Mindfulness-based cognitive therapy for depression: trends and developments
Bibliographic record
Abstract
Meagan B MacKenzie,1 Nancy L Kocovski21Department of Psychology, Ryerson University, Toronto, ON, Canada; 2Department of Psychology, Wilfrid Laurier University, Waterloo, ON, CanadaAbstract: Mindfulness-based cognitive therapy (MBCT) was developed as a psychological intervention for individuals at risk of depressive relapse. Possible mechanisms of change for this intervention are in line with its theoretical underpinnings, and include increases in mindfulness and/or decreases in negative repetitive thoughts. This review provides an overview of current trends in MBCT research, including efficacy and questions regarding the specific effects of MBCT in light of recent comparisons with structurally equivalent control conditions, mechanisms of change, and moderators of treatment outcome. In addition, future directions are discussed, such as challenges with training an adequate number of therapists and disseminating this therapy.Keywords: MBCT, efficacy, mechanisms of change, dissemination, moderators
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".