Mindfulness‐based cancer recovery and supportive‐expressive therapy maintain telomere length relative to controls in distressed breast cancer survivors
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Bibliographic record
Abstract
BACKGROUND: Group psychosocial interventions including mindfulness-based cancer recovery (MBCR) and supportive-expressive group therapy (SET) can help breast cancer survivors decrease distress and influence cortisol levels. Although telomere length (TL) has been associated with breast cancer prognosis, the impact of these two interventions on TL has not been studied to date. METHODS: The objective of the current study was to compare the effects of MBCR and SET with a minimal intervention control condition (a 1-day stress management seminar) on TL in distressed breast cancer survivors in a randomized controlled trial. MBCR focused on training in mindfulness meditation and gentle Hatha yoga whereas SET focused on emotional expression and group support. The primary outcome measure was relative TL, the telomere/single-copy gene ratio, assessed before and after each intervention. Secondary outcomes were self-reported mood and stress symptoms. RESULTS: Eighty-eight distressed breast cancer survivors with a diagnosis of stage I to III cancer (using the American Joint Committee on Cancer (AJCC) TNM staging system) who had completed treatment at least 3 months prior participated. Using analyses of covariance on a per-protocol sample, there were no differences noted between the MBCR and SET groups with regard to the telomere/single-copy gene ratio, but a trend effect was observed between the combined intervention group and controls (F [1,84], 3.82; P = .054; η(2) = .043); TL in the intervention group was maintained whereas it was found to decrease for control participants. There were no associations noted between changes in TL and changes in mood or stress scores over time. CONCLUSIONS: Psychosocial interventions providing stress reduction and emotional support resulted in trends toward TL maintenance in distressed breast cancer survivors, compared with decreases in usual care.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 it