Association Between Music Therapy Techniques and Patient-Reported Moderate to Severe Fatigue in Hospitalized Adults With Cancer
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Bibliographic record
Abstract
PURPOSE: Cancer-related fatigue is a prevalent, debilitating symptom that contributes to increased health care utilization among hospitalized patients. Music therapy is a nonpharmacological intervention that uses active (eg, singing, selecting songs) and passive (eg, listening) techniques. Preliminary evidence from small trials suggests a potential benefit for cancer-related fatigue in the inpatient setting; however, it remains unclear which techniques are most effective. METHODS: A cross-sectional mixed-methods study was performed to compare cancer-related fatigue before and after active or passive music therapy. Cancer-related fatigue was captured via the Edmonton Symptom Assessment Scale fatigue item. Patients were asked to provide postsession free-text comments. RESULTS: A total of 436 patients (mean [standard deviation] age, 62.2 [13.4] years; n = 284 [65.1%] women; n = 294 [67.4%] white; active music therapy n = 360 [82.6%]; passive music therapy n = 76 [17.4%]) with a range of primary malignancies participated. Active music therapy was associated with a 0.88-point greater reduction in cancer-related fatigue (95% CI, 0.26 to 1.51; P = .006; Cohen’s D, 0.52) at postsession as compared with passive music therapy when restricting the analysis to patients who rated their baseline cancer-related fatigue as moderate to severe (ie, ≥ 4; n = 236 [54.1%]). Free-text responses confirmed higher frequencies of words describing positive affect/emotion among active music therapy participants. CONCLUSIONS: In a large sample of inpatient adults with diverse cancer disease types, active music therapy was associated with greater reduction in cancer-related fatigue and increased reporting of positive affect/emotions compared with passive music therapy. Additional research is warranted to determine the specific efficacy and underlying mechanisms of music therapy on cancer-related fatigue.
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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) | 0.000 | 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 it