Bibliographic record
Abstract
목적: 국내에서 재가암환자를 대상으로 시행된 연구는 많지 않다. 이 연구의 목적은 재가암환자들의 증상정도와 돌봄 요구도를 확인하기 위함이다. 방법: 진주시 재가암 서비스에 등록된 환자를 대상으로 자료를 수집하였다. 측정은 보건소에 소속된 간호사들이 시행하였다. 증상의 평가를 위해 Edmontone Symptome Assessment System (ESAS)와 Numeric Rating Scale (NRS)가 사용되었으며 정신적, 사회적 영적 요구도의 평가를 위해 4점 Likert scale이 사용되었다. 결과: 2013년 10월에 단면조사 방식으로 자료를 수집하였다. 총 209명이 등록되었으며 평균 나이는 65세였다(범위 17~89세). 대다수의 환자들이 초기에 진단 받았으며(n=188), 19명만이 진행된 병기였다. 절반 이상의 환자들이 혼자 거주하고 있었으며(n=115, 55%), 다른 보호자가 없이 스스로 돌보고 있었다(n=128, 61.2%). 식욕부진과 피로가 가장 흔한 증상이었다(NRS 중앙값 각각 5, 4). 환자들은 경제적 문제에 대한 지원이 가장 필요한 반면 영적인 돌봄이 가장 적게 필요하다고 대답하였다(n=138 [67.3%] vs. n=128 [62.1%]). 결론: 이 자료는 진주시 재가암환자들이 신체적 증상과 경제적 문제로 고통 받고 있다는 결과를 보여주었다. 서비스의 질을 향상시키기 위하여 맞춤형 접근이 필요할 것으로 사료된다. 【Purpose: This study was performed to identify the symptoms and care needs of home-based cancer patients in Korea and to add to the scarce literature on this topic. Methods: Data were collected from patients who subscribed to home-based cancer care services in Jinju. Assessments were performed by nurses at the local public health center. The Edmonton Symptom Assessment System with a numeric rating scale (NRS) was used to identify symptoms, and a four-point Likert scale was used to assess psychological, social, and spiritual needs. Results: Cross-sectional data were collected in October 2013. A total of 209 patients participated and their median age was 65 years (range, 17~89 years). Most patients were diagnosed in the early stage of cancer (n=188); only 19 patients were diagnosed in the advanced stage. More than half the patients lived alone (n=115, 55.0%) and took care of themselves (n=128, 61.2%). Anorexia and fatigue were the most common symptoms (median NRS, 5 and 4, respectively). Patients needed economic support the most, whereas spiritual care was least needed (n=138 [67.3%] vs. n=128 [62.1%], respectively). Conclusion: Patients who signed up for home-based cancer care services in Jinju are struggling with a financial issue and physical symptoms. A customized approach is needed to improve the quality of the home-based care services.】
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".