Internet-based ACT For PTSD:Development,Efficacy,Mechanism And Matching

The COVID-19 epidemic,which broke out in early 2020 and continues to this day,has brought a huge impact on people’s mental health,especially increasing the prevalence of PTSD worldwide.PTSD is a psychogenic mental disorder that appears after an individual’s experiences or witnesses an unusual catastrophic threatening event,which contains intrusions/re-experiencing,avoidance,negative changes in cognition and emotion,and arousal and reactivity alterations(American Psychiatric Association,2013).Symptoms are characterized by high prevalence and high risk.Current interventions for PTSD are hampered by a lack of transdiagnostic interventions(Gutner et al.,2016),comorbidities(Van Minnen et al.,2015),and high dropout rates(Garcia et al.,2011)and other factors,therefore,exploring effective PTSD intervention methods suitable for the new crown epidemic is crucial for public psychological reconstruction,economic recovery,and social stability.Internet-based Acceptance and Commitment Therapy(iACT)has been pushed to researchers and practitioners with its unique advantages.However,there is no iACT program that can effectively intervene in PTSD in China.Therefore,this study focuses on the development of an Internet-based ACT(iACT)intervention program for PTSD.The specific research routes and results are as follows:In order to clarify the influencing factors of internet-based intervention in PTSD and guide the development of iACT intervention programs for PTSD,Study 1 used network meta-analysis to explore the effect of internet-based intervention on PTSD and its comorbid symptoms based on different theoretical foundations,and subgroup analysis and meta-regression analysis were used to explore the moderating variables affecting the intervention effect and dropout rate.The main conclusions are as follows:(1)Narrative-based CBT may be the optimal therapy for PTSD intervention.Compared with the waiting group,narrative-based CBT and guided CBT can simultaneously alleviate PTSD,depression,anxiety,and improve quality of life;(2)type of traumatic event,support,feedback,specific for PTSD,type of control group,and the sample size significantly affected the intervention effect of PTSD.(3)Whether there is homework and the sample size affect the dropout rate.The primary objectives of Study 2 were to develop an iACT intervention program for PTSD(Study 2-1)and to evaluate the intervention effect of the program(Study 2-2).Research 2-1 develops an iACT intervention program suitable for Chinese cultural background to intervene PTSD through five steps:needs investigation,determination of intervention program script,interactive needs improvement program,initial assessment and determination of intervention program.In the preliminary evaluation step,quantitative(single-group pre-and post-test research design)and qualitative(semi-structured interviews)are combined to preliminarily evaluate the intervention effect of the program.Preliminary research results show that the developed iACT can significantly relieve PTSD and its comorbid symptoms,and the acceptability is good.In order to further evaluate the efficacy and usability of the internet-based intervention program,study 2-2 used a multi-point instantaneous randomized controlled trial,with subjects who met the provisional diagnosis and subthreshold diagnosis of PTSD,and set up an ACT intervention group,a mindfulness intervention group,and a waiting group,using PTSD,anxiety,depression,and post-traumatic growth as outcome variables,to examine the relative and absolute effects of the iACT intervention program on PTSD,and to explore the intervention process.The specific results are as follows:(1)The generalized linear mixed model test the intervention effect of the iACT program.Compared with the waiting group,iACT can significantly relieve the total symptoms of PTSD(d=-0.79),anxiety(d=-0.62),depression(d=-0.51),and significantly improved post-traumatic growth(d=0.46);the effect size of iACT intervention on the above variables was greater than that in the mindfulness group,but the difference was not significant.(2)The latent class growth model found three types of change trajectories of PTSD during the intervention process,namely:the slowest decline group with moderate symptoms,the moderately rapid decline group with severe symptoms,and the fastest decline group with mild symptoms.There was no significant relationship between the change trajectories and the intervention efficacy.(3)The results of the network intervention analysis showed that in the symptom clusters of PTSD,the negative changes of cognition and emotion(cluster D)and arousal(cluster E)were the most directly affected symptoms.In order to further improve the efficacy and efficiency of iACT intervention in PTSD,study 3 explored the psychological mechanisms of iACT intervention in PTSD.Specifically:Re-analyze the data of Study 2-2,using the network intervention analysis to explore the direct and indirect effectsduring the interventionon PTSD of 6 components of ACT,namely,acceptance,cognitive defusion,self-as-context,present awareness,values,and commitment action;latent growth curve modeling(LGCM)revealed the mechanism of these six core components in the intervention of PTSD.This study draws the following conclusions:(1)iACT generally acts first on cognitive defusion and acceptance,only living a valuable life is not directly or indirectly affected by iACT intervention,and the nodes with the highest predictability are committed action and self-as-context.(2)Thefive components of psychological flexibility,except for the present moment awareness,were the mediator variables in the iACT intervention.Study 4 explored patient characteristics suitable for ACT intervention.Machine learning was used to re-analyze the data of study 2-2 to explore the characteristics of patients suitable for iACT intervention and mindfulness intervention,as well as the characteristics of those in the waiting group who could heal themselves,and to build a predictive model for treatment effectiveness.The following conclusions are drawn:(1)The accuracy of machine learning prediction of sample features suitable for intervention is acceptable,and the accuracy can be further improved by larger samples,which is a promising direction.(2)Individuals with inability to meet life needs,higher education level,high negative self-awareness,low PTSD baseline,job stability,extraverted coping style,experienced traumatic events,and high depression baseline are more likely to iACT benefited from intervention in PTSD;no medication,low resistance,low introverted coping style,high educational attainment,female gender,traumatic event early in life,high extraverted coping style,high PTSD baseline,met life needs,low Individuals with psychological flexibility,high self-negative cognition,high self-blame,and high anxiety baseline were more likely to benefit from mindfulness-based interventions for PTSD.Individuals with permanent residence outside the city,stable work status,less negative social cognition,low anxiety baseline,high psychological flexibility,and high self-blame were more likely to heal themselves.This study establishes a complete technical route of internet-based intervention from initial development to verification of effect and acceptability,exploration of psychological mechanism,and investigation of optimal matching,which can provide some references for the development and research of the same type of internet-based intervention.This study has also obtained some conclusions that can guide practice.When developing internet-based intervention programs,taking qualitative research to obtain user feedback is an important step;the intervention is a complex process,and the interaction between the symptoms has a greater effect on the effect of the intervention than the direct effect of the intervention.