A survey of the perspectives of patients who are seriously ill regarding end-of-life decisions in some medical institutions of Korea, China and Japan
Bibliographic record
Abstract
PURPOSE: The debate about the end-of-life care decision is becoming a serious ethical and legal concern in the Far-Eastern countries of Korea, China and Japan. However, the issues regarding end-of-life care will reflect the cultural background, current medical practices and socioeconomic conditions of the countries, which are different from Western countries and between each other. Understanding the genuine thoughts of patients who are critically ill is the first step in confronting the issues, and a comparative descriptive study of these perspectives was conducted by collaboration between researchers in all three countries. METHODS: Surveys using self-reporting paper questionnaire forms were conducted from December 2008 to April 2009 in Korea (six hospitals in two regions), China (five hospitals in four regions) and Japan (nine hospitals in one region). The subjects were patients who were critically ill who had been diagnosed as having cancer. A total of 235 participants (Korea, 91; China, 62; Japan, 52) were eventually recruited and statistically analysed. RESULTS: Most respondents had sometimes or often thought of their own death, mostly fear of 'separation from loved ones'. They wanted to hear the news regarding their own condition directly and frankly from the physician. A quarter of them preferred making end-of-life care decisions by themselves, while many respondents favoured a 'joint decision' with their family members. The most favoured proxy decision maker was the spouse, followed by the children. Most admitted the necessity of 'advance directives' and agreed with artificial ventilation withdrawal in irreversible conditions. The most common reason was 'artificial prolongation of life is unnecessary'. Most respondents agreed with the concept of active euthanasia; however, significant differences were sometimes observed in the responses according to variables such as patient's country of origin, age, gender and education level. CONCLUSION: Patients in Far-Eastern countries gave various responses regarding end-of-life care decisions. Although familial input is still influential, most patients think of themselves as the major decision maker and accept the necessity of advance directives with Westernization of the society. Artificial ventilation withdrawal and even active euthanasia may be acceptable to them.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".