In Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE : Prior studies of Dialectical Behavior Therapy (DBT) for borderline personality disorder (BPD) have yielded heterogeneous findings on what factors differentiate individuals with or without sufficient treatment response, highlighting the need for further research.
METHOD : We investigated a sample of 105 individuals with BPD receiving a 6-month course of DBT. Participants were categorized as sufficient or insufficient responders using clinical and statistical change indices (based on emotion dysregulation, BPD symptom severity, utilization of DBT skills, and functional impairment). Sociodemographic, clinical severity, and treatment process factors were tested as potential predictors of treatment response using a machine learning approach (LASSO regression).
RESULTS : Two cross-validated LASSO regression models predicted treatment response (AUCs > .75). They suggested that higher homework completion rate, retention in treatment, and greater baseline severity were the most important predictors of DBT treatment response indicated by BPD symptom severity and utilization of DBT skills. Favorable effects of some aspects of therapeutic alliance during initial sessions were also found.
CONCLUSIONS : Future research may benefit from consolidating the criteria of treatment response, identifying clinically relevant variables, and testing the generalizability of findings to enhance knowledge of insufficient treatment response in DBT for BPD.
Yin Qingqing, Stern Molly, Kleiman Evan M, Rizvi Shireen L
2022-Oct-28
Dialectical Behavior Therapy, LASSO regression, borderline personality disorder, machine learning, treatment response
