일개 보건소에서 시행한 독거노인 한방 가정방문 결과보고: 이침치료를 활용한 인지기능 개선을 중심으로
Bibliographic record
Abstract
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".