Unpacking posttraumatic growth: Identifying predictors in trauma-affected individuals using machine learning

Emotion regulation influences psychological responses to trauma, with event-related rumination affecting the development of posttraumatic stress disorder and posttraumatic growth (PTG). Deliberate rumination-conscious, intentional reflection on negative life events-is key to fostering growth and resilience. However, it remains unclear which aspects of deliberate rumination best predict PTG and whether these vary across PTG dimensions (e.g., Relating to Others, Appreciation of Life).

This cross-sectional study examined PTG predictors among 710 individuals meeting posttraumatic stress disorder Criterion A. Deliberate rumination, posttraumatic stress disorder symptoms, trauma-related aspects, and demographic variables were considered as potential predictors of PTG. A machine learning model (Random Forest) was employed to identify key predictors and assess variation in predictive performance across PTG dimensions.

The model achieved a root-mean-square error of 0.81 and R² of .32 for overall PTG level. Domain-specific models showed slightly lower but comparable performance (root-mean-square error = 0.83-0.87, R² = .22-.29). Feature importance analysis highlighted the importance of specific aspects of deliberate rumination for PTG, particularly reflection on how the traumatic experience changed one's life, what was learned, and its future meaning. Confronting one's feelings about the event and belief reevaluation also predicted higher growth. In contrast, trauma-related and demographical factors contributed minimally. Exploratory analyses suggested that reflecting on life changes and future implications was important across most PTG dimensions.

Although cross-sectional, our findings underscore the role of emotion regulation in fostering PTG, with specific aspects of deliberate rumination contributing uniquely to different growth dimensions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).