Imagined Timed Up and Go test (iTUG) in people with Parkinson’s Disease: test-retest reliability and validity

PURPOSE To determine the test-retest reliability and validity of the Imagined Timed Up and Go Test (iTUG) as a Motor Imagery measure of temporal accuracy in people with Parkinson's Disease (PD). MATERIALS AND METHODS A descriptive study was conducted following the GRRAS recommendations. Thirty-two people with idiopathic, mild to moderate PD (Hoehn and Yahr I-III), without cognitive impairment (MMSE ≥ 24), were assessed twice (7-15 days apart) with the iTUG. The absolute unadjusted difference in seconds, and the absolute adjusted difference as percentage of estimation error, between real and imagined TUG times, were calculated as outcome measures. Test-retest reliability was assessed using a two-way mixed-effects model of the ICC. Construct validity was tested with the Imagined Box and Blocks Test (iBBT) and convergent validity with clinical characteristics of PD, using the Spearman's rank correlation coefficient. RESULTS The ICC for the unadjusted and adjusted measures of the iTUG was ICC = 0.61 and ICC = 0.55, respectively. Correlations between iTUG and iBBT were not statistically significant. The iTUG was partially correlated to clinical characteristics of PD. CONCLUSIONS Test-retest reliability of the iTUG was moderate. Construct validity between iTUG and iBBT was poor, so caution should be taken when using them concurrently to assess imagery's temporal accuracy.

[1]  R. Vale,et al.  Effects of Motor Imagery as a Complementary Resource on the Rehabilitation of Stroke Patients: A Meta-Analysis of Randomized Trials. , 2021, Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association.

[2]  A. Zeman,et al.  Behavioral and Neural Signatures of Visual Imagery Vividness Extremes: Aphantasia versus Hyperphantasia , 2021, Cerebral cortex communications.

[3]  Wilma A. Bainbridge,et al.  Quantifying aphantasia through drawing: Those without visual imagery show deficits in object but not spatial memory , 2019, Cortex.

[4]  O. Gerke.  Reporting Standards for a Bland–Altman Agreement Analysis: A Review of Methodological Reviews , 2020, Diagnostics.

[5]  Sarah N. Kraeutner,et al.  Generate, maintain, manipulate? Exploring the multidimensional nature of motor imagery , 2020 .

[6]  Kazuyuki Kanosue,et al.  Vividness and accuracy: Two independent aspects of motor imagery , 2019, Neuroscience Research.

[7]  J. Keogh,et al.  Motor imagery training improves balance and mobility outcomes in older adults: a systematic review. , 2019, Journal of physiotherapy.

[8]  M. Bang,et al.  Target-oriented motor imagery for grasping action: different characteristics of brain activation between kinesthetic and visual imagery , 2019, Scientific Reports.

[9]  S. Swinnen,et al.  Neural correlates of action: Comparing meta-analyses of imagery, observation, and execution , 2018, Neuroscience & Biobehavioral Reviews.

[10]  G. Allali,et al.  Age and gender differences in motor imagery , 2018, Journal of the Neurological Sciences.

[11]  Sarah N. Kraeutner,et al.  Experience modulates motor imagery‐based brain activity , 2018, The European journal of neuroscience.

[12]  A. Sterr,et al.  The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research—A Behavioral Study , 2018, Front. Hum. Neurosci..

[13]  D. Matsuzawa,et al.  Comparison of brain activity between motor imagery and mental rotation of the hand tasks: a functional magnetic resonance imaging study , 2018, Brain Imaging and Behavior.

[14]  C. Papaxanthis,et al.  The influence of imagery capacity in motor performance improvement , 2017, Experimental Brain Research.

[15]  K. Takakusaki.  Functional Neuroanatomy for Posture and Gait Control , 2017, Journal of movement disorders.

[16]  Kazuyuki Kanosue,et al.  Task-dependent engagements of the primary visual cortex during kinesthetic and visual motor imagery , 2017, Neuroscience Letters.

[17]  Daniele Caligiore,et al.  Action observation and motor imagery for rehabilitation in Parkinson's disease: A systematic review and an integrative hypothesis , 2017, Neuroscience & Biobehavioral Reviews.

[18]  Terry K Koo,et al.  A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. , 2016, Journal of chiropractic medicine.

