Effects of Mindmap Program on Cognitive Function and Occupational Participation of Stroke Patients
Bibliographic record
Abstract
Objective : This study attempted to present the basis of the mindmap program as an intervention method for stroke rehabilitation by confirming changes in cognitive function and occupational participation after applying the mindmap program to stroke patients. Methods : This study involved 20 stroke patients, and after dividing into two groups through randomization, the experimental group applied the mindmap program and the control group applied the cognitive training program for a total of 12 sessions (30 minutes per day, 3 times a week, 4 weeks). Cognitive function was measured using the Korean version of Montreal Cognitive Assessment (MoCA-K), and occupational participation was measured using the Model Of Human Occupation Screening Tool (MOHOST). Results : Before the intervention, the MoCA-K and MOHOST scores between the two groups showed no significant differences (p>.05). Significant changes were found between the MoCA-K and MOHOST scores before and after each intervention in both groups (p<.05). After the intervention, the MoCA-K and MOHOST difference scores between the two groups showed a significant difference (p<.05), and the difference scores of the experimental group were higher than those of the control group. Conclusion : Through this study, it was confirmed that the mindmap program is effective in improving cognitive function and occupational participation of stroke patients. It is expected that the mindmap program will be used as an intervention method for a balanced life of stroke patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".