The Timed up and Go test is a mobile native test for both iOS and Android that is widely used for balance assessments in patients. It is often used to assess older patient’s risk of falling. It can be executed on the Qolty platform as a module in your study, either at home or in the clinic. See information below to view how the TGUG works.
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$ 4.00Per Patient/Month
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- Unlimited sampling intervals during collection period.
The timed-get-up-and-go task is a widely used test to determine balance assessment. Many parameters are developed and devised to determine patient’s balance assessment. Most of the screening tools are developed to determine older patients’ risk of falling. The Timed-Get-Up-and-Go (TUG) test is a modified version of the Get-up-and-Go (GUG) which was initially developed by Mathias et al. 1986. The “Get-up-and-Go” (GUG) relied on subjective measurement because the performance was rated on a 5-point scale where 1 was normal, and 5 was strictly abnormal with the higher risk of falling. In this version, an individual rises from a chair, walk at a 3-meter distance, turn around, return and sit back on the chair.
To improve and change the subjectivity of “Get-up-and-Go” (GUG) test, it was modified by the inclusion of time measurement for the entire procedure. The use of chair and stopwatch with a 3-meter walkway is necessary to perform the task. The entire procedure from standing up, walking, turning around, and then going back to the chair was timed. It was observed that older adult who finished the whole procedure under 10 seconds has no balance deficiency while for those who took more than 10 seconds has a high risk of falling.
In a more advanced version, the Expanded Timed Get-up-and-Go (ETGUG), all series of tasks such as seated position, walking, turning, stopping and sitting down are measured separately using a multi-memory stopwatch as incorporated in the Qolty app. The assessment is usually scored automatically by the smartphone (Galán-Mercant et al. 2014). In ETGUG, intensive time measurement is followed with respect to the component tasks. This approach pinpoints the main area of patient’s problem. Although TGUG is reliable in determining balance assessment among elderly patients, it is substantial to isolate the areas of functional deficit to provide useful clinical information.
A study on timed get-up-and-go test is revisited by measuring its component tasks (Wall et al. 2000). The basic procedure for TGUG is modified with different walkway measurement and stopwatch to monitor different activities. The chair used has no arm rest with a sea elevation of approximately 46 cm. The general procedure is as follows:
- Measure and mark a 10-m walkway from the subject’s legs of the straight-backed chair.
- The patient is advised to wear their usual footwear and have a walking aid if necessary.
- Allow the patient to sit back on a standard arm chair.
- Ideally, the patient should walk parallel to the line at normal pace.
- Every activity such as standing, gait initiation, walk 1, turning around, walk 2, slowing down phase, stopping, turning around and sitting down should be recorded separately.
The use of multimemory stopwatch which has lap buttons should be pressed at the following event:
- When the subject was standing upright;
- As the subject passed the 2-meter mark;
- As the subject passed the 8-meter mark;
- As the subject passed the 8-meter mark when returning; and
- As the subject passed the 2-meter mark when returning.
Figure 1. Schematic Diagram of ETGUG test’s arrangement
Both TGUG and ETGUG tests are performed among three groups such as healthy young individual, healthy elderly and elderly who has a greater risk of falling.
Patients with Bilateral Vestibular Loss
Swanenburg et al. 2014 performed the timed-get-up-and-go test in patients with bilateral vestibular loss. The test was performed twice among 21 BVL patients and 21 controls aged 58±14 years old with two different recruiters. It was observed that BVL patients walked slower paralleled to control subjects. Therefore, ETGUG tests show good reliability for BVL patients with functional deficits.
Elderly patients performing physical exercise
Another study on timed get-up-and-go predicted an explanation of falls in elderly adults performing physical exercises (Virtuoso et al. 2014). Over a span of 12 months, data was collected for the participants with an occurrence of falling. It was observed that the classic and cognitive TUG tests have an indirect relationship with the manifestation of falls. This is due to a different factorial cause of falling during physical activity which can be intrinsic or extrinsic. The prediction should be assessed in a broad range within the protocols or elderly population.
ETGUG performed with Stroke Individual
Faria et al. 2012 performed the Expanded Timed Get-up-and-Go task in patients who had undergone stroke. In this study, intra and interrater reliabilities of ETGUG test were validated and compared among patients who suffered a stroke and healthy individuals. It was observed that the group who suffered from stroke took longer time in every activity of the test.
Individuals with Right and Left Hemiplegia
A comparative study between left and right hemiplegics using ETGUG was performed by Muthukaruppan et al. 2011. Male individuals ages from 45-55 who suffered from either left or right immobility were assessed. The time it took for each subject to perform different component tasks were recorded. It was observed that individuals with left hemiplegia took more time in standing up, turning and sitting down while the individuals with right hemiplegia were having trouble with gait initiation, walking & speed.
