Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Work in the development and evaluation of mindfulness-based interventions (MBIs) for cancer care has been underway for the last 20 years, and a growing body of literature now supports their efficacy. MBIs are particularly helpful in dealing with common experiences related to cancer diagnosis, treatment, and survivorship, including loss of control, uncertainty about the future, and fears of recurrence, as well as a range of physical and psychological symptoms, including depression, anxiety, insomnia, and fatigue. Our adaptation, mindfulness-based cancer recovery (MBCR), has resulted in improvements across a range of psychological and biological outcomes, including cortisol slopes, blood pressure, and telomere length, in various groups of cancer survivors. In this paper, I review the rationale for MBIs in cancer care and provide an overview of the state of the current literature, with a focus on results from three recent clinical trials conducted by our research group. These include a comparative efficacy trial comparing MBCR to supportive-expressive therapy in distressed breast cancer survivors, a non-inferiority trial comparing MBCR to cognitive behavioral therapy for insomnia in cancer survivors with clinical insomnia, and an online adaptation of MBCR for rural and remote cancer survivors without access to in-person groups. I conclude by outlining work in progress and future directions for MBI research and applications in cancer care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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