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Ren, Z., Zhao, C., Bian, C., Zhu, W., Jiang, G., & Zhu, Z. (2019). Mechanisms of the Acceptance and Commitment Therapy: A meta-analytic structural equation model. Acta Psychologica Sinica, 51(6), 662-676.

APA Citation

Ren, Z., Zhao, C., Bian, C., Zhu, W., Jiang, G., & Zhu, Z. (2019). Mechanisms of the Acceptance and Commitment Therapy: A meta-analytic structural equation model. Acta Psychologica Sinica, 51(6), 662-676. DOI: 10.3724/SP.J.1041.2019.00662

Publication Topic
ACT: Empirical
Publication Type
Article
Language
Chinese Simplified
Keyword(s)
acceptance and commitment therapy; meta-analytic structural equation model; mechanism; mediational study; cognitive-behavior therapy
Abstract

Following the Behavioral Therapy and the Cognitive-Behavioral Therapy (CBT), Acceptance and Commitment Therapy (ACT) is considered as one of the third wave of behavioral therapies. ACT is based on the relational frame theory, and its therapeutic model includes 6 components (i.e., acceptance, cognitive defusion, self-as-context, committed action, contact with the present moment, values) and psychological flexibility. What is the empirical evidence for these hypothesized components or mechanisms? In recent years, integrating meta-analysis and structural equation modeling, the meta-analytic structural equation model (MASEM) has made it possible to systematically examine the mechanisms of psychotherapy. Compared to the traditional single randomized controlled trial (RCT) studies, the MASEM combines multiple samples to increase statistical power and obtain more robust model estimates. The current study utilized two-stage structural equation modeling (TSSEM) to examine three aspects of the mechanisms of ACT, including: (1) the mediational effects of psychological flexibility and the 6 components, (2) the unique mechanisms of ACT compared to CBT, and (3) the generalizability of these mechanisms to internet-based ACT interventions.

Studies were identified by searching Web of science, PsycARTICLES, PsycINFO, Pubmed, Elsevier, EBSCO, Wiley Online Library from the first available date until November, 2017. We used the search term Acceptance and Commitment Therapy combined with acceptance, cognitive defusion, self-as-context, committed action, contact with the present moment, values, or psychological flexibility. Selection criteria included: (1) adult sample (age > 18), (2) RCT or quasi-experimental design, which measured pre-post change with ACT interventions, (3) quantitative measures of psychological outcomes (clinical or non-clinical) before and after treatment, and (4) quantitative measures of mediational variables at pre and post treatment. Excluding criteria were (1) not having a control group, (2) mixed intervention studies, which integrated ACT with other interventions, or included the Acceptance component but not the complete ACT model, or used CBT with the Acceptance component, and (3) medication treatment as the control group. The metaSEM package in R was used for the TSSEM analysis to examine the mechanisms of ACT.

The literature search resulted in 50 studies, involving issues such as pain disorder, personality disorder, depression, anxiety, substance abuse, and work-related burnout among healthy populations. Most studies examined psychological flexibility (k = 39), followed by contact with the present moment (k = 14), acceptance (k = 6), cognitive defusion (k = 9), and values (k = 5), whereas the studies of self-as-context (k = 1) and committed action (k = 1) were excluded from further MASEM analysis due to a low number of publications. Results indicated that (1) the mediational effects of psychological flexibility, acceptance, contact with the present moment, and values were significant, while the effects of cognitive defusion were not significant, (2) the mechanisms of ACT are evident in internet-based interventions, suggesting the generalizability of these mechanisms, and (3) compared to the traditional CBT, the hypothesized mechanisms of ACT have their unique advantages.

Implications for future studies: (1) measure all 6 core mechanisms as comprehensively as possible; (2) focus more on the increase of wellbeing as opposed to improvement of symptoms; (3) use RCT based multiple measurements combined with the experience sampling method; and (4) apply more advanced statistical methods in addition to the traditional mediation statistics.