Mindfulness-based cognitive therapy in patients with depression: current perspectives
Bibliographic record
Abstract
Mindfulness-based cognitive therapy (MBCT) was developed to prevent relapse in individuals with depressive disorders. This widely used intervention has garnered considerable attention and a comprehensive review of current trends is warranted. As such, this review provides an overview of efficacy, mechanisms of action, and concludes with a discussion of dissemination. Results provided strong support for the efficacy of MBCT despite some methodological shortcomings in the reviewed literature. With respect to mechanisms of action, specific elements, such as mindfulness, repetitive negative thinking, self-compassion and affect, and cognitive reactivity have emerged as important mechanisms of change. Finally, despite a lack of widespread MBCT availability outside urban areas, research has shown that self-help variations are promising. Combined with findings that teacher competence may not be a significant predictor of treatment outcome, there are important implications for dissemination. Taken together, this review shows that while MBCT is an effective treatment for depression, continued research in the areas of efficacy, mechanisms of action, and dissemination are recommended.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".