Can Self-Compassion Predict Future Anxiety and Depression?: A Cross-Lagged Panel Model Analysis in a Dominican Republic Sample

Abstract

Emotional dysregulation, in the form of anxiety and depression, has a significant economic, social and psychological impact on a global scale. Several approaches have been developed in the hope of helping people to better regulate these emotions, with mixed results. Specifically, third-wave therapies seem to perform particularly well. These therapies share the variable of self-compassion, which both in evolutive and practical terms appears to be a key variable in regulating difficult emotional states such as anxiety and depression. The objective of this research was to verify the adjustment of an explanatory model of anxiety and depression, which considers the effect of self-compassion. A sample of 371 residents in Dominican Republic was used and a cross-lagged panel model analysis was carried out. The measurement model fit the data well. Also, it is possible to verify that self-compassion at time 1 predicts depression and anxiety at Time 2 in a theoretically coherent direction. Clinical implications for non-WEIRD countries are discussed.