TY - JOUR
T1 - Response-to-Treatment for Comorbid Post-Traumatic Stress and Substance Use Disorders
T2 - the Value of Combining Person- and Variable-Centered Approaches
AU - Allan, Nicholas P.
AU - López-Castro, Teresa
AU - Hien, Denise A.
AU - Papini, Santiago
AU - Killeen, Therese K.
AU - Gros, Daniel F.
AU - Ruglass, Lesia M.
AU - Barrett, Emma
AU - Back, Sudie E.
N1 - Funding Information:
The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of NIH, the VA, or the United States government.
Funding Information:
The authors would like to acknowledge support from the National Institute on Drug Abuse grants R01 DA030143 (Back, S.E.), K02 DA039229 (Back, S.E.), and R01 DA10843 (Hien, D. A.).
Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
KW - Growth mixture modeling
KW - Intervention
KW - Post-traumatic stress disorder
KW - Substance use disorder
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U2 - 10.1007/s10862-020-09803-w
DO - 10.1007/s10862-020-09803-w
M3 - Article
AN - SCOPUS:85084002456
SN - 0882-2689
VL - 42
SP - 725
EP - 738
JO - Journal of Psychopathology and Behavioral Assessment
JF - Journal of Psychopathology and Behavioral Assessment
IS - 4
ER -