Description

Research Background Traditional psychotherapy research tends to emphasize description rather than explanation, relying excessively on data accumulation while neglecting theoretical construction and development (Gelo \& Salvatore, 2016). Complex network theory and its related methods can overcome the limitations of traditional empiricism, providing a deeper theoretical framework and analytical tools for psychotherapy research. By applying complex network methods, it becomes possible to comprehensively analyze the multidimensional and multicausal dynamic relationships between symptoms or psychological variables during psychotherapy, thus gaining a clearer understanding of the processes underlying the development and recovery of mental health problems.

Network analysis can reveal the direct connections between different variables (Borsboom, 2017), rather than relying solely on changes in overall mean levels. Combined with multi-time-point measurement designs, researchers can track gradual changes in relationships between variables during the intervention, thereby identifying which associations change first in the therapeutic process and which variables may play key roles throughout the intervention (Blanken et al., 2019; Cervin et al., 2020). This contributes to an in-depth exploration of the mechanisms underlying psychological interventions and a more comprehensive understanding of change patterns in the therapeutic process.

Mindfulness-Based Interventions (MBIs) are a form of psychotherapy whose effectiveness has been widely validated (Wielgosz et al., 2019). Through regular mindfulness practice, individuals tend to develop healthier behavioral patterns, such as reduction of substance abuse, self-harm, suicidal behaviors, and eating disorder symptoms (Schuman-Olivier et al., 2020). Mindfulness-centered interventions are applicable to both clinical and non-clinical populations: not only to patients with physical or mental disorders (Carlson, 2012; Turgon et al., 2019), but also to individuals experiencing behavioral or emotional distress (Ju, 2022; Ma et al., 2018), all of whom can benefit from short-term or long-term mindfulness practice. Both traditional face-to-face formats and online mindfulness programs have been shown to improve emotional well-being and enhance quality of life (Li et al., 2025; Taylor et al., 2021). The convenience and accessibility of online interventions, in particular, enable more people experiencing emotional distress to receive continuous psychological support.

In addition to studying the efficacy of interventions, understanding the mechanisms of mindfulness interventions is equally important. Many researchers have begun to explore the mechanisms underlying Mindfulness-Based Stress Reduction (MBSR) and Mindfulness-Based Cognitive Therapy (MBCT) (Gu et al., 2015; Maloney et al., 2024). Traditional mechanism studies are mostly based on mediation models that conceptualize mechanisms as static variables linking interventions and outcomes (Kazdin, 2007), making it difficult to capture the dynamic interactions among multiple variables (such as distress tolerance, experiential avoidance, and cognitive flexibility) during the intervention process. The cross-diagnostic interactions and longitudinal predictive relationships between these transdiagnostic factors and anxiety or depressive symptoms during intervention remain unclear.

Therefore, to gain a deeper understanding of how mindfulness interventions "take effect" and the "change patterns" that occur during the process, this study is based on Liu's (2024) Rhombus Model of Psychopathology in Emotional Distress. Using a randomized controlled trial design, weekly measurements will be conducted on individuals participating in an online mindfulness intervention. By applying network analysis methods, this study will focus on the weekly dynamics of psychopathological and symptom networks formed by key mechanism variables-distress tolerance, experiential avoidance, life engagement, and cognitive flexibility-as well as anxiety and depression symptoms during the intervention. The aim is to systematically reveal the dynamic processes and core pathways through which mindfulness interventions drive psychological change.

Summary and Outlook

Summary of current research on mindfulness programs and main findings:

1. Existing studies have shown that online mindfulness programs help alleviate stress, anxiety, depression, and other forms of emotional distress.
2. The mechanisms underlying online mindfulness programs remain unclear. Traditional mechanism studies cannot capture the multidimensional and multicausal interactions between mechanism and outcome variables, nor their temporal dynamics.
3. Network analysis and dynamic systems analysis methods have shown promising potential in clinical science.

Based on the above summary, the following issues need to be further explored:

1. How do the psychopathological networks formed by transdiagnostic factors and anxiety/depression symptoms evolve week by week during mindfulness intervention?
2. During different stages of the intervention, which mechanism variables change first, and which changes may predict later treatment effects? Research Objectives

Based on the above summary, the overall objective of this study is to reveal the weekly dynamic characteristics and key pathways of psychological mechanisms and symptom networks among individuals with emotional distress during mindfulness intervention. The specific objectives are as follows:

1. To construct a weekly psychopathological network model of the mindfulness intervention process, systematically depicting the structural relationships among distress tolerance, experiential avoidance, cognitive flexibility, life engagement, and anxiety and depression symptoms;
2. To identify key mechanism variables and their temporal effects during intervention, revealing which psychological mechanisms change first and subsequently lead to improvements in other variables or symptoms;
3. To compare differences in network structures across different stages of intervention, clarifying the evolving patterns of network connection strength and node centrality indicators during the process.

Research Design The participants in this study will be adults. Participants will be recruited voluntarily and screened based on questionnaires included in the informed consent process. Inclusion criteria: 18 years or older, experiencing emotional distress such as depression or anxiety (Kessler-10 score \> 21), no prior experience with mindfulness meditation, no current self-harm or suicidal risk, no bipolar disorder or schizophrenia, no history of substance abuse, and no severe personal trauma history.

After being randomly assigned to an intervention group or a waitlist control group, participants in the intervention group will take part in the self-guided mindfulness intervention for emotional distress, with a total of ten assessments: before the intervention, after each week during the intervention, after the intervention, and one week after one month post-intervention. The questionnaires will include, but are not limited to, measures of mindfulness, distress tolerance, experiential avoidance, cognitive flexibility, life engagement, and emotional distress. The waitlist control group will be allowed to participate in the self-guided mindfulness intervention for emotional distress after completing the ten assessments.

Withdrawal criteria: failure to complete questionnaires for two consecutive times; failure to check in via the mini-program for seven consecutive days.

Participants

Sample size:

The intervention group will include five classes conducted simultaneously, with a maximum capacity of 250 participants.

The control group will include an equivalent number of 250 participants.

Measures

Demographics, K10, PHQ-9, GAD-7, OASIS, ODSIS, FFMQ-SF, TTT, CFI, BEAQ, DTS, ELS, RNT (Repetitive Negative Thinking), CPSS-SF.