Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22643
Title: Evaluation of upper extremity neurorehabilitation using technology: a European Delphi consensus study within the Eu COST Action Network on Robotics for Neurorehabilitation
Authors: Hughes, Ann-Marie
Boucas, Sofia Barbosa
Burridge,Jane
Murphy, Margit Alt
Buurke,Jaap
FEYS, Peter 
Klamroth-Marganska, Verena
LAMERS, Ilse 
Prange-Lasonder, Gerdienke
TIMMERMANS, Annick 
Keller, Thierry
Issue Date: 2016
Source: Journal of neuroengineering and rehabilitation, 13(86)
Abstract: Background: The need for cost-effective neurorehabilitation is driving investment into technologies for patient assessment and treatment. Translation of these technologies into clinical practice is limited by a paucity of evidence for cost-effectiveness. Methodological issues, including lack of agreement on assessment methods, limit the value of meta-analyses of trials. In this paper we report the consensus reached on assessment protocols and outcome measures for evaluation of the upper extremity in neurorehabilitation using technology. The outcomes of this research will be part of the development of European guidelines. Methods: A rigorous, systematic and comprehensive modified Delphi study incorporated questions and statements generation, design and piloting of consensus questionnaire and five consensus experts groups consisting of clinicians, clinical researchers, non-clinical researchers, and engineers, all with working experience of neurological assessments or technologies. For data analysis, two major groups were created: i) clinicians (e.g., practicing therapists and medical doctors) and ii) researchers (clinical and non-clinical researchers (e.g. movement scientists, technology developers and engineers). Results: Fifteen questions or statements were identified during an initial ideas generation round, following which the questionnaire was designed and piloted. Subsequently, questions and statements went through five consensus rounds over 20 months in four European countries. Two hundred eight participants: 60 clinicians (29 %), 35 clinical researchers (17 %), 77 non-clinical researchers (37 %) and 35 engineers (17 %) contributed. At each round questions and statements were added and others removed. Consensus (≥69 %) was obtained for 22 statements on i) the perceived importance of recommendations; ii) the purpose of measurement; iii) use of a minimum set of measures; iv) minimum number, timing and duration of assessments; v) use of technology-generated assessments and the restriction of clinical assessments to validated outcome measures except in certain circumstances for research. Conclusions: Consensus was reached by a large international multidisciplinary expert panel on measures and protocols for assessment of the upper limb in research and clinical practice. Our results will inform the development of best practice for upper extremity assessment using technologies, and the formulation of evidence-based guidelines for the evaluation of upper extremity neurorehabilitation.
Notes: Hughes, AM (reprint author), Univ Southampton, Fac Hlth Sci, Southampton, Hants, England. A.Hughes@soton.ac.uk
Keywords: neurology; assessment; upper extremity; rehabilitation technology; robotics; evaluation; outcome measures
Document URI: http://hdl.handle.net/1942/22643
e-ISSN: 1743-0003
DOI: 10.1186/s12984-016-0192-z
ISI #: 000384763100003
Rights: © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated
Category: A1
Type: Journal Contribution
Validations: ecoom 2017
Appears in Collections:Research publications

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