Individual Mindfulness-Based Cognitive Therapy and Cognitive Behavior Therapy for Treating Depressive Symptoms in Patients With Diabetes: Results of a Randomized Controlled Trial
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Bibliographic record
Abstract
OBJECTIVE: Depression is a common comorbidity of diabetes, undesirably affecting patients' physical and mental functioning. Psychological interventions are effective treatments for depression in the general population as well as in patients with a chronic disease. The aim of this study was to assess the efficacy of individual mindfulness-based cognitive therapy (MBCT) and individual cognitive behavior therapy (CBT) in comparison with a waiting-list control condition for treating depressive symptoms in adults with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: In this randomized controlled trial, 94 outpatients with diabetes and comorbid depressive symptoms (i.e., Beck Depression Inventory-II [BDI-II] ≥14) were randomized to MBCT (n = 31), CBT (n = 32), or waiting list (n = 31). All participants completed written questionnaires and interviews at pre- and postmeasurement (3 months later). Primary outcome measure was severity of depressive symptoms (BDI-II and Toronto Hamilton Depression Rating Scale). Anxiety (Generalized Anxiety Disorder 7), well-being (Well-Being Index), diabetes-related distress (Problem Areas In Diabetes), and HbA1c levels were assessed as secondary outcomes. RESULTS: Results showed that participants receiving MBCT and CBT reported significantly greater reductions in depressive symptoms compared with patients in the waiting-list control condition (respectively, P = 0.004 and P < 0.001; d = 0.80 and 1.00; clinically relevant improvement 26% and 29% vs. 4%). Both interventions also had significant positive effects on anxiety, well-being, and diabetes-related distress. No significant effect was found on HbA1c values. CONCLUSIONS: Both individual MBCT and CBT are effective in improving a range of psychological symptoms in individuals with type 1 and type 2 diabetes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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