Validation of the Short Form of Korean-Everyday Cognition (K-ECog)
Bibliographic record
Abstract
BACKGROUND: Evaluating the activities of daily living (ADL) is an important factor for diagnosing dementia. The Everyday Cognition (ECog) scale was developed to measure ADL changes that were correlated with specific neuropsychological impairments. A short form of the ECog (ECog-12) was also developed, consisting of 12 items, two from each of the six cognitive domains of the ECog. The Korean full version of ECog (K-ECog) has recently been standardized, but the need for a shortened version has been raised in clinical practice. The purpose of this study was to develop a Korean version of ECog-12 (K-ECog-12) and to verify its reliability and validity by comparing those to the full version of K-ECog. METHODS: The participants were 267 cognitively normal older adults (CN), 183 patients with mild cognitive impairment (MCI), and 89 patients with dementia. The Korean-Mini Mental State Examination (K-MMSE), Korean-Montreal Cognitive Assessment (K-MoCA), and Short form of Geriatric Depression Scale (SGDS) were administered to all participants. The K-ECog and Korean-Instrumental Activities of Daily Living (K-IADL) were rated by the informants of patients. RESULTS: ) were 0.67 for K-ECog-12 and 0.73 for K-ECog. The K-ECog-12 was significantly correlated with K-ECog as well as K-IADL, K-MMSE, and K-MoCA. The K-ECog-12 scores differed significantly between the CN, MCI, and dementia groups, as did the K-ECog scores. Receiver operating characteristic curve analyses showed that K-ECog-12, like K-ECog, could differentiate MCI and dementia patients from CN as well. CONCLUSION: The K-ECog-12 is as reliable and valid as the K-ECog in assessing ADL. Therefore, K-ECog-12 can be used as an alternative to the K-ECog in clinical and community settings in Korea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".