Psycho-existential distress in hospice patients and their caregivers
Bibliographic record
Abstract
AIM: To assess the psycho-existential distress of patients and their caregivers in a specific setting, like hospice. METHODS: Patients consecutively admitted to two hospices for a period of 8 months were enrolled. At admission (T0), patients were assessed by a routine data recording: age; gender; Edmonton Symptom Assessment Scale (ESAS); Memorial Delirium Assessment Scale (MDAS); Cut down, Annoy, Guilt, Eye-opener (CAGE); Karnofsky level; primary diagnosis; education; religiosity and comorbidities. Psycho-existential distress was assessed at T0 by the Psycho-existential Symptom Assessment Scale (PeSAS). The measurements were repeated 1 week after comprehensive palliative care treatment. RESULTS: 159 patients and 87 caregivers were considered. The majority of patients had a cancer diagnosis (88.7%). Non-cancer patients were older (p<0.0005), had a lower Karnofsky (p<0.0005) and higher cognitive decline (MDAS, p<0.0005). After 1 week of comprehensive palliative care treatment, significant changes were observed for most ESAS items and total ESAS in both patients and caregivers. PeSAS items were mild-moderate. All symptoms of PeSAS, except for depression, significantly decreased after 1 week of comprehensive palliative care with a significant decrease in total PeSAS. Caregivers showed similar psycho-existential distress, but total PeSAS did not significantly change. There was a positive correlation between patients and caregivers in the changes from T0 to T7 (Δ) for PeSAS (p=0<004) and total ESAS (p=0.005). CONCLUSIONS: Admission to hospice improved both physical symptoms and psycho-existential distress in patients significantly and non-significantly in caregivers.
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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 | 0.000 | 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) | 0.001 | 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".