Evidence map›Paper›PMID 27506203›Full record

Trial reportJournal of neuroengineering and rehabilitation2016

Counteracting learned non-use in chronic stroke patients with reinforcement-induced movement therapy.

Belén Rubio Ballester, Martina Maier, Rosa María San Segundo Mozo, Victoria Castañeda, Armin Duff, Paul F M J Verschure

2 registry-linked trialsAbstract readRandomized Controlled Trial
In one paragraph

Trial report 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. It is linked to 2 registered trials, which are not on this map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 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.

NCT02657070 nacompletednot on this map

Desaprendiendo la parálisis Aprendida Con RGS en Pacientes Afectos de Ictus

TypeinterventionalSponsorUniversitat Pompeu FabraRan2014 to 2015Enrolled23ConditionsHemiparesisArmsReinforcement-Induced Movement Therapy (RIMT), VR-based motor rehabilitation in RGS without augmented feedback
NCT06885502 narecruitingnot on this mapstarted 2025, after this paper: background citation

Personalised Health Motor and Cognitive Assistance System for RehAbilitation (PHRASE): A Randomized Clinical Trial

TypeinterventionalSponsorEodyne Systems SLRan2025 to 2026Enrolled70ConditionsStroke, Stroke Rehabilitation, Chronic Stroke Patients, Post Stroke RecoveryArmsRGS
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  9. Volitional Control of the Paretic Hand Post-Stroke Increases Finger Stiffness and Resistance to Robot-Assisted Movement.Proceedings of the ... IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics · 2024
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  14. Autonomy support encourages use of more-affected arm post-stroke.Journal of neuroengineering and rehabilitation · 2023
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  16. Review
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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

6 authors.

Belén Rubio BallesterLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain.
Martina MaierLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain.
Rosa María San Segundo MozoServei de Medicina Física i Rehabilitació del, Hospital Universitari Joan XXIII de Tarragona, Tarragona, Spain.
Victoria CastañedaServei de Medicina Física i Rehabilitació del, Hospital Universitari Joan XXIII de Tarragona, Tarragona, Spain.
Armin DuffLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain.
Paul F M J VerschureLaboratory of Synthetic, Perceptive, Emotive and Cognitive Systems, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain. paul.verschure@upf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAfter stroke, patients who suffer from hemiparesis tend to suppress the use of the affected extremity, a condition called learned non-use. Consequently, the lack of training may lead to the progressive deterioration of motor function. Although Constraint-Induced Movement Therapies (CIMT) have shown to be effective in treating this condition, the method presents several limitations, and the high intensity of its protocols severely compromises its adherence. We propose a novel rehabilitation approach called Reinforcement-Induced Movement Therapy (RIMT), which proposes to restore motor function through maximizing arm use. This is achieved by exposing the patient to amplified goal-oriented movements in VR that match the intended actions of the patient. We hypothesize that through this method we can increase the patients self-efficacy, reverse learned non-use, and induce long-term motor improvements.

methodsWe conducted a randomized, double-blind, longitudinal clinical study with 18 chronic stroke patients. Patients performed 30 minutes of daily VR-based training during six weeks. During training, the experimental group experienced goal-oriented movement amplification in VR. The control group followed the same training protocol but without movement amplification. Evaluators blinded to group designation performed clinical measurements at the beginning, at the end of the training and at 12-weeks follow-up. We used the Fugl-Meyer Assessment for the upper extremities (UE-FM) (Sanford et al., Phys Ther 73:447-454, 1993) as a primary outcome measurement of motor recovery. Secondary outcome measurements included the Chedoke Arm and Hand Activity Inventory (CAHAI-7) (Barreca et al., Arch Phys Med Rehabil 6:1616-1622, 2005) for measuring functional motor gains in the performance of Activities of Daily Living (ADLs), the Barthel Index (BI) for the evaluation of the patient's perceived independence (Collin et al., Int Disabil Stud 10:61-63, 1988), and the Hamilton scale (Knesevich et al., Br J Psychiatr J Mental Sci 131:49-52, 1977) for the identification of improvements in mood disorders that could be induced by the reinforcement-based intervention. In order to study and predict the effects of this intervention we implemented a computational model of recovery after stroke.

resultsWhile both groups showed significant motor gains at 6-weeks post-treatment, only the experimental group continued to exhibit further gains in UE-FM at 12-weeks follow-up (p<.05). This improvement was accompanied by a significant increase in arm-use during training in the experimental group.

conclusionsImplicitly reinforcing arm-use by augmenting visuomotor feedback as proposed by RIMT seems beneficial for inducing significant improvement in chronic stroke patients. By challenging the patients' self-limiting believe system and perceived low self-efficacy this approach might counteract learned non-use.

trial registrationClinical Trials NCT02657070 .

Indexed as

Reinforcement, PsychologyAdultAgedChronic DiseaseComputer SimulationDouble-Blind MethodFemaleHumansMaleMiddle AgedMovementParesisPhysical Therapy ModalitiesRecovery of FunctionStrokeStroke RehabilitationDeductive medicineLearned non-useRehabilitationStrokeVirtual reality

Identifiers

PMID27506203
PMCPMC4979116

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.