Effects of Bathing in a Tub on Physical and Psychological Symptoms of End-of-Life Cancer Patients
Bibliographic record
Abstract
This observational, controlled study explored the effects of bathing on the physical and psychological aspects of terminal cancer patients on a palliative care ward. With nurses' assistance, the patients evaluated and recorded the severity of their symptoms at 10:00 am, 30 minutes after initial bathing, and at 5:00 pm. The bathing care was provided as routine care according to the patients' wishes. Twelve symptoms were measured using 9 items (numbers 1-9) from the Edmonton Symptom Assessment System-Revised Japanese version and 3 items from the Cancer Fatigue Scale. Outcomes were compared between bathing days and nonbathing days (control) and between before and after bathing. Of the 57 bathers, data were available for both bathing days and nonbathing days for 42 bathers. In the comparison between bathing and nonbathing days, tiredness was significantly improved (effect size [ES], 0.35; P = .02). On the basis of the pre-post bathing comparison, 6 symptoms, namely, tiredness (ES, 0.40; P < .01), lack of appetite (ES, 0.36; P = .01), decreased well-being (ES, 0.33; P = .01), anxiety (ES, 0.36; P = .01), pain (ES, 0.31; P = .02), and depression (ES, 0.30; P = .02), were significantly improved. Bathing in a tub effectively improves tiredness and might be effective for distressing symptoms in end-of-life cancer patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".