Brief Mindfulness Intervention vs. Health Enhancement Program for Patients Undergoing Dialysis: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Between 20-50% of patients undergoing maintenance dialysis for end-stage kidney disease experience symptoms of depression and/or anxiety, associated with increased mortality, greater health care utilization, and decreased quality of life. It is unknown whether mindfulness-based interventions can improve depression and anxiety symptoms in patients receiving this treatment. METHODS: We conducted an 8-week multicenter randomized controlled trial comparing a brief mindfulness intervention (BMI) vs. an active control (Health Enhancement Program [HEP]) in 55 patients receiving dialysis with symptoms of depression and/or anxiety. The primary outcome was change in Patient Health Questionnaire-9 (PHQ-9) depression scores, with a primary analysis in participants with baseline PHQ-9 ≥ 10, and a secondary analysis including all participants. The secondary outcome was change in Generalized Anxiety Disorder-7 (GAD-7) anxiety scores with corresponding primary and secondary analyses. RESULTS: = 0.01). Secondary analyses revealed no differences between arms. CONCLUSIONS: For patients undergoing dialysis, both BMI and HEP may be helpful interventions for depression symptoms, and BMI may be superior to HEP for anxiety symptoms. Mindfulness-based and other psychosocial interventions may be further evaluated in those undergoing dialysis as treatment options for symptoms of depression and anxiety.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".