Enhancing latent cognitive capacity in mild cognitive impairment with gist reasoning training: a pilot study
Bibliographic record
Abstract
OBJECTIVE: Cognitive training offers a promising way to mitigate cognitive deterioration in individuals with mild cognitive impairment (MCI). This randomized control pilot trial examined the effects of Gist Reasoning Training on cognition as compared with a training involving New Learning in a well-characterized MCI group. METHODS: Fifty participants with amnestic MCI were randomly assigned to the experimental Gist Training group or an active control New Learning group. Both groups received 8 h of training over a 4-week period. We compared pre-training with post-training changes in cognitive functions between the two training groups. RESULTS: The Gist Training group showed higher performance in executive function (strategic control and concept abstraction) and memory span compared with the New Learning group. Conversely, the New Learning group showed gains in memory for details. CONCLUSION: These findings suggest that cognitive training in general yields benefits, and more specifically, training programs that target top-down cognitive functions such as gist reasoning may have a broad impact on improving cognition in MCI. © 2016 The Authors. International Journal of Geriatric Psychiatry Published by John Wiley & Sons Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".