The Effect of Dual task Program on Reducing the Risk of Dementia in older Adults
Bibliographic record
Abstract
Background/Objectives: The purpose of this study was to assess the effect of a dual task program on prevention to dementia in old adult. Methods/Statistical analysis: Forty-four people were selected as subjects with a high risk of developing dementia. Using a Korean version of the Montreal Cognitive Assessment, cognitive function was recorded; the Short Form of the Geriatric Depression Scale and the Korean version of the Quality of Life-Alzheimer’s Disease were administered pre- and post-evaluation to determine the changes in levels of depression and quality of life. Paired t tests were conducted using SPSS Version 12.0. Findings: The results indicated that the dual task program affected cognitive function and quality of life in older adults with a higher risk of developing dementia. The level of depression decreased after the intervention, but there was no statistically significant difference. In these studies, dual task programs included the synchronized use of both hands, integration of the bilateral side, and bimanual activity of inserting to facilitate cognitive function. Additionally, through the process of making procedures, the dual task program consisted of contents that enhance cognitive functions and motor functions. As a result, the dual task has been shown to be effective in preventing dementia. The dual task program was designed to improve cognitive functions and quality of life of those in an older population with a higher risk of developing dementia. Improvements/Applications: Applying the dual task program to elderly subjects at a high risk of developing dementia was confirmed to prevent dementia.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".