analyses showed that the mean time of execution for the four TUG modalities was able to accurately discriminate the three diagnostic groups. The
TABLE 3. Cutoff Scores (in Seconds), Sensitivities, and Specificities for Each TUG Modality According to Diagnostic Group Group Control versus MCI
Control versus AD
MCI versus AD
Variable
AUC
Cutoff score
Sensitivity
Specificity
p
TUG 1 TUG 2 TUG 3 TUG 4 TUG 1 TUG 2 TUG 3 TUG 4 TUG 1 TUG 2 TUG 3 TUG 4
.83 .89 .84 .89 .89 .98 .94 .97 .67 .73 .74 .75
9.75 12.03 10.95 14.35 9.90 13.02 11.11 15.70 11.39 15.38 12.25 19.68
79% 83% 76% 69% 89% 96% 92% 89% 65% 77% 81% 58%
81% 83% 83% 94% 81% 92% 86% 100% 69% 62% 62% 86%
< .001 < .001 < .001 < .001 < .001 < .001 < .001 < .001 .02 .002 .001 .001
Note. TUG D timed up and go; AUC D area under the curve; TUG 1 D TUG simple task; TUG 2 D TUG plus cognitive task; TUG 3 D TUG plus manual task; TUG 4 D TUG plus cognitive and manual task; MCI D mild cognitive impairment; AD D Alzheimer’s disease.
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Functional Mobility in a Divided Attention Task in the Elderly
discrimination was most effective between control and MCI groups, and between control and AD groups. However, discrimination was less accurate between MCI and AD groups. Although TUG 1 was as accurate as the divided-attention TUG modalities in differentiating MCI and control groups, it was less accurate in differentiation between MCI and AD groups, as predicted by our hypothesis. Although motor changes are more pronounced in AD (Hauer et al., 2002), the threshold for identifying motor changes may occur earlier in the disease continuum (Muir et al., 2012). This may explain the lower accuracy in differentiation between MCI and AD patients. A novel contribution of our study was to determine that the TUG test with and without divided attention tasks was able to discriminate MCI patients from controls individuals from controls with levels of accuracy; however, such discrimination between MCI and AD patients was not so powerful. Our findings reinforce the theory that motor performance is decreased even in early cognitive impairment (Aggarwal et al., 2006; Beauchet et al., 2008; Buchman et al., 2007; Buracchio, Dodge, Howieson, Wasserman, & Kaye, 2010; Camicioli, Howieson, Lehman, & Kaye, 1997; Deshpande, Metter, Bandinelli, Guralnik, & Ferrucci, 2009; Gillain et al., 2009; Verghese et al., 2008; Verghese et al., 2007; Wait et al., 2005) and that functional mobility is affected by cognitive impairment in both single and divided attention tasks. Everyday life frequently comprises functional activities requiring divided attention (i.e., walking while engaging in conversation). Hence, assessment using divided attention TUG modalities may allow detection of such difficulties in older subjects with cognitive impairment in different ecological contexts (environmental and behavioral), thus enhancing focused rehabilitation efforts. A limitation of our study was a lack of analyses comparing MCI subgroups (amnestic, nonamnestic, single and multiple domains), due to the small sample size. A different performance pattern may be expected for each subgroup according to the main cognitive domain affected. In conclusion, our results indicate that MCI patients perform differently from AD patients and cognitively healthy elders in all modalities of the TUG test; the level of performance of MCI patients is between that observed in the other two groups. The combination of the TUG test with a cognitive task reinforces the discriminatory ability, but we could not demonstrate the combined cognitive-manual task (TUG 4) to be superior than the cognitive task alone (TUG 2). Therefore, TUG 2 proves to be more time-effective for clinical purposes. Although the TUG should not be regarded as a diagnostic tool, we understand that combined tasks may be useful for the rehabilitation professional in his/her clinical practice, particularly raising the attention to the presence of cognitive impairments. On the other hand, the discriminatory ability of patients with MCI from those with dementia was not as good as the former (i.e., normal elders vs. MCI), 2015, Vol. 47, No. 5
