Exploring a cognitive-based treatment approach to improve motor-based skill performance in chronic stroke: Results of three single case experiments
Bibliographic record
Abstract
PRIMARY OBJECTIVE: Early evidence suggests the use of cognitive strategies has potential to improve skill performance in people living with the effects of stroke, but no specific protocol has been identified. This study aimed to explore the potential of using the Cognitive Orientation to daily Occupational Performance (CO-OP) protocol to improve the functional performance of adults with chronic stroke. RESEARCH DESIGN AND METHODS: A single case experimental design study with two replications was conducted. Three community-dwelling participants were recruited. Each selected three functional goals for the focus of the CO-OP intervention. Multiple video recorded data points were collected at baseline, during intervention, post-intervention and at 1-month follow-up. RESULTS: The nine goals selected varied widely, e.g. using a computer mouse, bicycling and yoga. An independent observer used the observational Performance Quality Rating Scale (PQRS) to rate performances throughout. Using the 2 SD band method to analyse the data, each participant showed significant performance improvements in at least two goals during the course of the intervention and at follow-up. Two participants had an additional goal show significant improvement at follow-up. CONCLUSION: Results provide preliminary evidence that CO-OP is associated with significant performance improvements in self-selected functional goals.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".