Cross-sectional survey of the wish to die among palliative patients in Spain: one phenomenon, different experiences
Bibliographic record
Abstract
Objective Cultural backgrounds and values have a decisive impact on the phenomenon of the wish to die (WTD), and examination of this in Mediterranean countries is in its early stages. The objectives of this study were to establish the prevalence of WTD and to characterise this phenomenon in our cultural context. Methods A cross-sectional study with consecutive advanced inpatients was conducted. Data about WTD ( Assessing Frequency & Extent of Desire to Die (AFFED) interview) and anxiety and depression ( Edmonton Symptom Assessment System-revised (ESAS-r)) were collected through two face-to-face clinical encounters. Data were analysed with descriptive statistics, χ 2 and analysis of variance. Results 201 patients participated and 165 (82%) completed both interviews. Prevalence of WTD was 18% (36/201) in the first interview and 16% (26/165) in the second interview (p=0.25). After the first interview, no changes in depression (p=0.60) or anxiety (p=0.90) were detected. The AFFED shows different experiences within WTD: 11% of patients reported a sporadic experience, while 7% described a persistent experience. Thinking about hastening death (HD) appeared in 8 (22%) out of 36 patients with WTD: 5 (14%) out of 36 patients considered this hypothetically but would never take action, while 3 (8%) out of 36 patients had a more structured idea about HD. In this study, no relation was detected between HD and frequency of the appearance of WTD (p=0.12). Conclusions One in five patients had WTD. Our findings suggest the existence of different experiences within the same phenomenon, defined according to frequency of appearance and intention to hasten death. A linguistically grounded model is proposed, differentiating the experiences of the ‘wish’ or ‘desire’ to die, with or without HD ideation.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".