which may have been due to the insufficient number of subjects in AD group. Further studies addressing this issue in larger samples are warranted. ACKNOWLEDGMENTS The authors would like to thank the team members of the Neuroscience Laboratory (LIM-27) and the postgraduate program in Psychiatry at the Faculty of Medicine, University of S~ao Paulo; their statistical consultant Bernardo dos Santos; and the elders who voluntarily participated in this study. FUNDING This study received funding from Coordination for the Improvement of Higher Education Personnel (CAPES). REFERENCES Aggarwal, N. T., Wilson, R. S., Beck, T. L., Bienas, J. L., & Bennett, D. A. (2006). Motor dysfunction in mild cognitive impairment and the risk of incident Alzheimer disease. Archives of Neurology, 63, 1763–1769. Al-Yahya, E., Dawes, H., Smith, L., Dennis, A., Howells, K., & Cockburn, J. (2011). Cognitive motor interference while walking: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 35, 715–728. Ayan, C., Cancela, J. M., Gutierrez, A., & Prieto, I. (2013). Influence of the cognitive impairment level on the performance of the timed “up & go” test (TUG) in elderly institutionalized people. Archives of Gerontology and Geriatrics, 56, 44–49. Beauchet, O., Allali, G., Berrut, G., Hommet, C., Dubost, V., & Assal, F. (2008). Gait analysis in dementia subjects: Interests and perspectives. Neuropsychiatric Diseases and Treatment, 4, 155–160. Beaunieux, H., Desgranges, B., & Eustache, F. (1998). Procedural memory: Construct validity and assessment methods. Journal of Neuropsychology, 8, 271–300. Bloem, B. R., Grimbergen, Y. A., van Dijk, J. G., & Munneke, M. (2006). The “posture second” strategy: A review of wrong priorities in Parkinson’s disease. Journal of the Neurological Sciences, 248, 196–204. Borges, S. M., Radanovic, M, & Forlenza, O. V. (2014). Fear of falling and falls in older adults with mild cognitive impairment and Alzheimer’s disease. Neuropsychiatry, Development, and Cognition, Section B, 3, 1–10. doi: 10.1080/13825585.2014.933770 Boyle, P. A., Buchman, A. S., Wilson, R. S., Leurgans, S. E., & Bennett, D. A. (2010). Physical frailty is associated with incident mild cognitive impairment in community-based older persons. Journal of the American Geriatrics Society, 58, 248–255. Brucki, S. M. D., Nitrini, P., Caramelli, P., Bertolucci, P. H. F., & Okamoto, I. H. (2003). Suggestions for the use of the Mini Mental State Examination. Arquivos de Neuro-Psiquiatria, 61, 777– 781. Buchman, A. S., Wilson, R. S., Boyle, P. A., Bienas, J. L., & Bennett, D. A. (2007). Grip strength and the risk of incident Alzheimer’s disease. Neuroepidemiology, 29, 66–73. Buracchio, T., Dodge, H. H., Howieson, D., Wasserman, D., & Kaye, J. (2010). The trajectory of gait speed preceding mild cognitive impairment. Archives of Neurology, 67, 980–986. Camicioli, R., Howieson, D., Lehman, S., & Kaye, J. (1997). Talking while walking: The effect of a dual task in aging and Alzheimer’s disease. Neurology, 48, 955–958. 383
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McGough, E. L., Kelly, V. E., Logsdon, R. G., McCurry, S. M., Cochrane, B. B., Engel, J. M., & Teri, L. (2011). Associations between physical performance and executive function in older adults with mild cognitive impairment: Gait speed and the timed “up and go” test. Physical Therapy, 91, 1198–1207. McKhan, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS-ADRDA work group under the auspices of department of the health and human services task force on Alzheimer’s disease. Neurology, 34, 939–944. Montero-Odasso, M., Bergman, H., Phillips, N. A., Wong, C. H., Sourial, N., & Chertkow, H. (2009). Dual-tasking and gait in people with mild cognitive impairment. The effect of working memory. BMC Geriatrics, 9, 41. Montero-Odasso, M., Muir, S. W., & Speechley, M. (2012). Dualtask complexity affects gait in people with mild cognitive impairment: The interplay between gait variability, dual tasking, and risk of falls. Archives of Physical Medicine and Rehabilitation, 93, 293–239. Muir, S. W., Speechley, M., Wells, J., Borrie, M., Gopaul, K., & Montero-Odasso, M. (2012). Gait assesment in mild cognitive impairment and Alzheimer´s disease: The effect of dual-task challenges across the cognitive spectrum. Gait & Posture, 35, 96–100. Petersen, R. C., Stevens, J. C., Ganguli, M., Tangalos, E. G., Cummings, J. L., & DeKosky, S. T. (2001). Practice parameter: Early detection of dementia: Mild cognitive impairment (an evidence-based review): Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology, 56, 1133–1142. Pettersson, A. F., Olsson, E., & Wahlund, L. O. (2005). Motor function in subjects with mild cognitive impairment and early Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 19, 299–304. Podsiadlo, D., & Richardson, S. (1991). The timed “Up & Go”: A test of basic functional mobility for frail elderly persons. Journal of the American Geriatrics Society, 39, 142–148. Puisieux, F., Pardessus, V., & Bombois, S. (2005). Dementia and falls: Two related syndromes in old age. Psychologie et Neuropsychiatrie due Vieillissement, 3, 271–279. Royal, D. R., Mahurin, R. K., & Gray, K. F. (1992). Beside assessment of executive impairment: The executive interview. Journal of the American Geriatrics Society, 40, 1221–1226. Scarmeas, N., Albert, M., Brandt, J., Blacker, D., Hadjigeorgiou, G., Papadimitriou, A., . . . Stern, Y. (2005). Motor signs predict poor outcomes in Alzheimer disease. Neurology, 64, 1696– 1703. Shumway-Cook, A., Brauer, S., & Woollacott, M. (2000). Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Physical Therapy, 80, 896–903. Shumway-Cook, A., Woollacott, M., Kerns, K. A., & Baldwin, M. (1997). The effect of two types of cognitive tasks on postural stability in older adults with and without a history of falls. The Journals of Gerontolology Series A: Biological Sciences and Medical Sciences, 54, 232–240. Suttanon, P., Hill, K. D., Said, C. M., Logiudice, D., Lautenschlager, N. T., & Dodd, K. J. (2012). Balance and mobility dysfunction and falls risk in older people with mild to moderate Alzheimer disease. American Journal of Physical Medicine and Rehabilitation, 91, 12–23. Taylor, M. E., Delbaere, K., Mikolaizak, A. S., Lord, S. R., & Close, J. C. (2013). Gait parameter risk factors for falls under simple and dual task conditions in cognitively impaired older people. Gait & Posture, 37, 126–130.
Journal of Motor Behavior
Functional Mobility in a Divided Attention Task in the Elderly and dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 78, 929–935. Wait, L. M., Grayson, D. A., Piguet, O., Creasey, H., Bennett, H. P., & Broe, G. A. (2005). Gait slowing as a predictor of incident dementia: 6 years longitudinal data from the Sydney older person study. Journal of the Neurological Sciences, 229, 89–93. Wittwer, J. E., Webster, K. E., & Hill, K. (2014). The effects of a concurrent motor task on walking in Alzheimer’s disease. Gait & Posture, 39, 291–296. Yogev-Seligmann, G., Hausdorff, J. M., & Giladi, N. (2008). The role of executive function and attention in gait. Movement Disorders, 23, 329–342. Received February 19, 2014 Revised October 30, 2014 Accepted December 9, 2014
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2015, Vol. 47, No. 5
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ISSN: 0022-2895 (Print) 1940-1027 (Online) Journal homepage: http://www.tandfonline.com/loi/vjmb20
Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment Sheila de Melo Borges, Márcia Radanovic & Orestes Vicente Forlenza To cite this article: Sheila de Melo Borges, Márcia Radanovic & Orestes Vicente Forlenza (2015) Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment, Journal of Motor Behavior, 47:5, 378-385, DOI: 10.1080/00222895.2014.998331 To link to this article: https://doi.org/10.1080/00222895.2014.998331
Published online: 22 Jan 2015.
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Date: 10 December 2017, At: 18:02
Journal of Motor Behavior, Vol. 47, No. 5, 2015 Copyright © Taylor & Francis Group, LLC
RESEARCH ARTICLE
Functional Mobility in a Divided Attention Task in Older Adults With Cognitive Impairment rcia Radanovic, Orestes Vicente Forlenza Sheila de Melo Borges, Ma
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~o Paulo, Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, Faculty of Medicine, University of Sa Brazil. ABSTRACT. Motor disorders may occur in mild cognitive impairment (MCI) and at early stages of Alzheimer’s disease (AD), particularly under divided attention conditions. We examined functional mobility in 104 older adults (42 with MCI, 26 with mild AD, and 36 cognitively healthy) using the Timed Up and Go test (TUG) under 4 experimental conditions: TUG single task, TUG plus a cognitive task, TUG plus a manual task, and TUG plus a cognitive and a manual task. Statistically significant differences in mean time of execution were found in all four experimental conditions when comparing MCI and controls (p < .001), and when comparing MCI and AD patients (p < .05). Receiver-operating characteristic curve analyses showed that all four testing conditions could differentiate the three groups (area under the curve > .8, p < .001 for MCI vs. controls; area under the curve > .7, p < .001 for MCI vs. AD). The authors conclude that functional motor deficits occurring in MCI can be assessed by the TUG test, in single or dual task modality.
