Exploring the effectiveness of a patient‐tailored integrative oncology program on emotional distress during chemotherapy for localized cancer
Bibliographic record
Abstract
STUDY OBJECTIVE: There is a need to explore how patient-tailored integrative oncology (IO) programs reduce emotional distress. This study set out to bridge the IO research gap between non-specific, quality of life-related and specific emotional-related concerns in chemotherapy-treated patients. METHODS: This pragmatic, prospective and preference-controlled study examined patients attending an integrative-physician consultation and weekly IO treatments during adjuvant/neo-adjuvant chemotherapy for localized cancer. Patients choosing to attend ≥4 IO sessions (highly adherent to integrative care, AIC) were compared to low AIC patients using the ESAS (Edmonton Symptom Assessment Scale) anxiety, depression and sleep; and the EORTC QLQ-C30 (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire) emotional functioning scale, at baseline, 6 and 12 weeks. Emotional distress was assessed by ESAS anxiety and depression, considered as the primary study outcomes. RESULTS: Of 439 participants, 260 (59%) were high-AIC and 179 low-AIC, both with similar baseline demographic and cancer-related characteristics. At 6 weeks, high-AIC patients reported greater improvement on ESAS sleep (p = 0.044); within-group improvement on ESAS anxiety and; and EORTC emotional functioning. Compared with low-AIC, high-AIC patients showed greater improvement on ESAS depression (p = 0.022) and sleep (p = 0.015) in those with high baseline ESAS anxiety scores (≥7); and ESAS anxiety (p = 0.049) for patients moderately anxious (4-6) at baseline. CONCLUSIONS: High-AIC was associated with significantly reduced anxiety, depression and sleep severity at 6 weeks, especially those with high-to-moderate baseline anxiety levels. These findings reduce the research gap, suggesting specific emotional-related effects of IO.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".