Motor Learning and the Use of Videotape Feedback After Stroke
Bibliographic record
Abstract
BACKGROUND: Efforts have been made to apply motor learning theories to the rehabilitation of individuals following stroke. Motor learning poststroke has not been well investigated in the literature. This research attempted to fill the gap regarding motor learning applied to practice. PURPOSE: This two-group research study attempted to determine the effectiveness of an experimental therapy combining videotape feedback with occupational therapy compared to only occupational therapy in learning the motor skill of donning socks and shoes after stroke. METHOD: Ten participants were randomly assigned to one of the two groups and all participants were videotaped during pretest and up to 10 treatment sessions aimed at donning socks and shoes. Only one group viewed their videotape replay. The acquisition of donning socks and shoes was measured using the socks and shoes subtests of the Klein-Bell Activities of Daily Living Scale and their scores on the Canadian Occupational Performance Measure. RESULTS: There was no significant difference between the two groups and both groups improved. However, the group that received videotape feedback thought they performed better and were more satisfied with their ability to don shoes, lending support for the use of videotape feedback poststroke to improve satisfaction with performance.
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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 | 0.002 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".