Multi-component exercise training improves the physical and cognitive function of the elderly with mild cognitive impairment: a six-month randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: This study explored the effects of multi-component exercise training on the physical and cognitive function of the elderly with mild cognitive impairment (MCI). METHODS: A total of 90 older adults with MCI were chosen from screened volunteers and randomly assigned into 2 groups (n=45), and 84 completed the 6-month follow-up. Participants in the control group received general community health instruction, while the multi-component exercise training performed on the other group. The multi-component exercise training performed on these participants was designed to suit Chinese elderly based on advice from the nursing specialist and sports medicine specialist after the preliminary experiment. The Chinese version Mini-Physical Performance Test (CM-PPT), the Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA) scores were examined by repeated measures analysis of variance to evaluate the physical and cognitive function of adults with MCI before and at 3 and 6 months after the intervention. The follow-up data collectors were blinded to group allocation. P<0.05 was considered statistically significant. RESULTS: (I) The average score of CM-PPT was increased from 11.36±2.69 to 11.88±2.40 and 12.83±2.19 in 3 and 6 months respectively after intervention, while control group was decreased from 10.79±2.73 to 10.24±2.62 in 3 months and 9.21±2.09 in 6 months. CM-PPT scores with the main intervention effect and the interaction between intervention and time were both statistically significant (P<0.05), indicating that the physical function of participants with MCI were improved after intervention. (II) The average score of MoCA was increased from 21.52±2.05 to 23.48±1.47 (3 months) and 25.19±1.29 (6 months) after intervention, while control group was decreased from 21.14.79±1.97 to 20.21±1.88 and 19.45±2.00 in 3 and 6 months. The score of MMSE showed the same trend with the score of MoCA. The MoCA score with main intervention effect and the MMSE and MoCA scores with the effect of time, the MMSE and MoCA scores with the interaction between the intervention and time were all statistically significant (P<0.05), showing that the cognitive function of participants with MCI was improved by the intervention. CONCLUSIONS: Multi-component exercise training could significantly improve physical function and cognitive function of the elderly with MCI. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2100049350.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".