THE CORRELATION OF COGNITIVE FUNCTION TO BRAIN GYM IN THE ELDERLY
Bibliographic record
Abstract
Background: A decline in cognitive function is often considered normal in the elderly, but the advanced stages of cognitive decline can decrease the ability to perform functional activities. Brain gym is one of the physical activity therapies that is proven to improve cognitive function. The purpose of this study is to know the effect of brain gym on cognitive function. Objective: This study aims to determine the correlation of cognitive function to brain gym in elderly. Methods: This is a queasy experimental study in 70 respondent with a pre and post-test group design. The subjects were elderly who were examined with Montreal Cognitive Assessment Indonesian (MoCA-Ina) and Visual Reproduction Test (VRT) on the first day and given brain gym 13 times, which was done 2 times in 1 week and re-examined MoCA-Ina and VRT after the intervention. Results: The research results show improvement in the MoCA-Ina and VRT pre and post-examinations after being given intervention. In the MoCA-INA examination, the mean score of the pretest was 23.30 and the mean score of the post-test was 24.50, while in the VRT examination, the mean score of the pretest was 10.08, and the post-test mean score was 10.83. However, there was no significant difference between MoCA-Ina or VRT in pre- and post-interventional brain gym (p>0.05). Conclusion: There is a relationship between cognitive function which is marked by an increase in the results of Moca INA and VRT with brain gym in the elderly at Balearjosari Malang
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".