2015
DOI: 10.1123/jab.2013-0319
|View full text |Cite
|
Sign up to set email alerts
|

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

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 t… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
76
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
7
2
1

Relationship

0
10

Authors

Journals

citations
Cited by 93 publications
(83 citation statements)
references
References 19 publications
(23 reference statements)
0
76
0
Order By: Relevance
“…Ambulatory assessment is more representative of people’s gait. Indeed, the environment with ILG is physiological; hours of walking at different times of day can be recorded, which is key to valid interpretation of pattern and rhythm variability parameters that assess gait at a macro-level (Robles-García et al, 2015); and the putative “white-coat” syndrome (Andrzejewski et al, 2016) is avoided. Nevertheless, ambulatory data extraction and analysis entail great challenges because various algorithms have been developed for controlled testing, and their validity in this uncontrolled environment is questioned.…”
Section: Discussionmentioning
confidence: 99%
“…Ambulatory assessment is more representative of people’s gait. Indeed, the environment with ILG is physiological; hours of walking at different times of day can be recorded, which is key to valid interpretation of pattern and rhythm variability parameters that assess gait at a macro-level (Robles-García et al, 2015); and the putative “white-coat” syndrome (Andrzejewski et al, 2016) is avoided. Nevertheless, ambulatory data extraction and analysis entail great challenges because various algorithms have been developed for controlled testing, and their validity in this uncontrolled environment is questioned.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, utilising wearable activity monitors permits continuous patient monitoring by allowing data collection in the patient's own home [15]. These out-of-clinic data may provide a more accurate representation of the patient's ability, as some patients perform better in the clinical environment when under the observation of a clinician [16], while others perform better in the familiar environment of their own home. This approach also has the potential to reduce the burden on both the patient and the clinical site by decreasing the utilisation of valuable resources.…”
Section: Introductionmentioning
confidence: 99%
“…BWM allow for prolonged data capture which is essential for fluctuating pathologies such as Parkinson's disease (PD). In addition, data can be collected in habitual environments reducing the influence of Hawthorne effect [9].…”
Section: Introductionmentioning
confidence: 99%