Mediators of change in online mindfulness-based cognitive therapy: A secondary analysis of a randomized trial of mindful mood balance.
Bibliographic record
Abstract
OBJECTIVE: Digital delivery of mindfulness-based cognitive therapy through the Mindful Mood Balance (MMB) program is clinically effective (Segal et al., 2020); however, the mechanisms through which this program delivers its benefits have not been established. METHOD: This study investigates the differential impact of the MMB program paired with usual depression care (UDC) compared to UDC alone on the putative targets of self-reported mindfulness, decentering, and rumination and the extent to which change in these targets mediates subsequent depressive relapse among a sample of predominantly White, female participants, with residual depressive symptoms. RESULTS: The MMB program relative to UDC was associated with a significantly greater rate of change in decentering (t = 4.94, p < .0001, d = 0.46), mindfulness (t = 6.04, p < .0001, d = 0.56), and rumination (t = 3.82, p < .0001, d = 0.36). Subsequent depressive relapse also was mediated by prior change in these putative targets, with a significant natural indirect effect for decentering, χ2(1) = 7.25, p < .008, OR = 0.57; mindfulness, χ2(1) = 9.99, p < .002, OR = 0.50; and rumination, χ2(1) = 12.95, p < .001, OR = 0.35. CONCLUSIONS: These findings suggest the mechanisms of MMB are consistent with the conceptual model for mindfulness-based cognitive therapy and depressive relapse risk and that such processes can be modified through digital delivery. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".