The Effects of multicomponent exercise on mild cognitive impairment in elderly population: a randomized control trial
Bibliographic record
Abstract
Objective: The study was aimed to find out effects of multicomponent exercise on mild cognitive impairment in older adults. Methodology: A randomized control trail was conducted at Department of Rehabilitation at Pakistan Railway General Hospital, Rawalpindi. Fifty eight older persons with mild cognition impairment randomly divided in to two groups. The participants of the experimental group (n=29) performed multicomponent exercises two times in a week, 55-60 minute for 6 weeks. The participants of the control group (n=29) performed thrice a week ;20 minutes treadmill walk for 6 weeks. The participants were assessed at baseline and after 6 week of intervention for the following test: Mini-mental state examination (MMSE), Montreal Cognitive Assessment (MoCA), Trail-making test A (TMT-A) and Trail making test-B (TMT-B). Data was analyzed using SPSS 21. Results: The overall mean age of study participants was 62.74±74 years. Within group analysis for MMSE, MoCA, TMT-A and TMT-B significantly improved (p <0.05) in experimental group as compared to control group. Between group analysis showed that all parameters were significantly improved (P <0.05) at post intervention assessment. Conclusion: Multicomponent exercise training was found to be effective in older adults with mild cognitive impairment. Combination of exercise can enhance cognitive function, help in the prevention of the decline in cognitive function and moreover reduce the risk for dementia. Trial Registration number: NCT03938051
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".