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Dynamic Mechanisms and Efficacy of Online Mindfulness-Based Cognitive Therapy for Current Depression: A Randomized Controlled Trial Using Network Intervention Analysis

Mingyang Zhou, Jingyi Jiang, Zenan Liu, Xingwei Luo, Taisheng Cai

preprint DOI: 10.2139/ssrn.6145953 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Randomized controlled trial
Sample size 64
Population Patients currently experiencing a depressive episode
Duration 8-week intervention, with assessments at baseline, week 4, week 8, and one-month follow-up (week 12)
Measures BDI, SAS, FFMQ, RRS, SRT
Topics Depression Meditation
Key findings Online MBCT reduced depressive symptoms relative to a waitlist control, with a between-group difference at one-month follow-up (Cohen's d = 0.75), and also improved anxiety, mindfulness, rumination, and negative interpretation bias. Network analysis indicated the effects were predominantly indirect, mediated by changes in mindfulness facets (nonjudging, nonreactivity) and rumination (brooding, reflective pondering).

Abstract

Background: Mindfulness-Based Cognitive Therapy (MBCT) has demonstrated efficacy in preventing depression relapse and alleviating residual symptoms. However, evidence for its effectiveness in patients currently experiencing depressive episodes—particularly when delivered online—remains limited. This study evaluated the therapeutic effects and dynamic symptom-level mechanisms of online MBCT in patients with current depression using Network Intervention Analysis (NIA).

Method: In a randomized controlled trial, participants currently experiencing depressive episodes (N = 64) were allocated to online MBCT group or Waitlist control group. The MBCT program comprised eight weekly group sessions delivered via synchronous videoconferencing, supplemented by home practice. Outcomes were assessed at baseline (T0), mid-intervention (T1, week 4), post-intervention (T2, week 8), and one-month follow-up (T3, week12). Primary and secondary outcomes included depressive symptoms (BDI), anxiety (SAS), mindfulness (FFMQ), rumination (RRS), and negative interpretation bias (SRT). Generalized Linear Mixed Models (GLMM) estimated treatment effects, and NIA examined direct and indirect pathways within symptom networks over time.

Results: GLMM showed significant group and time effects for depressive symptoms, with between-group differences emerging at T3 (Cohen’s d = 0.75). Online MBCT also produced significant improvements in anxiety, mindfulness, rumination, and negative interpretation bias. NIA revealed that treatment effects were predominantly indirect, mediated by changes in key psychological processes—particularly facets of mindfulness (nonjudging, nonreactivity) and rumination (reflective pondering, brooding). Early-stage improvements primarily targeted negative interpretation bias and rumination, whereas later stages emphasized describing, nonjudging of inner experience, and nonreactivity to inner experience.

Conclusion: Online MBCT is effective in reducing depressive and anxiety symptoms in patients with current depression, with sustained benefits at follow-up. The intervention operates mainly through indirect effects, highlighting the role of mindfulness and rumination processes as potential therapeutic targets. These findings support the feasibility of synchronous online MBCT and underscore the value of network-based approaches for elucidating treatment mechanisms.