[19]  Takashi Hanakawa,et al.  Organizing motor imageries , 2016, Neuroscience Research.

[20]  H. Nakata,et al.  Motor imagery beyond the motor repertoire: Activity in the primary visual cortex during kinesthetic motor imagery of difficult whole body movements , 2016, Neuroscience.

[21]  Paul J. Stapley,et al.  A prolonged motor imagery session alter imagined and actual movement durations: Potential implications for neurorehabilitation , 2016, Behavioural Brain Research SreeTestContent1.

[22]  A. Guillot,et al.  Comparing self-report and mental chronometry measures of motor imagery ability , 2015, European journal of sport science.

[23]  R. Newman-Norlund,et al.  Biological evidence of imagery abilities: intraindividual differences. , 2015, Journal of sport & exercise psychology.

[24]  A. Guillot,et al.  Impact of Neurologic Deficits on Motor Imagery: A Systematic Review of Clinical Evaluations , 2014, Neuropsychology Review.

[25]  J. Liepert,et al.  Assessment of mental chronometry (MC) in healthy subjects. , 2014, Archives of gerontology and geriatrics.

[26]  Patrik Vuilleumier,et al.  The influence of individual motor imagery ability on cerebral recruitment during gait imagery , 2014, Human brain mapping.

[27]  W. Helsen,et al.  Evaluation of motor imagery ability in neurological patients: a review , 2013 .

[28]  K. Takakusaki.  Neurophysiology of gait: From the spinal cord to the frontal lobe , 2013, Movement disorders : official journal of the Movement Disorder Society.

[29]  Tetsuro Muraoka,et al.  Brain activity during motor imagery of an action with an object: A functional magnetic resonance imaging study , 2013, Neuroscience Research.

[30]  Joe R. Nocera,et al.  Using the Timed Up & Go test in a clinical setting to predict falling in Parkinson's disease. , 2013, Archives of physical medicine and rehabilitation.

[31]  J. Jankovic,et al.  How to identify tremor dominant and postural instability/gait difficulty groups with the movement disorder society unified Parkinson's disease rating scale: Comparison with the unified Parkinson's disease rating scale , 2013, Movement disorders : official journal of the Movement Disorder Society.

[32]  G Y Zou,et al.  Sample size formulas for estimating intraclass correlation coefficients with precision and assurance , 2012, Statistics in medicine.

[33]  A. Guillot,et al.  Selective Effect of Physical Fatigue on Motor Imagery Accuracy , 2012, PloS one.

[34]  J. Liepert,et al.  Reduced Upper Limb Sensation Impairs Mental Chronometry for Motor Imagery After Stroke , 2012, Neurorehabilitation and neural repair.

[35]  W. Helsen,et al.  Motor Imagery Ability in Patients With Early- and Mid-Stage Parkinson Disease , 2011, Neurorehabilitation and neural repair.

[36]  A. Hrõbjartsson,et al.  Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. , 2011, Journal of clinical epidemiology.

[37]  Cédric Annweiler,et al.  Imagined Timed Up & Go test: A new tool to assess higher-level gait and balance disorders in older adults? , 2010, Journal of the Neurological Sciences.

[38]  J. Pratt,et al.  Fitts’s Law violation and motor imagery: are imagined movements truthful or lawful? , 2010, Experimental Brain Research.

[39]  Ana Solodkin,et al.  Imaging motor imagery: methodological issues related to expertise. , 2008, Methods.

[40]  Julien Doyon,et al.  Functional neuroanatomical networks associated with expertise in motor imagery , 2008, NeuroImage.

[41]  Julien Doyon,et al.  Reliability of mental chronometry for assessing motor imagery ability after stroke. , 2008, Archives of physical medicine and rehabilitation.

[42]  A. Guillot,et al.  Contribution from neurophysiological and psychological methods to the study of motor imagery , 2005, Brain Research Reviews.

[43]  J. Hughes,et al.  Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases. , 1992, Journal of neurology, neurosurgery, and psychiatry.

[44]  Diane Podsiadlo,et al.  The Timed “Up & Go”: A Test of Basic Functional Mobility for Frail Elderly Persons , 1991, Journal of the American Geriatrics Society.

[45]  V. Mathiowetz,et al.  Adult norms for the Box and Block Test of manual dexterity. , 1985, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[46]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.