Meditation effects on physical, psychological, and symptom distress in an outpatient integrative medicine clinic.
Bibliographic record
Abstract
e20675 Background: Mind-body practices help cancer patients manage psychological distress and control symptoms such as pain, nausea, and sleep disturbances. However, the effects of a single meditation session on self-reported symptoms, including physical, psychological and symptom distress in an outpatient setting, are largely unknown. Methods: All patients receiving an individual meditation consultation (60 minute initial visits, and 30 minutes follow-up visits) at our Integrative Medicine Center outpatient clinic from May 2011 through December 2013, were asked to complete a modified Edmonton Symptom Assessment Scale (ESAS; scale from 0-10, where 10 is most severe). Data were analyzed examining the pre- and post-meditation scores using paired t-tests. Results: Our analysis included 81 meditation visits for 121 participants (mean 1.2 visits/person) over 32 months. The ESAS revealed a significant reduction from pre- to post-meditation session in physical, psychological, and symptom distress component scores (-7.85; -4.6; and -12.4, respectively; all p’s <0.0001). The greatest mean reductions for individual symptoms were for: Anxiety [-1.9], Fatigue [-1.9], Distress [-1.8], Well Being [-1.6]; Sleep [-1.5]; and Pain [-1.0]; all changes reaching statistically (all p’s <0.0001) and clinically significant thresholds (decrease in symptom score ≥1). Conclusions: A single meditation session resulted in acute relief of self-reported symptoms, as well as physical, psychological and symptom distress subscores in patients. Further research with a larger sample size and appropriate control groups is needed to better understand the symptoms that meditation can help control and the frequency of self-practice outside of the clinic to help maintain the long-term benefits.
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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 | 0.002 |
| 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) | 0.003 | 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".