Inpatient Music Therapy Effects On Self-Reported Symptoms In A Cancer Center : A Preliminary Report
Bibliographic record
Abstract
Introduction:Music therapy has shown benefits for reducing distress in individuals with cancer. We explore the effects of music therapy on self-reported symptoms of patients receiving inpatient care at a comprehensive cancer center. Methods:Music therapy was available as part of an inpatient integrative oncology consultation service; we examined interventions and symptoms for consecutive patients treated by a board certified music therapist from 9/2016-5/2017. Patients completed the Edmonton Symptom Assessment Scale (ESAS, 10 symptoms, scale 0-10, 10 most severe) before and after the intervention. Data was summarized by descriptive statistics. Change in ESAS symptom and subscale scores [physical distress (PHS), psychological distress (PSS), and global distress (GDS)] were evaluated by Wilcoxon signed rank test.Results:Data were evaluable for 96 of 100 consecutive patients; 55% were women, average age 50, majority with hematologic malignancies (47%). Reasons for music therapy referral included: anxiety/stress (67%), adjustment disorder/coping (28%), and mood elevation/depression (17%). Highest (worst) symptoms at baseline were sleep disturbance (5.7) and well-being (5.5). We observed statistically and clinically significant improvement (means) for anxiety (-2.3u00b11.5), drowsiness (-2.1u00b12.2), depression (-2.1u00b11.9), nausea (-2.0u00b12.4), fatigue (-1.9u00b11.5), pain (-1.8u00b11.4), shortness of breath (-1.4u00b12.2), appetite (-1.1u00b11.7); and for all ESAS subscales (all pu2019s<0.02). Highest clinical response rates were observed for anxiety (92%), depression (91%), and pain (89%).Conclusions:A single, live, tailored music therapy intervention as part of an integrative oncology inpatient consultation service contributed to significant improvement in global, physical and psychosocial distress. A randomized controlled trial is justified.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.041 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.012 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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; both teacher heads agree on what is shown here.
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".