Examining the Acceptability and Feasibility of the Compassionate Mindful Resilience (CMR) Programme in Adult Patients with Chronic Kidney Disease: The COSMIC Study Protocol
Bibliographic record
Abstract
Kidney disease is often progressive, and patients experience diminished health-related quality of life. In addition, the impact of the coronavirus (COVID-19) pandemic, and its associated restrictions, has brought many additional burdens. It is therefore essential that effective and affordable systems are explored to improve the psychological health of this group that can be delivered safely during the COVID-19 pandemic. The aim of this study is to support a new service development project in partnership with the UK's leading patient support charity Kidney Care UK by implementing the four-session Compassionate Mindful Resilience (CMR) programme, developed by MindfulnessUK, and explore its effectiveness for patients with stage 4 or 5 chronic kidney disease or have received a kidney transplant. The study will utilise a quasi-experimental, pretest/posttest design to measure the effect of the CMR programme on anxiety, depression, self-compassion, the ability to be mindful, wellbeing, and resilience, using pre- and posttests, alongside a qualitative exploration to explore factors influencing the feasibility, acceptability, and suitability of the intervention, with patients (and the Mindfulness Teacher) and their commitment to practice. Outcomes from this study will include an evidence-based mindfulness and compassion programme for use with people with kidney disease, which is likely to have applicability across other chronic diseases.
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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 | 0.030 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".