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Record W4388014981 · doi:10.3346/jkms.2023.38.e370

Validation of the Short Form of Korean-Everyday Cognition (K-ECog)

2023· article· en· W4388014981 on OpenAlexaboutno aff
Minji Song, Dong Gi Seo, Seong Yoon Kim, Yeonwook Kang

Bibliographic record

VenueJournal of Korean Medical Science · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersHallym University
KeywordsCognitionCognitive impairmentMedicineComputer scienceCognitive psychologyPsychologyNeuroscience

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.358
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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