Problematic Areas in the Everyday Life of Patients with Huntington's Disease. Subtitle: A Suggestion of Compensatory Strategies in Coping with Cognitive Impairment
Bibliographic record
Abstract
This diploma thesis explores problematic areas of patients with Huntington's disease in their performance during activities of daily living (ADLs) from the perspective of patients and their caregivers. The aim of the research was also to assess a possible correlation between cognitive impairment and the patient's performance in ADL. Twenty-five patients with their caregivers met the selection criteria for the research. There were used standardized assessment methods available in Czech: the Montreal Cognitive Assessment (MoCA), the Canadian Occupational Performance Measure (COPM) and the questionnaire for caregivers called Bristol Activities of Daily Living Scale (BADLS-CZ). The statistical analyses consisted of methods of the nonparametric statistics, qualitative analysis was processed by data categorizing. Caregivers reported more problematic areas in ADLs which was significantly confirmed in the statistical hypothesis testing (p <0,05). A significant correlation was seen between the results of the questionnaire and the results of the MoCA assessment (rSp = -0,620; p <0,05). For various reasons, patients with Huntington's disease did not mention as many problematic areas in performing ADL as their caregivers. Therefore, it is appropriate in clinical practice to supplement the assessment of the patient's...
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".