Adding Acupuncture to Touch/Relaxation for Pain in Wartime: A Randomized Controlled Trial
Bibliographic record
Abstract
CONTEXT AND OBJECTIVES: Patients with cancer living in war zones face significant quality of life (QoL)-related challenges. This study examined an integrative oncology (IO) intervention in northern Israel for pain and autonomic response. METHODS: This prospective, randomized, controlled and pragmatic study examined an IO intervention with manual-relaxation, with acupuncture (Group A) or without (Group B). ESAS (Edmonton Symptom Assessment Scale), EORTC QLQ-C30 (European Organization for Research and Treatment of Cancer QoL Questionnaire), and MYCAW (Measure Yourself Concerns and Wellbeing) tools were used to examine QoL. Heart rate and variability (HRV) were measured at baseline and 15 minutes post-treatment, comparing frequency-domain variable changes (e.g., LN Power Total, Power HF, Power LF, Power VLF). RESULTS: Of 125 patients, Groups A (67) and B (58) had similar demographic and cancer-related characteristics. ESAS pain scores improved in both groups post-treatment (A, P < 0.001; B, P = 0.002), as did anxiety, depression, and fatigue. At three weeks, Group B reported greater improvement on ESAS pain (P = 0.039) and MYCAW pain-related concerns (P = 0.025), both showing within-group improvement on EORTC pain. HRV showed greater change in Group A, with decreased LN Power Total (P = 0.006), LN Power LF (P = 0.02), and LN Power VLF (P = 0.026). While Relative Power HF increased marginally (P = 0.054), heart rate decreasing more significantly in Group B (P = 0.005). CONCLUSIONS: IO treatments led to reduced pain among patients with cancer living in a war zone, with no additive effect of acupuncture. HRV changes suggest enhanced parasympathetic activity, with acupuncture-treated patients showing additional frequency-domain changes attributed to decreased sympathetic tone.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".