Verghese et al., 2007; Wait et al., 2005). According to Camicioli and Majumdar (2010) and Liu-Ambrose et al. (2010), older adults with mild cognitive impairment (MCI) are also at an increased risk for mobility decline and falls (Borges, Radanovic, & Forlenza, 2014; Puisieux, Pardessus, & Bombois, 2005). Therefore, evaluation of changes in gait may be useful for preventing falls, assessing functional decline, and detecting the early stages of cognitive decline (Gillain et al., 2009). Mobility in daily life often requires walking while simultaneously performing cognitive or motor tasks, such as talking with a friend or carrying a cup of coffee (Kelly, Eusterbrock, & Schmway-Cook, 2012). Thus, gait abnormalities may be magnified by divided attention tasks, also known as dual tasks (Hauer et al., 2002; Shumway-Cook, Woollacott, Kerns, & Baldwin, 1997). There is evidence that older people who demonstrate a slower gait during a dual task are more likely to develop cognitive impairment (Camicioli, Howieson, Oken, Sexton, & Kaye, 1998). However, there is no consensus as to whether patients with MCI exhibit similar performance to patients with AD dementia, or whether the evaluation of mobility during a divided attention task can differentiate older adults with MCI from those with AD (Muir et al., 2012). The timed “up and go” (TUG) test is widely utilized by professionals in gerontology to assess functional mobility in an ecological manner, as it simultaneously evaluates assesses gait, dynamic balance, and functional mobility. It is a useful tool for rehabilitation professionals to evaluate the risk of falls in older people, as well as motor deficits in MCI subjects (Ayan, Cancela, Gutierrez, & Prieto, 2013; Donoghue et al., 2012; Gillain et al., 2009; Herman, Giladi, & Hausdorff, 2011; McGough et al., 2011; Podsiadlo & Richardson, 1991; Shumway-Cook, Brauer & Woollacott, 2000). Impairment in this test has been associated with the occurrence of falls in elderly populations (Shumway-Cook, Brauer, & Woollacott, 2000) and early motor intervention should be prioritized in this population in order to prevent falls and ensure independence and autonomy. The aim of the present study was to evaluate whether
Keywords: functional mobility, divided attention task, cognitive impairment
F
unctional mobility, particularly gait, depends on several systems for the maintenance of postural stability. Cognitive functions (including executive function and attention) are important in the regulation of functional mobility (Montero-Odasso et al., 2009). Motor changes are associated with senescence and are more pronounced in the presence of cognitive decline (Hauer, Marburger, & Oster, 2002). Cognitive decline is the main clinical marker of dementia, and motor disorders are most commonly described at advanced stages of Alzheimer’s disease (AD; Beauchet et al., 2008). Over the last decade, several studies (Aggarwal, Wilson, Beck, Bienas, & Bennett, 2006; Beauchet et al., 2008; Scarmeas et al., 2005; Verghese, Wang, Lipton, Holtzer, & Wue, 2007; Wait et al., 2005) have shown that gait abnormalities may indeed precede the diagnosis of cognitive decline. This indicates that a deficiency in cortical control of gait, in addition to certain motor deficits (e.g., postural control and muscle strength), may be observed at early stages of AD and other dementias. Boyle, Buchman, Wilson, Leurgans, and Bennett (2010) suggested that measures of physical frailty, such as walking speed and grip strength, may facilitate the identification of individuals prone to developing cognitive dysfunction. Many other studies have indicated that decreased gait speed may accompany incipient cognitive decline in elderly populations (Aggarwal et al., 2006; Beauchet et al., 2008; Buchman, Wilson, Boyle, Bienas, & Bennett, 2007; Gillain et al., 2009;
Correspondence address: Sheila de Melo Borges, Laboratory of Neuroscience (LIM 27), Department and Institute of Psychiatry, Faculty of Medicine, University of S~ ao Paulo, Rua Dr. Ovıdio Pires de Campos 785, 05403–010, S~ ao Paulo, SP, Brazil. e-mail: [email protected] 378
Functional Mobility in a Divided Attention Task in the Elderly
functional mobility with or without divided attention is a useful test in differentiating MCI patients from cognitively healthy elderly controls and mild AD patients. Our hypothesis was that the examined groups would differ in functional mobility, particularly when performing divided attention tasks, and that the difference would be most pronounced when a cognitive task was associated with a basic motor task.
