Linear and nonlinear modeling of life satisfaction in relation to resilience and positive emotions

This study explores the complex relationships among life satisfaction, positive emotions, and psychological resilience in 1170 Greek adults. Understanding these interactions is crucial for enhancing well-being and tailoring effective interventions. We employed linear and nonlinear methods, including Generalized Additive Models, Random Forests, Gradient Boosting Machines, and Neural Networks, to analyze the data and uncover intricate patterns. The analysis revealed that resilience and positive emotions are non-linearly associated with life satisfaction. At lower resilience levels, increases in resilience do not consistently lead to higher life satisfaction, especially in the absence of strong positive emotions. However, with intense positive emotions, life satisfaction increases significantly at higher resilience levels, indicating synergistic effects. Notably, resilience alone is insufficient for high life satisfaction without substantial positive emotions. These findings underscore the limitations of linear models in capturing the complexity of these relationships and demonstrate that nonlinear models outperform linear ones in explaining life satisfaction. This study highlights the need for more sophisticated nonlinear methodologies to understand the intricate dynamics between psychological resilience and positive emotions. By adopting these advanced approaches, we can better reflect the complex realities of human well-being and devise effective strategies to enhance life satisfaction globally.