Motor–Cognitive Interventions May Effectively Improve Cognitive Function in Older Adults with Mild Cognitive Impairment: A Randomized Controlled Trial
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is a syndrome that occurs in the preclinical stage of Alzheimer's disease. Early intervention can be effective in preventing Alzheimer's disease, but further research is needed on intervention methods. To identify interventions that are more suitable for Chinese characteristics and to investigate the effects of motor-cognitive intervention on the cognitive functions of older adults with MCI, we screened 103 community-dwelling older adults with MCI aged 65 years and older in Qingdao, Shandong, China; divided them into an intervention group and a control group; and administered a motor-cognitive intervention to the intervention group for 12 weeks. The study used the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) to assess the initial cognitive level of the MCI participants and detect the effects of the intervention. We found that the cognitive abilities of the intervention group were significantly improved at the end of the intervention, as well as at the end of the follow-up, compared with the control group. The results of the current study suggest that the motor-cognitive intervention we used may improve the cognition of older people with MCI in the Chinese community.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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".