Symptom reduction in advanced cancer from multi-session mindful breathing: randomised controlled study
Bibliographic record
Abstract
Objectives While single-session mindful breathing shows symptom reduction in palliative care, data on multi-session efficacy is lacking. This study aimed to determine the effectiveness of multi-session mindful breathing in reducing symptoms among patients with advanced cancer. Methods Adult patients with advanced cancer who scored ≥4 in at least two or more symptoms based on the Edmonton Symptom Assessment Scale (ESAS) were recruited from January to March 2020 at the University of Malaya Medical Centre, Malaysia. Participants were randomly assigned to receive either four daily sessions of 30 min mindful breathing and standard care (intervention) or standard care alone (control). The outcome measured was the change in the ESAS score after each session. Results 80 patients were recruited and randomised equally into the intervention and control groups. The demographic and clinical characteristics between the two groups were not statistically different. For the intervention group, there were statistically significant reductions in the total ESAS scores following all four sessions of 30 min mindful breathing (n 1 =40: z 1 =−5.09, p<0.001; z 2 =−3.77, p<0.001; z 3 =−4.38, p<0.001; z 4 =−3.27, p<0.05). For the control group, statistically significant reductions in the total ESAS scores were seen only after sessions 1 and 3 (n 2 =40: z 1 =−4.04, p<0.001; z 3 =−4.53, p<0.001). Conclusions Our result provides evidence that four daily sessions of 30 min mindful breathing may be effective in reducing multiple symptoms rapidly in patients with advanced cancer. Trial registration number NCT05910541 .
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".