Modified Constraint-Induced Therapy: A Promising Restorative Outpatient Therapy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Stroke is the leading cause of disability in the United States, and upper limb hemiparesis is a primary impairment resulting in this disability. However, there remains a paucity of scientifically validated treatment regimens for hemiparesis. Data from randomized controlled studies suggest the effectiveness and efficacy of modified constraint-induced therapy (mCIT), a reimbursable, outpatient, upper limb training regimen. The purpose of this article is to review evidence and discuss the theoretical bases of mCIT for stroke-induced hemiparesis. The objective is to make stroke practitioners aware of the mCIT theoretical bases and of this clinically practical, efficacious protocol. CONCLUSIONS: mCIT is solidly grounded in motor learning principles, is practical and safe, and is both efficacious and effective. mCIT studies have shown efficacy using rigorous randomized controlled methods in both subacute and chronic stroke and have shown high effect sizes that have been independently confirmed. It thus seems reasonable to recommend mCIT for clinical application.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".