Evidence map›Paper›PMID 27663356›Full record

ArticleJournal of neuroengineering and rehabilitation2016

Evaluation of upper extremity neurorehabilitation using technology: a European Delphi consensus study within the EU COST Action Network on Robotics for Neurorehabilitation.

Ann-Marie Hughes, Sofia Barbosa Bouças, Jane H Burridge, Margit Alt Murphy, Jaap Buurke, Peter Feys, Verena Klamroth-Marganska, Ilse Lamers, Gerdienke Prange-Lasonder, Annick Timmermans and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
12.5field-weighted citation impact, top 2% of its field
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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 26 citations in OpenAlex.

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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

11 authors at 7 institutions in 6 countries.

Ann-Marie HughesFaculty of Health Sciences, University of Southampton, Southampton, UK. A.Hughes@soton.ac.uk.ORCID http://orcid.org/0000-0002-3958-8206
Sofia Barbosa BouçasDepartment of Psychology, School of Health & Social Sciences, Buckinghamshire New University, High Wycombe, UK.
Jane H BurridgeFaculty of Health Sciences, University of Southampton, Southampton, UK.
Margit Alt MurphyInstitute of Neuroscience and Physiology, Rehabilitation Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Jaap BuurkeRoessingh Research and Development, Enschede, The Netherlands.
Peter FeysREVAL- Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium.
Verena Klamroth-MarganskaSensory Motor Systems Lab, Department of Health Science and Technologies, Swiss Federal Institute of Technology, Zurich, Switzerland.
Ilse LamersREVAL- Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium.
Gerdienke Prange-LasonderRoessingh Research and Development, Enschede, The Netherlands.
Annick TimmermansREVAL- Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium.
Thierry KellerNeurorehabilitation Department, Health Division, TECNALIA Research & Innovation, Donostia-San Sebastián, Spain.
Hasselt University · BERoessingh Research and Development · NLUniversity of Southampton · GBBuckinghamshire New University · GBÉcole Polytechnique Fédérale de Lausanne · CHTecnalia · ESUniversity of Gothenburg · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsA 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).

resultsFifteen 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.

conclusionsConsensus 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.

Indexed as

AssessmentEvaluationNeurologyOutcome measuresRehabilitation technologyRoboticsUpper extremity

Identifiers

PMID27663356
PMCPMC5035444
OpenAlexW2521332869

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.