Cognitive Intervention in Older Adults With Mild Cognitive Impairment
Bibliographic record
Abstract
Abstract Individuals with mild cognitive impairment (MCI) experience cognitive difficulties and many find themselves in a transitional stage between aging and dementia, making this population a suitable target for cognitive intervention. In MCI, not all cognitive functions are impaired and preserved functions can thus be recruited to compensate for the impact of cognitive impairment. Improving cognition may have a tremendous impact on quality of life and help delay the loss of autonomy that comes with dementia. Several studies have reported evidence of cognitive benefits following cognitive intervention in individuals with MCI. Studies that relied on training memory and attentional control have provided the most consistent evidence for cognitive gains. A few studies have investigated the neurophysiological processes by which these training effects occur. More research is needed to draw clear conclusions on the type of brain processes that are engaged in cognitive training and there are insufficient findings regarding transfer to activities of daily life. Results from recent studies using new technologies such as virtual reality provide encouraging evidence of transfer effects to real-life situations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".