Effectiveness of an enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) in older adults with mild cognitive impairment
Bibliographic record
Abstract
The aim of this study was to provide a dual-task program that included cognitive and physical training to older adults with mild cognitive impairment (MCI) and evaluate its effects. A single-group pretest-posttest design was performed using 15 older adults with MCI. A 12-week enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) program was conducted from September 2019 to December 2019. Participants were assessed using the Korean version of the Montreal Cognitive Assessment, electroencephalography (EEG), muscle strength, flexibility, agility, memory self-efficacy questionnaire, physical self-efficacy scale, and quality of life before and after 6 and 12 weeks of the intervention. The ESCARF program significantly improved cognitive function, physical function, self-efficacy, and quality of life in older adults with MCI. These findings will provide insights into the development and implementation of customized cognitive interventions to prevent or delay the onset of cognitive decline in older adults with MCI.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".