The role of the occupational therapist in the training of cognitive functions in patients after stroke. Subtitle: Beds early rehabilitation
Bibliographic record
Abstract
This thesis deals with the effectiveness of individual vs. group cognitive therapies in stroke patients by training sheets, and pencil-paper exercises. The thesis is divided into theoretical and practical part. The theoretical part of the thesis describes the issue of this disease and the current study of cognitive training. The main aim of the practical part is to compare the effectiveness of group and individual cognitive training by means of intensive cognitive training in patients after stroke (within a year after a stroke). Another aim of the study is to find out how patients were satisfied with cognitive function by using the Schwartz scale of therapy. The study included 20 patients who were selected based on predetermined entry criteria. Subsequently, they were divided into two groups of 10 patients. Group 1 underwent individual cognitive therapy and group 2 underwent group therapy. In both groups, cognitive therapy was performed three times a week for one month. The time of one therapy was always 35-40 minutes. Patients were examined at baseline with the Montreal Cognitive Test and Schwartz's scale of therapy evaluation was added to the test at the end of the test. The results showed comparable improvements in the Montreal cognitive test in both groups. Furthermore, they showed comparable...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".