Effects of Cognitive Function and Naming Ability on the Quality of Communication Life in the Korean Elderly
Bibliographic record
Abstract
Purpose: As old people age, their cognitive skills as well as naming ability decrease. In particular, dementia, along with memory, is a decline in other intellectual abilities that can interfere with everyday life. Therefore, the aim of this study was to explore the naming ability, cognitive function, and quality of communication life in the Korean elderly and thier relationship.Methods: A total of 50 Korean elderly people (25 normal, 25 elderly patients with mild cognitive impairment (MCI) from Korean version of Montreal Cognitive Assessment (K-MoCA) ranged in age from 65 to 85 years old participated. The naming ability and quality of communication life were measured using short form of the Korean-Boston naming test (S-K-BNT) and the quality of communication life scale (QCL).Results: Significantly lower naming ability and poor QCL scores were observed in the elderly group with MCI. In addition, significantly strong correlation was revealed between K-MoCA score and QCL (r = 0.728). All cognitive function including executive function, visuospatial ability, memory, attention, language, and orientation demonstrated significant relationship with QCL. Among the cognitive function, in particular, visuospatial ability showed the highest correlation with QCL (r = 0.626). Moreover, significantly moderate positive correlation (r = 0.620) was revealed between naming score and QCL.Conclusion: In current study, cognitive function as well as naming ability can be important diagnostic indice for predicting and determining good quality of communication life in elderly people.
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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) | 0.000 | 0.000 |
| 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) | 0.001 | 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".