The Effects of a Brief Relaxation Program on Symptom Distress and Heart Rate Variability in Cancer Patients
Bibliographic record
Abstract
OBJECTIVES: To determine whether a 15-minute, one-time guided relaxation program for cancer patients could improve symptom distress as measured by the Edmonton Symptom Assessment System (ESAS). In addition, we were interested in characterizing the changes of the autonomic nervous system, as demonstrated by heart rate variability (HRV) high-frequency (HF) spectral analysis, before and after this relaxation program. DESIGN: Nonrandomized pilot study. SETTING: Comprehensive cancer center. METHODS: Twenty cancer patients underwent a 15-minute relaxation program. The ESAS and a 5-minute HRV recording were completed before and after the relaxation program. MAIN OUTCOME MEASURES: The differences between the pre- and post-summed ESAS score and HRV values were compared by a paired t-test. RESULTS: The summed ESAS scores were significantly lower after the relaxation program (P<.01), with an average 31% decrease in total score. However, no differences were found in HRV HF power. There was no correlation between the change in HRV HF and change in symptom distress, as measured by ESAS. CONCLUSIONS: A brief guided relaxation program can significantly improve symptoms as measured by ESAS. More research is required to understand the effects of relaxation on HF HRV power.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".