Text Topics and Treatment Response in Internet-Delivered Cognitive Behavioral Therapy for Generalized Anxiety Disorder: Text Mining Study.

BACKGROUND: Text mining methods such as topic modeling can offer valuable information on how and to whom internet-delivered cognitive behavioral therapies (iCBT) work. Although iCBT treatments provide convenient data for topic modeling, it has rarely been used in this context. OBJECTIVE: Our aims were to apply topic modeling to written assignment texts from iCBT for generalized anxiety disorder and explore the resulting topics' associations with treatment response. As predetermining the number of topics presents a considerable challenge in topic modeling, we also aimed to explore a novel method for topic number selection. METHODS: We defined 2 latent Dirichlet allocation (LDA) topic models using a novel data-driven and a more commonly used interpretability-based topic number selection approaches. We used multilevel models to associate the topics with continuous-valued treatment response, defined as the rate of per-session change in GAD-7 sum scores throughout the treatment. RESULTS: Our analyses included 1686 patients. We observed 2 topics that were associated with better than average treatment response: "well-being of family, pets, and loved ones" from the data-driven LDA model (B=-0.10 SD/session/∆topic; 95% CI -016 to -0.03) and "children, family issues" from the interpretability-based model (B=-0.18 SD/session/∆topic; 95% CI -0.31 to -0.05). Two topics were associated with worse treatment response: "monitoring of thoughts and worries" from the data-driven model (B=0.06 SD/session/∆topic; 95% CI 0.01 to 0.11) and "internet therapy" from the interpretability-based model (B=0.27 SD/session/∆topic; 95% CI 0.07 to 0.46). CONCLUSIONS: The 2 LDA models were different in terms of their interpretability and broadness of topics but both contained topics that were associated with treatment response in an interpretable manner. Our work demonstrates that topic modeling is well suited for iCBT research and has potential to expose clinically relevant information in vast text data.

Feasibility of generic, short, and easy-to-use assessment of psychological distress during psychotherapy: Longitudinal measurement invariance of CORE-10 and -OM.

Objective: While the CORE-10 inventory for Clinical Outcome Routine Evaluation has shown good psychometric properties in cross-sectional assessment, the feasibility of generic, short, and easy-to-use longitudinal assessment of a broadband construct such as the targeted "general psychological distress" remains to be psychometrically demonstrated. Therefore, we investigated longitudinal measurement invariance (LMI) of CORE-10. For comprehensiveness, we also analyzed its parent inventory, CORE-OM. Method: We investigated the LMI of pre- and post-therapy CORE-10 and -OM assessments in a naturalistic treatment register of 1715 patients' short psychotherapies, testing whether the construct of "psychological distress" remained the same across the treatments. Results: We observed good psychometric properties and no violations of LMI for CORE-10 in chi-squared equivalence tests, nor in effect-size-based evaluations. Only the highly sensitive chi-squared difference tests detected LMI violations but these had little practical influence. The CORE-OM data did not fit well with factorial models but this was cross-sectional rather than a genuinely longitudinal (LMI-related) issue. Conclusions: CORE-10 appeared a structurally valid measure of general psychological distress and suitable for longitudinal assessment, whereas the CORE-OM had a less clear factorial structure. Regarding psychometrics, these findings support the use of CORE-10 in longitudinal assessment during psychotherapy and do not support CORE-OM.