Can dual-task paradigms predict Falls better than single task? - A systematic literature review.

Ageing Attention Dual task (DT) Falls Gait Gait initiation (GI) Posture Turns

Journal

Neurophysiologie clinique = Clinical neurophysiology
ISSN: 1769-7131
Titre abrégé: Neurophysiol Clin
Pays: France
ID NLM: 8804532

Informations de publication

Date de publication:
Nov 2020
Historique:
received: 10 08 2020
revised: 06 10 2020
accepted: 06 10 2020
pubmed: 13 11 2020
medline: 16 9 2021
entrez: 12 11 2020
Statut: ppublish

Résumé

With about one third of adults aged 65 years and older being reported worldwide to fall each year, and an even higher prevalence with advancing age, aged-related falls and the associated disabilities and mortality are a major public health concern. In this context, identification of fall risk in healthy older adults is a key component of fall prevention. Since dual-task outcomes rely on the interaction between cognition and motor control, some studies have demonstrated the role of dual-task walking performance or costs in predicting future fallers. However, based on previous reviews on the topic, (1) discriminative and (2) predictive powers of dual tasks involving gait and a concurrent task are still a matter of debate, as is (3) their superiority over single tasks in terms of fall-risk prediction. Moreover, less attention has been paid to dual tasks involving postural control and transfers (such as gait initiation and turns) as motor tasks. In the present paper, we therefore systematically reviewed recent literature over the last 7 years in order to answer the three above mentioned questions regarding the future of lab-based dual tasks (involving posture, gait initiation, gait and turning) as easily applicable tests for identifying healthy older adult fallers. Despite great heterogeneity among included studies, we emphasized, among other things, the promising added value of dual tasks including turns and other transfers, such as in the Timed Up and Go test, for prediction of falls. Further investigation of these is thus warranted.

Identifiants

pubmed: 33176988
pii: S0987-7053(20)30118-0
doi: 10.1016/j.neucli.2020.10.008
pii:
doi:

Types de publication

Journal Article Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

401-440

Commentaires et corrections

Type : ErratumIn

Informations de copyright

Copyright © 2020 Elsevier Masson SAS. All rights reserved.

Auteurs

Madli Bayot (M)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Clinical Neurophysiology, F-59000 Lille, France.

Kathy Dujardin (K)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Neurology and Movement Disorders, F-59000 Lille, France.

Lucile Dissaux (L)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Clinical Neurophysiology, F-59000 Lille, France.

Céline Tard (C)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Neurology and Movement Disorders, F-59000 Lille, France.

Luc Defebvre (L)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Neurology and Movement Disorders, F-59000 Lille, France.

Cédrick T Bonnet (CT)

Univ. Lille, UMR 9193 - SCALab - Sciences Cognitives et Sciences Affectives, CNRS UMR 9193, F-59000 Lille, France.

Etienne Allart (E)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Neurorehabilitation Unit, F-59000 Lille, France.

Gilles Allali (G)

Department of Neurology, Geneva University Hospitals and University of Geneva, Geneva 1211, Switzerland, Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, US.

Arnaud Delval (A)

Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Department of Clinical Neurophysiology, F-59000 Lille, France. Electronic address: arnaud.delval@chru-lille.fr.

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Classifications MeSH