Evidence map›Paper›PMID 34392429›Full record

SynthesisJournal of medical systems2021

Gait and Balance Assessments using Smartphone Applications in Parkinson's Disease: A Systematic Review.

Libak Abou, Joseph Peters, Ellyce Wong, Rebecca Akers, Mauricette Sènan Dossou, Jacob J Sosnoff, Laura A Rice

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of medical systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Libak AbouDepartment of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.ORCID http://orcid.org/0000-0001-6404-7623
Joseph PetersDepartment of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Ellyce WongDepartment of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Rebecca AkersDepartment of Rehabilitation Science, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Mauricette Sènan DossouCentre National Hospitalier et Universitaire de Pneumo-Phtisiologie, Cotonou, Littoral, Benin.
Jacob J SosnoffDepartment of Physical Therapy and Rehabilitation Science, School of Health Professions, Medical Center, University of Kansas, Kansas City, KS, USA.
Laura A RiceDepartment of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA. ricela@illinois.edu.ORCID http://orcid.org/0000-0003-3902-1151

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait dysfunctions and balance impairments are key fall risk factors and associated with reduced quality of life in individuals with Parkinson's Disease (PD). Smartphone-based assessments show potential to increase remote monitoring of the disease. This review aimed to summarize the validity, reliability, and discriminative abilities of smartphone applications to assess gait, balance, and falls in PD. Two independent reviewers screened articles systematically identified through PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss. Studies that used smartphone-based gait, balance, or fall applications in PD were retrieved. The validity, reliability, and discriminative abilities of the smartphone applications were summarized and qualitatively discussed. Methodological quality appraisal of the studies was performed using the quality assessment tool for observational cohort and cross-sectional studies. Thirty-one articles were included in this review. The studies present mostly with low risk of bias. In total, 52% of the studies reported validity, 22% reported reliability, and 55% reported discriminative abilities of smartphone applications to evaluate gait, balance, and falls in PD. Those studies reported strong validity, good to excellent reliability, and good discriminative properties of smartphone applications. Only 19% of the studies formally evaluated the usability of their smartphone applications. The current evidence supports the use of smartphone to assess gait and balance, and detect freezing of gait in PD. More studies are needed to explore the use of smartphone to predict falls in this population. Further studies are also warranted to evaluate the usability of smartphone applications to improve remote monitoring in this population.Registration: PROSPERO CRD 42020198510.

Indexed as

Gait Disorders, NeurologicParkinson DiseaseCross-Sectional StudiesGaitHumansPostural BalanceQuality of LifeReproducibility of ResultsSmartphoneGaitmHealthParkinson’s DiseasePostural controlSmartphone

Identifiers

PMID34392429
PMCPMC8364438

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.