Response-to-Treatment for Comorbid Post-Traumatic Stress and Substance Use Disorders: the Value of Combining Person- and Variable-Centered Approaches

JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT(2020)

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摘要
Optimizing treatment for co-occurring post-traumatic stress disorder and substance use disorder (PTSD+SUD) is critically important. Whereas treatments have been designed that target PTSD+SUD with some success, these treatments do not benefit all. Data-driven approaches that combine person- and variable-centered methods, such as parallel process latent class growth analysis (PP-LCGA) can be used to identify response-to-treatment trajectories across both PTSD symptoms and substance use. The current study employed PP-LCGA separately in two randomized clinical trials (study 1 n = 81, Mean age = 40.4 years, SD = 10.7; study 2 n = 59, Mean age = 44.7 years, SD = 9.4) to examine PTSD symptom response and percentage of days using substances across treatment trials comparing Concurrent Treatment of PTSD and SUD using Prolonged Exposure and Relapse Prevention. Results revealed four PTSD+SUD profiles for study one and three PTSD+SUD profiles for study two. For PTSD symptoms, response trajectories could be broadly classified into treatment responders and non-responders across both studies. For substance use, response trajectories could be broadly classified into declining, moderately stable, and abstaining profiles. When considering PTSD symptoms and substance use trajectories together, profiles emerged that would have been missed had these treatment outcomes been considered separately.
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关键词
Post-traumatic stress disorder,Substance use disorder,Intervention,Growth mixture modeling
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