Promoting Resilience with the Mindfulness-Based Stress Reduction Program in Patients With Chronic Illness
Bibliographic record
Abstract
Objectives: Twenty-first century patients need to take a proactive stance with regard to their health in order to cope well with chronic illness. Mindfulness-Based Stress Reduction (MBSR) is an 8-week structured group program that encourages patients to take responsibility for their health and teaches them to cope with stressors inherent in living with illness.Methods: Patients with chronic illnesses (e.g., breast cancer, chronic pain, multiple sclerosis) participated in the MBSR program from 2006-2012. They completed questionnaires pertaining to depression, medical symptoms, stress, coping, sense of coherence, and mindfulness pre- and post-MBSR. They filled out a follow-up questionnaire that asked them to rate the program and its components. A self-care index was created from 5 items.Results: Of the 126 patients, 85.7% were woman, breast cancer was the most common illness (46.8%), and the average age was 52.3 (SD = 13.3). There were significant improvements on the following outcomes: depression, stress, and medical symptoms. With regard to process measures, there were significant increases in: mindfulness, sense of coherence (comprehensibility, manageability, and meaningfulness of life), as well as significant decreases in emotional coping. Patients rated the program with a mean of 8.94 (1 to 10 scale) for importance. They rank ordered the program components in terms of helpfulness with awareness of breath, the silent retreat day, and yoga practice as the highest of 10 items. There was a significant positive correlation between self-care index at the end of the course and its perceived importance. Moreover, self-care was positively and significantly correlated with post-MBSR mindfulness and viewing life as meaningful.Conclusions: Patients who took the MBSR program reported mental and physical health benefits. Furthermore, being mindful enabled them to cope better, take care of themselves, and view life as more coherent such that they became more stress resilient.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".