Concussion Assessment using Dual-Task Combination
Preliminary investigation of the efficacy of clinically practical dual task tests as concussion assessment tool was performed by Finer. 2014. 54 healthy individuals were subjected to a physical task; expanded time-get-up-and-go (ETGUG) and three cognitive activities such as backward digital recall (BDR), serial sevens (SS) and auditory pure switch task (APST). Finer concluded that that response rate of SS and APST was declined when combined with ETGUG test. On the other hand, the response rate of BDR was comparatively enhanced when combined with ETGUG.
Patients with COPD
Bromboszcz et al. 2010 assessed ETGUG among patients with chronic obstructive pulmonary disease (COPD). In their study, a 20-meter walking distance was used for the test since it is the best metric to assess the walking abilities of patients. It emerged as a breakthrough because the typical testing for COPD such as 6MWT requires more walk distance.
Results and Data Analysis
The sample data represents the average time spent by healthy young, healthy adults, and at-risk adults to complete the entire course of the test. It is evident from Figure 2 that the time spent by the three groups is in the following order: At-risk adults > Adults > Young
Figure 2. TGUG and ETGUG test mean and standard deviation
The data for Figure 3, shows the time measured for each component in ETGUG test. It is observed that at-risk control group took a longer time to accomplish each task. Among all the components, Walk 1 shows significant difference among the three groups. While young and elderly group have a marginal difference, the at-risk group spent almost twice their time.
- Poor test-retest reliability was validated in older people with impaired mobility with the mean ICC of 0.06 (Botolfsen et al. 2008)
- Excellent test-retest reliability was observed by Ries et al. 2009 among people with Alzheimer’s disease with the mean interclass correlation coefficient of 0.987.
- Excellent test-retest reliability (Interclass correlation coefficient = 0.97 for community-dwelling elderly people) (Steffen et al. 2002)
- Good test-retest reliability was validated in individuals with various medical conditions with the mean ICC of 0.99 (Podsiadlo et al. 1991)
- Excellent test-retest reliability was observed by Kennedy et al. 2005 among patients with osteoarthritis with the mean Interclass correlation coefficient of 0.75.
- Adequate test-reliability (Interclass correlation coefficient = 0.85 for people with Parkinson’s disease) (Steffen et al. 2008)
- Excellent test-retest reliability was detected in people with Parkinson’s disease with the mean ICC of 0.80 (Huang et al. 2011)
- Excellent test-retest reliability was assessed by Flansbjer et al. 2005 among men and women with hemiparesis with the mean interclass correlation coefficient of 0.96.
- Excellent test-retest reliability (Interclass correlation coefficient = 0.86 for children with traumatic brain injury) (Katz-Leurer et al. 2008)
- Adequate test-retest reliability was observed in individuals with Parkinson’s disease with the mean ICC of 0.69 (Dal Bello-Haas et al. 2011)
- Excellent test-reliability was validated by Swanenburg et al. 2014 among patients with the bilateral vestibular loss with a mean interclass correlation coefficient of 0.85 to 0.95.
- Good test-retest reliability (interclass correlation coefficient = 0.65 for elderly patients performing physical exercises) (Virtuoso et al. 2014)
- Brooks et al. 2006 compared the Spearman’s correlation coefficients of the TUG and Functional reach. They observed that there was an adequate correlation between Timed-up-and-go (TUG) and functional reach (Spearman r = -0.36). On the other hand, there was an excellent correlation between TUG and two-minute walk test (2MWT) (Spearman r = -0.68).
- Maly et al. 2005 compared the Spearman’s correlation coefficients among patients with osteoarthritis. They observed that there was an excellent correlation between the TUG and STR (Stair Climbing Task) (Spearman r = 0.88).
- Boonstra et al. 2008 compared the Spearman’s correlation coefficients among individuals with osteoarthritis. They observed that there was an adequate correlation between TUG and Visual Analog Scale (VAS) for pain (Spearman r = 0.58).
- Brusse et al. 2005 compared the Spearman’s correlation coefficients among individuals with Parkinson’s disease. They observed excellent correlations between TUG and BBS (r = -0.78); TUG and FGS (r = -0.69); and TUG and CGS (r = -0.67).
- Van Hedel et al. 2005 compared the Spearman’s correlation coefficients among individuals with spinal cord injury. They observed excellent correlations between WISCI II and TUG (r= -0.76); TUG versus 10MWT (r = 0.89); and TUG versus 6MWT (r = -0.88).
- Knorr et al. 2010 compared Spearman’s correlation coefficients among community-dwelling persons after stroke. They observed excellent correlations between TUG and CB&M (ρ= -0.75, p < 0.001); and TUG and BBS (ρ = -0.70, p < 0.001).
