Cognitive Training in Older Adults with Mild Cognitive Impairment.
Bibliographic record
Abstract
OBJECTIVE: We investigated the feasibility and efficacy of cognitive training for older adults in rural settings and with low education levels, who have mild cognitive impairment (MCI). METHODS: Forty-five older adults (ages >65 years) with MCI were assigned to treatment or control groups, at a 2:1 ratio. Cognitive training occurred in the treatment group for 2 months. The cognitive abilities of the participants were assessed at pre-training, metaphase, and post-training time points, using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Loewenstein Occupational Therapy Cognitive Assessment (LOTCA), and Hamilton Depression Scale (HAM-D). RESULTS: Following training, cognitive abilities improved in the treatment group, based on the total scores of all 4 measures, as well as specifically on the MoCA and LOTCA. There were differences in the main effects of group and time point on some subscales, but these differences had little, if any, effect on the overall analyses. CONCLUSION: The present study demonstrated that cognitive training has beneficial effects on attention, language, orientation, visual perception, organization of visual movement, and logical questioning in patients with MCI. Furthermore, the observed effects are long-term changes.
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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) | 0.000 | 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".