Constraint-Induced Movement Therapy With or Without Neuromuscular Electrical Stimulation Versus Conventional Therapy for Upper Extremity Function in Chronic Stroke Survivors: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Motor impairment is a common consequence of stroke, significantly impacting patients' daily functioning and quality of life. More than 80% of stroke survivors experience upper extremity (UE) motor impairments, which severely impact their ability to carry out daily living activities. Combining motor rehabilitation techniques, such as constraint-induced movement therapy (CIMT), with sensorimotor stimulation methods, such as neuromuscular electrical stimulation (NMES), may be beneficial in enhancing UE functional recovery after a stroke. This combined approach could activate a broader range of brain regions, improving motor control. However, evidence for the effectiveness of these interventions when combined is still lacking. OBJECTIVE: In this randomized controlled trial, we aim to determine the effectiveness of CIMT combined with NMES, CIMT alone, and conventional therapy in rehabilitating UE function in chronic stroke survivors. METHODS: We will compare 3 intervention groups, 2 experimental groups (CIMT combined with NMES group and CIMT group) and 1 control group (conventional therapy), in this assessor-blinded, cluster randomized controlled trial. A total of 42 participants will be recruited and randomly assigned to 1 of the 3 groups. Participants in the CIMT group will undergo 6 shaping practice tasks (50 repetitions for each task, totaling 300 repetitions per session). The combined CIMT/NMES group will perform tasks similar to those carried out by the CIMT-only group, and a biofeedback electrical stimulator for NMES will also be provided. The control group will receive conventional neurodevelopmental therapy. All groups will receive 1 session per day of treatment for 3 consecutive days a week for 4 weeks. A blinded assessor will measure the interventions' outcomes using standardized tests, including UE motor function, motor impairment, perceived motor function, and upper limb self-efficacy. All data will be analyzed descriptively, presenting the means and SDs. We will conduct inferential tests using a 2-way mixed ANOVA to evaluate the effects of the interventions and compare them between and within groups. RESULTS: Funding for this study was provided by the Research and Ethics Committee of the Universiti Kebangsaan Malaysia (the National University of Malaysia) starting in November 2023. Between January 2023 and May 2023, we developed the initial ethics proposal and recruited research staff. Research ethics applications were submitted to the Research and Ethics Committee of the Universiti Kebangsaan Malaysia from May 2023 to November 2023. We anticipate publishing the study results in September 2025. CONCLUSIONS: This trial will provide insights into the effectiveness of CIMT combined with NMES, CIMT alone, and conventional therapy for UE rehabilitation in stroke survivors. Findings will be published in a peer-reviewed journal, and any updates based on emerging evidence will be provided. Any changes to the study methods will be documented in the final publication. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12624000564550; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=387308.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.053 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".