Application of Cognitive Enhancement Protocol Based on ICT Program to Improve Cognitive Level of Older Adults Residents in Small‐sized City Community: A Pilot Study
Bibliographic record
Abstract
Abstract Background A home‐based ICT program to elderly people aged 65 years or older to confirm the effect of the cognitive enhancement program and explore the possibility of remote rehabilitation. Method This study from August to October 2022, three subjects were selected and the intervention was conducted for about two months. This intervention was conducted using the Korean version of Mini‐Mental State Examination(MMSE‐K), the Korean version of Montreal Cognitive Assessment(MoCA‐K), the Computer Cognitive Senior Assessment System(CoSAS), and the two shorter form of the Center for Epidemiologic Studies Depression scale(CESD‐10‐D) to evaluated cognitive improvement before and after the program. The therapist remotely set the difficulty lever of cognitive training suitable fore the level of the subject through weekly feedback, and during the program. Interviews were conducted for additional opinions on the cognitive enhancement program. Result After the intervention, all subjects showed improved scores in most items of the Korean version of the Montreal Cognitive Assessment conducted before and after the intervention. In addition, among the items of CoTras, upper cognition, language ability, attention, visual perception, and memory were improved. In addition, subjective satisfaction with the cognitive improvement program was high. Conclusion Cognitive rehabilitation training using a home‐based ICT program not only prevented dementia but also made it habitual. Through this study, it was confirmed that remote rehabilitation for the elderly could be possible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".