Exploring predictors of clinical response to a transdiagnostic, internet-delivered psychological intervention for people with chronic health conditions

Introduction: This study aims to identify participant- and treatment-related characteristics associated with response and deterioration in an internet-delivered intervention for people with chronic health conditions. Understanding these factors is critical for the development and delivery of these treatments. Method: Data were drawn from a randomized controlled trial of a transdiagnostic, internet-delivered intervention for people with chronic health conditions (N = 590). Demographic (e.g., age, gender, employment, education), clinical (e.g., health condition, medication usage, multimorbidity), psychological (e.g., baseline symptom severity), and treatment-related variables were examined. Outcomes included clinically meaningful response (>= 50% improvement in symptoms) and deterioration (>= 30% increase in symptoms) in depression, anxiety, and self-reported disability. Multivariable regression models were built to identify significant predictor variables of response and deterioration. Additional indicators of model fit were reported, including the area under the curve and Negelkerke's R2. Results: Several predictors of response and deterioration were identified within individual models; however, few predictors were significant across >1 outcome, while none were consistent across all three outcomes. The final models predicting participant outcomes explained 7%-16% of the variance in the likelihood of response or deterioration. Conclusion: Results suggest that few predictors are meaningfully associated with participants' response or deterioration to treatment. Encouragingly, potentially prognostic variables (e.g., more severe baseline symptoms and multimorbidity) were also nonsignificant. The results support the broad applicability of this treatment approach and for the role of remotely delivered interventions within stepped care frameworks.