Effects of Multicomponent Exercise on Community-Dwelling Older Adults With Mild Cognitive Impairment
Bibliographic record
Abstract
Purpose: To explore the effects of a group-based multicomponent exercise program on general cognitive functioning, depression, and social functioning in community-dwelling older adults with mild cognitive impairment (MCI) and whether the effects can be maintained. Method: Fifty older adults with MCI were conveniently recruited from two communities in the study area and randomly assigned to the intervention group or control group. The intervention group received three sessions of 60-minute, multicomponent exercise per week for 3 months, plus MCI-related health education. The control group only received MCI-related health education. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Beijing Version (MoCA-BJ) were used to assess general cognitive function. The Functional Activities Questionnaire (FAQ) and Geriatric Depression Scale (GDS-30) were used to evaluate participants' social function and depression, respectively. Participants' exercise intensity was assessed using the Category Ratio Scale. Results: After the 3-month intervention, there were significant improvements in general cognitive function ( p = 0.046), attention ( p = 0.009), delayed recall ( p = 0.015), and social function ( p = 0.011) in the intervention group compared with the control group. However, after 3-month postintervention follow up, no significant differences in MMSE, MoCA-BJ, GDS-30, and FAQ scores were noted between groups. Conclusion: The 3-month multicomponent exercise program improved general cognitive function and social functioning in community-dwelling older adults with MCI. However, there was no evidence that these benefits lasted for another 3 months after stopping the exercise program. [ Research in Gerontological Nursing, 17 (2), 65–79.]
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".