Positive and Negative Interpretation Biases in the Relationship Between Trait Mindfulness and Depressive Symptoms in Primarily White Emerging Adults

Theoretical and empirical work support the value of using an empirically derived model of trait mindfulness and lays the groundwork for questions about how to model mindfulness, how mindfulness and interpretation biases (IBs) are linked, and how IBs may explain the association between mindfulness and depressive symptoms—a major public health concern for emerging adults (EAs).

Exploratory Structural Equation Modeling (ESEM) was used to empirically derive a model of mindfulness from a sample of 258 primarily White EAs. Structural equation models were then built to explore relationships among the individual factors of mindfulness, positive and negative interpretation bias, and depressive symptoms.

Findings suggested a bi-factor (ESEM) model of mindfulness best fit the data, with four factors of attention (ATT), acceptance (AC), non-judgment (NJ), and non-judgmental acceptance (NJAC; the bi-factor). Results showed the NJAC factor to be most robustly related to depressive symptoms through positive and negative IBs (standardized indirect effects: negative biases β =  − 0.12, SE = 0.05, p = .016; positive biases β =  − 0.10, SE = 0.05, p = .035).

Mindfulness is a complex construct that does not reflect an overarching latent factor in this sample but rather is indicated by the separate factors of ATT, NJ, AC, and NJAC that should be considered individually in relation to outcomes. NJAC, and not ATT, contributes to lower levels of depressive symptoms in EAs in part through decreased negative and increased positive IBs.