Method
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Participants Participants were recruited from a cohort of older adults with varying degrees of cognitive impairment, ranging from normal cognition to mild–moderate dementia, as part of an ongoing study on cognitive aging that has been conducted since 2002 in the memory clinic of the Institute of Psychiatry, University of S~ao Paulo. All participants or their representatives signed an informed consent prior to the enrollment in this study, which was approved by the local Ethics Committee. One hundred and four individuals between 60 and 88 years old, of both genders, with a minimum of four years of schooling were included in this study. Cognition was assessed using the Mini-Mental State Examination (MMSE; Brucki, Nitrini, Caramelli, Bertolucci, & Okamoto, 2003; Folstein, Folstein, & McHugh, 1975), Short Cognitive Test (SKT; Erzigkeit, 1991; Flaks et al., 2006), Executive Interview – Exit 25 (Matioli & Caramelli, 2010; Royal, Mahurin, & Gray, 1992), and verbal fluency, animals category (Isaacs & Kennie, 1973). Clinical diagnoses were established at consensus meetings taking into account all clinical and available laboratory information gathered by a multidisciplinary team including physicians (psychiatrists, a geriatrician, and a neurologist), neuropsychologists, physical therapists, speech therapists, occupational therapists, and gerontologists. Participants were rated according to the Brazilian version of the Clinical Dementia Rating Scale (CDR; Maia et al., 2006) and then classified into three groups: mild AD (CDR D 1) according to the NINCS-ADRDA criteria (McKhan et al., 1984; n D 26), MCI (CDR D 0.5; according to Petersen et al., 2001; n D 42); or controls (CDR D 0; i.e., no evidence of cognitive or functional impairment; n D 36). Subjects with symptomatic orthopaedic conditions (e.g., acute or chronic pain in the lower limbs, recent surgery on the lower limbs) or other neurological disorders (e.g., stroke, Parkinson’s disease, or other dementias) that could impair mobility were excluded from the study. Well-controlled clinical conditions (e.g., hypertension, diabetes, hypothyroidism) or visual or hearing impairment corrected by prosthesis were not regarded as exclusion criteria provided that their manifestations did not interfere with motor or cognitive function. 2015, Vol. 47, No. 5
Procedures The TUG test was administered to all participants in four different ways: (a) TUG single task (performance of the TUG test alone), (b) TUG cognitive (TUG test combined with a verbal fluency task, animal category), (c) TUG manual (performing the TUG test while carrying a full cup of water), and (d) triple TUG test (TUG test in association with both the cognitive and manual task; i.e., performing the verbal fluency test while carrying a full cup of water). The sequence of administration of the four TUG tests was randomized according to Shumway-Cook et al. (2000). In this study, we used a standard manual task in combination with the TUG test (“holding a full cup of water”; Pettersson, Olsson, & Wahlund, 2005; Shumway-Cook, Brauer, & Woollacott, 2000). For the cognitive task, the most commonly used are counting backwards or the verbal fluency task. We used the verbal fluency task, animal category, as it is a widely used test that requires attention and executive function (Montero-Odasso, Muir, & Speechley, 2012). In accordance with Podsiadlo and Richardson (1991), a demonstration of how the test should be executed was performed by the current authors and all questions raised by the subjects were answered before starting the test. After this demonstration, participants were instructed to stand up from a chair, walk 3 m at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again to ensure that they were able to perform the task. For the manual task (holding a cup full of water), subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will be holding this cup of water.
For the cognitive task (animal fluency), subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will do it while naming as many animals as you can remember.
For the triple task (manual plus cognitive task) subjects were given the following instructions:
Please, now you will repeat the same thing you have done before (stand up from a chair, walk three meters at a comfortable speed, cross a line on the floor, turn around, walk back, and sit down again), but this time you will do it as you hold this cup of water and name as many animals as you can remember. 379
S. de Melo Borges, M. Radanovic, & O. V. Forlenza
No physical assistance was allowed during the performance of the tasks. The physical therapist stood next to the chair and accompanied the participant when required for safety reasons, such as risk of falling. During the performance of the tasks, no additional verbal cues (e.g., “turn around” or “sit down”) were provided.
