Mindfulness-Based Cancer Recovery (MBCR) versus Supportive Expressive Group Therapy (SET) for distressed breast cancer survivors: evaluating mindfulness and social support as mediators
Bibliographic record
Abstract
Despite growing evidence in support of mindfulness as an underlying mechanism of mindfulness-based interventions (MBIs), it has been suggested that nonspecific therapeutic factors, such as the experience of social support, may contribute to the positive effects of MBIs. In the present study, we examined whether change in mindfulness and/or social support mediated the effect of Mindfulness-Based Cancer Recovery (MBCR) compared to another active intervention (i.e. Supportive Expressive Group Therapy (SET)), on change in mood disturbance, stress symptoms and quality of life. A secondary analysis was conducted of a multi-site randomized clinical trial investigating the impacts of MBCR and SET on distressed breast cancer survivors (MINDSET). We applied the causal steps approach with bootstrapping to test mediation, using pre- and post-intervention questionnaire data of the participants who were randomised to MBCR (n = 69) or SET (n = 70). MBCR participants improved significantly more on mood disturbance, stress symptoms and social support, but not on quality of life or mindfulness, compared to SET participants. Increased social support partially mediated the impact of MBCR versus SET on mood disturbance and stress symptoms. Because no group differences on mindfulness and quality of life were observed, no mediation analyses were performed on these variables. Findings showed that increased social support was related to more improvement in mood and stress after MBCR compared to support groups, whereas changes in mindfulness were not. This suggests a more important role for social support in enhancing outcomes in MBCR than previously thought.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".