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Record W3192354524

경도인지장애 고령자의 인지기능 및 우울 수준에 대한 가정방문 개별 보드게임 프로그램의 융복합 연구

2019· article· ko· W3192354524 on OpenAlexaboutno aff
Hanna Kim, Bo-Kyoung Song

Bibliographic record

Venue한국융합학회논문지 · 2019
Typearticle
Languageko
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMini–Mental State ExaminationPsychologyCognitive impairmentDepression (economics)CognitionGerontologyMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

본 연구는 65세 이상 경도인지장애 7명을 대상으로 개별 보드게임프로그램 및 추척관찰을 통하여 인지기능 및 우울 수준에 미치는 영향을 알아보고자 하였고 이를 위해 Mini-Mental State Examination Korean version(MMSE-K), Korean Version of Montreal Cognitive Assessment(MoCA-K) 및 Korean Gorm of Geriatric Depression Scale(KGDS)를 사용하였다. 연구결과, MMSE-K 중재 전, 후 및 추적평가에서 유의한 차이를 보였고(p<0.05) 세부항목 중 시간, 장소 및 물건 인식력과 집중력에서 차이를 보였다(p<0.05). MoCA-K는 중재 전, 후 및 추적평가에서 차이를 보였는데(p<0.01) 세부항목 중 시공간, 이름 인식력, 주의집중 및 단기기억력에서 차이를 보였다(p<0.05). KGDS을 통한 우울수준의 중재 전, 후 및 추적 비교에서 우울에 차이를 보였다(p<0.01). 따라서 65세 이상의 경도인지장애 고령자의 개별보드게임은 인지기능을 개선에 도움을 줄 수 있고 또한 고령자의 시간과 장소 인식 력을 포함된 개선된 보드게임이 개발되고 적용되기 기대한다.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.067
GPT teacher head0.486
Teacher spread0.418 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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