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Statistical Analysis One-way analysis of variance (ANOVA) was used to compare means for demographic data and cognitive assessment scores respecting Gaussian distribution (age and scores on verbal fluency). The Kruskal-Wallis test was used to compare means for demographic data and cognitive assessment scores that did not respect Gaussian distribution (schooling and scores on GDS-15, MMSE, SKT, and Exit25). Pearson’s chi-square test was used to compare categorical data (gender) between groups. Bonferroni post hoc correction was used to perform pairwise comparisons. Two-way repeated measures ANOVA was used to compare the mean time of execution (in seconds) in the four modalities of the TUG test between test groups. The Huynh-Feldt correction was applied to overcome violation of sphericity found in the data covariance matrix. Tukey HSD post hoc correction was used to perform pairwise comparisons. Spearman’s correlation (r) was used to evaluate a possible relationship between scores on verbal fluency (as performed in the initial cognitive assessment) and performance in TUG 1–4. The effect size of the scores obtained in each TUG modality was determined by multivariate global linear model. Receiver-operating characteristic (ROC) curve analyses were employed to identify the cutoff scores in each TUG test that best discriminated MCI versus Control and MCI versus AD. For each variable, the SPSS program (version 20.0) provided a list of cutoff points with a value of sensitivity and specificity (which was later calculated by 1 [specificity]). We considered as the best cutoff scores those yielding the highest values for sensitivity and specificity. Results Table 1 displays the demographic and cognitive characteristics of the sample. No significant differences were observed between groups for age and gender. Patients in the AD group were less educated. As expected, the AD group performed worse than MCI and control groups in all cognitive tests (MMSE, SKT, Exit 25, and verbal fluency). The MCI group exhibited intermediate scores when compared to controls and AD patients. All participants were able to perform all four TUG modalities. The three groups differed with respect to the mean time required to complete each task (Table 2). The MCI group performed worse than the control group, yet better than the AD group in all four TUG tests, with higher 380
effect size associated with the cognitive task (TUG 2 and 4; p < .001). Spearman’s correlation showed a mild negative correlation between the verbal fluency tests in TUG 2 (r D –.432; p < .001) and TUG 4 (r D –.422; p < .001) in the AD group only (data not shown). The two-way repeated measures ANOVA with HuynhFeldt correction revealed significant differences in the mean of time of execution between the three groups for all TUG modalities: TUG 1 vs. TUG 2, F(2,101) D 15.580, p < .001; TUG 1 vs. TUG 3, F(2,101) D 7.638, p D .001; TUG 1 vs. TUG 4, F(2,101) D 22.204, p < .001; TUG 2 vs. TUG 3, F(2,101) D 12.432, p < .001; TUG 3 vs. TUG 4, F(2,101) D 17.434, p < .001; except for TUG 2 vs. TUG 4, F(2,101) D 0.429, p D .65 (Figure 1). Table 3 shows the output of ROC analyses, including the area under the curve (AUC) and the cutoff scores (in seconds) that best discriminated the three groups for each TUG modality. The four TUG modalities provided an accurate differentiation between the MCI and control groups (area under the curve > .8, p < .001), while discrimination between the MCI and AD groups was less accurate (TUG 1: AUC D .67, p D .02; TUG 2–4: AUC > .7, p D .001). All TUG modalities provided optimal accuracy in discriminating between AD and control groups (AUC > .9, p < .001). Comparison of AUCs using DeLong’s method revealed that the four TUG modalities were equally accurate in discriminating between MCI and controls, as well as between MCI and AD. In discriminating between controls and AD patients, TUG 1 was less accurate than other modalities (TUG 1 vs. TUG 2: p D .0129; TUG 1 vs. TUG 3: p D .0061; TUG 1 vs. TUG 4: p D .0219). Discussion In our study, MCI patients displayed more difficulty in performing the functional mobility task alone (TUG 1), as well as associated with motor and/or cognitive tasks (TUG 2–4) when compared to controls, as represented by increased time to perform the tasks. Conversely, MCI patients performed better in all tasks when compared to AD patients. This data is in agreement the notion that MCI represents a clinical entity that is distinct from normal aging, with the potential for further progression to AD or other dementias (Petersen et al., 2001). There is a substantial body of evidence that a divided attention task impairs gait performance, especially in the cognitively impaired elderly (Gillain et al., 2009; MonteroOdasso et al., 2009; Montero-Odasso, Muir & Speechley, 2012; Muir et al., 2012; Pettersson, Olsson, & Wahlund, 2005; Suttanon et al., 2012; Taylor, Delbaere, Mikolaizak, Lord, & Close, 2013; Theill, Martin, Schumacher, Bridenbaugh, & Kressig, 2011). The three groups exhibited impaired performance, particularly on functional mobility associated with cognitive tasks (TUG 2 and TUG 4), Journal of Motor Behavior
Functional Mobility in a Divided Attention Task in the Elderly
TABLE 1. Demographic and Cognitive Characteristics of the Diagnostic Groups Variable
Control (n D 36)
MCI (n D 42)
AD (n D 26)
p
72.6 §5.4 12.7 § 4.4b 27 (75%) 28.6 § 1.4b,e 1.7 § 2.4b,e 3.89 § 2.2b,e 19.6 § 4.9b,e
75.5 § 5.3 10.6 § 4.9 32 (76%) 27.4 § 2.1e,f 4.9 § 3.7e,f 8.9 § 4.2e,f 14.7 § 3.5e,f
74.3 § 5.6 9.3 § 4.6b 17 (65%) 22.6 § 3.0b,f 10.0 § 5.4b,f 15.5 § 5.8b,f 9.3 § 2.8b,f
.68a .02c .59d < .001c < .001c < .001c < .001c
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Age* Years of education* Gender, women# MMSE* SKT* Exit25* Verbal fluency*
Note. MCI D mild cognitive impairment; AD D Alzheimer’s disease; MMSE D Mini Mental State Examination; SKT D Short Cognitive Test; Exit25 D executive interview. a Analysis of variance for differences between diagnostic groups. b Significant difference between control and AD groups (Bonferroni correction, p < .05). c Kruskal-Wallis test for differences between diagnostic groups. d Chi-square test for differences between diagnostic groups. e Significant difference between control and MCI groups (Bonferroni correction, p < .05). f Significant difference between MCI and AD groups (Bonferroni correction, p < .05). *indicates mean § SD; #n(%).