- Lemay et al. 2010 compared Spearman’s correlation coefficients among individuals with acute spinal cord injury. They observed excellent correlations between TUG and Berg Balance Scale (r = -0.815); TUG and SCI-FAI parameter (r = -0.761); TUG and SCI-FAI assistive devices (r = -0.802); TUG and SCI-FAI mobility (r = -0.724); TUG and 2MWT (r = -0.623); TUG and WISCI II (r = -0.799); and lastly TUG and 10MWT (r = -0.646)
- Marchetti et al. 2011 compared Spearman’s correlation coefficients in community-dwelling older adults with vestibular disorders. They observed a strong correlation between TUG and AABC (r = -0.4,n = 98)
- Brown et al. 2001 observed fall risks on post rehabilitation among individuals with bilateral vestibular hypofunction using TUG (tug ≥ 13.5 sec; n= 6/9).
- Podsiadlo et al. 1991 compared Spearman’s correlation coefficients in elderly adults. They observed excellent correlations between TUG and Berg Balance (r= -0.81); TUG and gait speed (r = -0.61); TUG and Barthel Index of ADL (r = -0.78).
- Wrisley et al. 2010 compared Spearman’s correlation coefficient among elderly adults. They observed an excellent correlation between the TUG and Functional Gait Assessment (r = -0.84, p < 0.001).
- Sabirli t al. 2012 compared Spearman’s correlation coefficient among elderly adults with osteoarthritis. They observed an excellent correlation between the TUG and Kellengren-Lawrence radiological stages (r= 0.628).
- Bennie et al. 2003 compared the Spearman’s correlation coefficients among adults with Parkinson’s disease. They observed that there was a significant correlation between the TUG and BBS (r = -0.47, p = 0.04). On the other hand, there was also a significant correlation between combination of TUG and BBS with BBS (r = 0.56, p = 0.044)
- Flansbjer et al. 2005 compared the Spearman correlation coefficients among adults with chronic stroke. They observed that there was excellent correlations between TUG and CGS (r= -0.86), TUG and FGS (r = -0.91), TUG and SCas (r = 0.86), TUG and SCde (r = 0.90) and TUG and 6MW (r = 0.92).
- Gil-Body KM et al. 2000 compared the Spearman correlation coefficients among individuals with unilateral vestibular hypofunction. They observed a weak to moderate correlation between TUG scores and Dizziness Handicapped Inventory (r = 0.59).
- Meretta et al. 2006 compared the Spearman correlation coefficients among individuals with vestibular disorders. They observed adequate correlations between TUG and FTSST at baseline measurement (r= 0.53), TUG and FTSST at final measurement (r = 0.59) and TUG and FTSST change scores (r = 0.43),
- Caixeta GC et al. 2012 compared the Spearman correlation coefficients among vestibulopathy elderly patients. They observed a low yet significant correlation between the TUG and MMSE (Mini Mental State Exam) (r = -0.312).
- Excellent intra-rater reliability was validated in older people with impaired mobility with mean ICC of 0.97 (Botolfsen et al. 2008)
- Good intra-rater reliability was validated in community-dwelling elderly people with different medical conditions with mean ICC of 0.99 (Podsiadlo et al. 1991)
- Excellent inter-rater reliability was validated in individuals with Parkinson’s disease with mean ICC of 0.99 (Morris al, 2001)
- Excellent intra-rater reliability was validated in adults undergoing neuro rehab, skilled nursing and acute care with mean ICC of 0.98 (Bennie et al. 2003)
- Excellent intra-rater reliability was validated in older people living in residential care facilities with mean ICC of 0.92 (Nordin et al. 2006)
- Excellent inter-rater reliability was validated in adults with osteoarthritis with mean ICC of 0.87 (Wright et al. 2011)
- Rockwood et al. 2000 observed poor flooring effects (29%) while evaluating fitness and frailty among elderly adults.
- de Morton et al. 2008 observed poor flooring effects (25%) among older acute patients.
- Lin et al. 2004 observed a moderate effect for ADL decline (ES = 0.42) and small effects for falls (ES = 0.12) and DL improvements (ES = 0.05) among community-dwelling older adults.
- French et al. 2010 observed a small effect for response to physical therapy (ES = 0.33) among patients with osteoarthritis.
Strengths and Limitations
The timed-get-up-and-go task’s wide range of applicability makes it unique. It is a practical and reliable assessment tool to determine patient’s balance assessment. It can be used by clinicians with great ease as it requires minimal equipment and professional skills. This test screens functional deficiency that help the clinician in designing more productive intervention strategies. It is a promising tool to determine patient’s static and dynamic balance extensively. The specificity of the task is phenomenal as different components of balance assessment are evaluated rigorously.
Although widely used, but still further research is required to build a more robust correlation between increased component time and specific functional deficiency.
Summary and Key Points
- The “Timed Get-up-and-Go” (TGUG) test aim to assess the movement, balance, work capability and fall risk in older adults.
- It requires both static and dynamic balance. For the “Expanded Timed Get-up-and-Go” (ETGUG), a multi-memory stopwatch is used to measure the time it took for an individual to accomplish the task.
- This test has abundant applications.
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