Breaking the Chain: A Computational Approach to Identify Optimal Treatment Strategies for Rumination

Background. Rumination is a key risk factor for depression. Based on influential theories of rumination, this study aimed to model and evaluate intervention strategies.Methods. 95 adults at risk for depression completed ≥50% of a 21-day ecological momentary assessment. Idiographic network models were estimated and Control Theory principles applied to identify intervenable nodes and simulate effects of Cognitive Training, Self-System Therapy, Metacognitive Therapy and combined intervention approaches on rumination and related variables.Results. Constructs from self-regulatory and metacognitive models of rumination appeared among the most intervenable variables. Promotion focus and Negative beliefs about rumination had the greatest simulated impact. Negative beliefs also showed broad reach in its impact. Simulated intervention effects remained focal, and intervention order did not affect outcomes. We observed substantial individual variability in treatment response.Conclusion. Control Theory offers a promising framework for identifying intervention targets. Findings underscore the importance of individual differences in rumination dynamics.