however this effect was more pronounced in the MCI and AD groups (Table 2). Intragroup interaction analysis showed an expressive difference between mean time of execution for TUG 2 and TUG 4, when compared to TUG 1 and TUG 3 for the MCI and AD groups. This data, added to our findings of very similar mean time of execution for TUG 2 and TUG 4 (Figure 1 and Table 2), highlights the role of the cognitive task as the highest demanding factor in the divided attention task. Gait requires more attention with aging, and attentional resources are limited (according to the capacity-sharing theory), thus performing a second task while walking may result in a slower gait or delayed performance on the second task (i.e., cognitive and/or manual task; Yogev-Seligmann, Hausdorff, & Giladi, 2008). This is especially true for the elderly (Muir et al., 2012; Tseng, Cullum, & Zhang, 2014). In our study, the TUG test associated to the manual and cognitive task (TUG 4) did not prove to be more demanding than TUG associated to the cognitive task alone (TUG 2). This is probably due to the fact that functional motor dual
tasks may be more familiar and easier to comprehend than cognitive dual tasks, even in subjects with cognitive impairment (Wittwer, Webster, & Hill, 2014). We observed that TUG 2 and TUG 4 were more impaired than the TUG 1 and TUG 3 among examined groups. These data suggest that cognitive tasks interfere more with functional mobility than motor tasks. The performance of such tasks while walking poses an extra challenge in the attentional abilities of cognitively impaired elderly (Beaunieux, Desgranges, & Eustache, 1998), which is mediated by central mechanisms (prefrontal cortex activity and executive functions; Al-Yahya et al., 2011). According to Tseng et al. (2014), MCI patients are more prone to motor dysfunction than cognitively normal elderly under dual task conditions where competitive demands challenge cognitive functions while simultaneously performing a motor task. To Hausdorff, Yogev, Springer, Simon, and Giladi (2005), a possible explanation for the observed decline in gait performance relates to the concept of prioritization. When asked to walk and perform any other
TABLE 2. Mean Time to Perform Each TUG Task (in Seconds) According to Diagnostic Group Variable TUG 1 TUG 2 TUG 3 TUG 4
Control (n D 36) 8.90 10.54 9.56 11.05
§ 1.47 § 2.12a,b § 1.55a,b § 2.34a,b a,b
MCI (n D 42) 11.08 15.33 12.07 16.21
§ 2.01 § 3.78a,c § 2.06a,c § 3.77a,c a,c
AD (n D 26) 12.29 20.09 13.99 20.31
§ 2.37 § 8.17b,c § 3.61b,c § 5.52b,c b,c
h2 (effect size)
p
.328 .417 .366 .465
< .001 < .001 < .001 < .001
Note. Values are mean § SD (range). All p values were generated from a two-way repeated measures analysis of variance. TUG D timed up and go; MCI D mild cognitive impairment; AD D Alzheimer’s disease; TUG 1 D TUG simple task; TUG 2 D TUG plus cognitive task; TUG 3 D TUG plus manual task; TUG 4 D TUG plus cognitive and manual task. a Significant difference between control and MCI groups (Tukey HSD post hoc, p < .001). b Significant difference between control and AD groups (Tukey HSD post hoc, p < .001). c Significant difference between MCI and AD groups (Tukey HSD post hoc, p < .05).
