The Effect of ICF-Core Set-Based Occupational Therapy Interventions on the Function and Satisfaction of Individuals with Chronic Stroke: A Randomized Clinical Trial
Bibliographic record
Abstract
Stroke can affect all aspects of a person's health and functioning. Therefore, it is important occupational therapists, have a comprehensive understanding of various levels of function and the factors affecting function. The ICF (International Classification of Functioning, Disability, and Health) and the selections of ICF categories or Core Sets relevant for people with a specific health condition, offer a model for intervention. This study aimed to investigate the effect of ICF-CS-based occupational therapy interventions on the function and satisfaction of individuals with chronic stroke. This study was designed as a randomized, single-blind, parallel-group clinical trial. Twenty-five patients with stroke were randomly assigned to the control group (which received traditional occupational therapy) or the treatment group (Stroke ICF-CS based occupational therapy). Patients were evaluated before and after the intervention (two months, three sessions per week, 45 minutes each session), as well as two weeks after the end of the intervention, using Fugl-Meyer and COPM (Canadian Occupational Performance Measure) tools. The independent T-test, Chi-square, and ANOVA with repeated measures were used to analyze the data. The results showed that the interaction effect of time and group was not significant in none of the Fugl-Meyer test sections (p > 0. 05), but it was significant in the performance and satisfaction of COPM (p < 0.05). The results suggest that ICF-CS-based occupational therapy interventions may assist persons with chronic stroke improve their functional level and satisfaction.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".