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Record W3111126447

일개 보건소에서 시행한 독거노인 한방 가정방문 결과보고: 이침치료를 활용한 인지기능 개선을 중심으로

2019· article· ko· W3111126447 on OpenAlexaboutno aff
권찬영, Boram Lee, Seon Yong Jung, Jong Woo Kim

Bibliographic record

Venue동의신경정신과학회지 · 2019
Typearticle
Languageko
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeriatric Depression ScaleMedicineMontreal Cognitive AssessmentDepression (economics)DementiaMini–Mental State ExaminationClinical Dementia RatingPhysical therapyRating scaleGerontologyPromotion (chess)CognitionService (business)Cognitive impairmentDiseasePsychiatryPsychologyDepressive symptomsInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objectives: To conduct and report the results of a public health promotion program in Korean medicine (KM), namely the KM Visiting Care Service for Solitary Elderly, from November 2018 to April 2019. Methods: Six elderly people living in a rural area received the KM visiting care service, twice a week, for four months. This service consisted of acupuncture, auriculotherapy, and supportive counseling to manage their musculoskeletal pain, cognitive impairment, and/or depression. The changes of symptoms were assessed using Numeric Rating Scale (NRS), Korean version of Mini-Mental State Examination for Dementia Screening (MMSE-DS), Korean version of Montreal Cognitive Assessment (MoCA-K), and Geriatric Depression Scale-Short form Korean (GDS-SF-K). Results: Through the 4-months KM visiting care service, the overall subjects’ NRS-rated pain decreased slightly. Most showed improvement in MMSE-DS and/or MoCA-K, except one subject who was diagnosed with Alzheimer’s disease. Depression assessed by GDS-SF-K showed improvement in a few subjects who were unable to walk independently. Satisfaction assessed through survey was generally high in all subjects. Conclusions: This KM Visiting Care Service for Solitary Elderly may help improve the pain and cognitive function of frail solitary elderly in rural areas. However, the protocol need to be improved to optimize the effect.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0320.164

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 head0.066
GPT teacher head0.487
Teacher spread0.420 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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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