Literature DB >> 25536440

Spatiotemporal Gait Patterns During Overt and Covert Evaluation in Patients With Parkinson´s Disease and Healthy Subjects: Is There a Hawthorne Effect?

Verónica Robles-García1, Yoanna Corral-Bergantiños, Nelson Espinosa, María Amalia Jácome, Carlos García-Sancho, Javier Cudeiro, Pablo Arias.   

Abstract

Parkinson's disease (PD) and aging lead to gait impairments. Some of the disturbances of gait are focused on step length, cadence, and temporal variability of gait cycle. Under experimental conditions gait can be overtly evaluated, but patients with PD are prone to expectancy effects; thus it seems relevant to determine if such evaluation truly reflects the spontaneous gait pattern in such patients, and also in healthy subjects. Thirty subjects (15 subjects with PD and 15 healthy control subjects) were asked to walk using their natural, preferred gait pattern. In half of the trials subjects were made aware that they were being evaluated (overt evaluation), while in the rest of the trials the evaluation was performed covertly (covert evaluation). During covert evaluation the gait pattern was modified in all groups. Gait speed was significantly increased (P = .022); step cadence and average step length were also significantly modified, the average step length increased (P = .002) and the cadence was reduced (P ≤ .001). Stride cycle time variability was unchanged significantly (P = .084). These changes were not significantly different compared between elderly and young healthy controls either. Due to the small sample size, a note of caution is in order; however, the significant results suggest that covert evaluation of gait might be considered to complement experimental evaluations of gait.

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Year:  2014        PMID: 25536440     DOI: 10.1123/jab.2013-0319

Source DB:  PubMed          Journal:  J Appl Biomech        ISSN: 1065-8483            Impact factor:   1.833


  30 in total

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2.  Hawthorne Effect in Gait Analysis of Children with In-Toeing Caused by Increased Femoral Anteversion.

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3.  Measuring Gait Parameters from Structural Vibrations.

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4.  Accuracy of Step Count Estimations in Parkinson's Disease Can Be Predicted Using Ambulatory Monitoring.

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5.  Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score.

Authors:  Andong Zhan; Srihari Mohan; Christopher Tarolli; Ruth B Schneider; Jamie L Adams; Saloni Sharma; Molly J Elson; Kelsey L Spear; Alistair M Glidden; Max A Little; Andreas Terzis; E Ray Dorsey; Suchi Saria
Journal:  JAMA Neurol       Date:  2018-07-01       Impact factor: 18.302

6.  Free-living gait characteristics in ageing and Parkinson's disease: impact of environment and ambulatory bout length.

Authors:  Silvia Del Din; Alan Godfrey; Brook Galna; Sue Lord; Lynn Rochester
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7.  Training for Micrographia Alters Neural Connectivity in Parkinson's Disease.

Authors:  Evelien Nackaerts; Jochen Michely; Elke Heremans; Stephan P Swinnen; Bouwien C M Smits-Engelsman; Wim Vandenberghe; Christian Grefkes; Alice Nieuwboer
Journal:  Front Neurosci       Date:  2018-01-19       Impact factor: 4.677

Review 8.  Physical Activity Monitoring in Patients with Neurological Disorders: A Review of Novel Body-Worn Devices.

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Journal:  Digit Biomark       Date:  2017-06-12

9.  Improvements in clinical signs of Parkinson's disease using photobiomodulation: a prospective proof-of-concept study.

Authors:  Ann Liebert; Brian Bicknell; E-Liisa Laakso; Gillian Heller; Parastoo Jalilitabaei; Sharon Tilley; John Mitrofanis; Hosen Kiat
Journal:  BMC Neurol       Date:  2021-07-02       Impact factor: 2.474

10.  Amplitude Manipulation Evokes Upper Limb Freezing during Handwriting in Patients with Parkinson's Disease with Freezing of Gait.

Authors:  Elke Heremans; Evelien Nackaerts; Griet Vervoort; Sarah Vercruysse; Sanne Broeder; Carolien Strouwen; Stephan P Swinnen; Alice Nieuwboer
Journal:  PLoS One       Date:  2015-11-18       Impact factor: 3.240

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