Predictors of outcome during inpatient psychotherapy for posttraumatic stress disorder: a single-treatment, multi-site, practice-based study

Objective: The aims of this study were to determine the effectiveness of a routine clinical care treatment and to identify predictors of treatment outcome in PTSD inpatients. Methods: A routinely collected data set of 612 PTSD inpatients (M = 42.3 years [SD = 11.6], 75.7% female) having received trauma-focused psychotherapy was analyzed. Primary outcome was the clinical symptom severity change score, secondary outcomes were assessed using functional, anxiety, and depression change scores. Hedges g-corrected pre-post effect sizes (ES) were computed for all outcomes. Elastic net regulation as a data-driven, stability-based machine-learning approach was used to build stable clinical prediction models. Results: Hedges g ES indicated medium to large effects on all outcomes. The results of the predictor analyses suggested that a combined predictor model with sociodemographic, clinical, and psychometric variables contribute to predicting different treatment outcomes. Across the clinical and functional outcome, psychoticism, total number of diagnoses, and bronchial asthma consistently showed a stable negative predictive relationship to treatment outcome. Conclusion: Trauma-focused psychotherapy could effectively be implemented in a routine inpatient setting. Some important prognostic variables could be identified. If the proposed models of predictors are replicated, they may help personalize treatment for patients receiving routine clinical care.