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S. de Melo Borges, M. Radanovic, & O. V. Forlenza
FIGURE 1. Mean time of execution for timed up and go (TUG) test 1–4 with standard deviations in controls (n D 36), mild cognitive impairment (MCI; n D 42), and mild Alzheimer’s disease (AD; n D 26).
task, a person may give inappropriate prioritization to the concurrent task, sacrificing attention resources needed for gait (Bloem, Grimbergen, van Dijk, & Munneke, 2006; Hausdorff et al., 2005). In the present study, participants were not given explicit instructions regarding which task to prioritize (similar to what happens during normal daily life activities), yet gait was clearly affected in all dual tasks. We found a negative, albeit low correlation between scores
on the verbal fluency test and mean time of execution for TUG 2 and TUG 4 in the AD group, but not in the MCI or control groups. This finding may indicate impairment in prioritization abilities during the secondary (cognitive) task. In our sample, ROC curve analyses showed that the mean time of execution for the four TUG modalities was able to accurately discriminate the three diagnostic groups. The
TABLE 3. Cutoff Scores (in Seconds), Sensitivities, and Specificities for Each TUG Modality According to Diagnostic Group Group Control versus MCI
Control versus AD
MCI versus AD
Variable
AUC
Cutoff score
Sensitivity
Specificity
p
TUG 1 TUG 2 TUG 3 TUG 4 TUG 1 TUG 2 TUG 3 TUG 4 TUG 1 TUG 2 TUG 3 TUG 4
.83 .89 .84 .89 .89 .98 .94 .97 .67 .73 .74 .75
9.75 12.03 10.95 14.35 9.90 13.02 11.11 15.70 11.39 15.38 12.25 19.68
79% 83% 76% 69% 89% 96% 92% 89% 65% 77% 81% 58%
81% 83% 83% 94% 81% 92% 86% 100% 69% 62% 62% 86%
< .001 < .001 < .001 < .001 < .001 < .001 < .001 < .001 .02 .002 .001 .001
Note. TUG D timed up and go; AUC D area under the curve; TUG 1 D TUG simple task; TUG 2 D TUG plus cognitive task; TUG 3 D TUG plus manual task; TUG 4 D TUG plus cognitive and manual task; MCI D mild cognitive impairment; AD D Alzheimer’s disease.
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Functional Mobility in a Divided Attention Task in the Elderly
discrimination was most effective between control and MCI groups, and between control and AD groups. However, discrimination was less accurate between MCI and AD groups. Although TUG 1 was as accurate as the divided-attention TUG modalities in differentiating MCI and control groups, it was less accurate in differentiation between MCI and AD groups, as predicted by our hypothesis. Although motor changes are more pronounced in AD (Hauer et al., 2002), the threshold for identifying motor changes may occur earlier in the disease continuum (Muir et al., 2012). This may explain the lower accuracy in differentiation between MCI and AD patients. A novel contribution of our study was to determine that the TUG test with and without divided attention tasks was able to discriminate MCI patients from controls individuals from controls with levels of accuracy; however, such discrimination between MCI and AD patients was not so powerful. Our findings reinforce the theory that motor performance is decreased even in early cognitive impairment (Aggarwal et al., 2006; Beauchet et al., 2008; Buchman et al., 2007; Buracchio, Dodge, Howieson, Wasserman, & Kaye, 2010; Camicioli, Howieson, Lehman, & Kaye, 1997; Deshpande, Metter, Bandinelli, Guralnik, & Ferrucci, 2009; Gillain et al., 2009; Verghese et al., 2008; Verghese et al., 2007; Wait et al., 2005) and that functional mobility is affected by cognitive impairment in both single and divided attention tasks. Everyday life frequently comprises functional activities requiring divided attention (i.e., walking while engaging in conversation). Hence, assessment using divided attention TUG modalities may allow detection of such difficulties in older subjects with cognitive impairment in different ecological contexts (environmental and behavioral), thus enhancing focused rehabilitation efforts. A limitation of our study was a lack of analyses comparing MCI subgroups (amnestic, nonamnestic, single and multiple domains), due to the small sample size. A different performance pattern may be expected for each subgroup according to the main cognitive domain affected. In conclusion, our results indicate that MCI patients perform differently from AD patients and cognitively healthy elders in all modalities of the TUG test; the level of performance of MCI patients is between that observed in the other two groups. The combination of the TUG test with a cognitive task reinforces the discriminatory ability, but we could not demonstrate the combined cognitive-manual task (TUG 4) to be superior than the cognitive task alone (TUG 2). Therefore, TUG 2 proves to be more time-effective for clinical purposes. Although the TUG should not be regarded as a diagnostic tool, we understand that combined tasks may be useful for the rehabilitation professional in his/her clinical practice, particularly raising the attention to the presence of cognitive impairments. On the other hand, the discriminatory ability of patients with MCI from those with dementia was not as good as the former (i.e., normal elders vs. MCI), 2015, Vol. 47, No. 5
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