Psychiatry 2020: Mediating Role 0f Self-Esteem in The Relationship of Mindfulness to Resilience and Stress
The present study seeks to examine the effect of mindfulness on resilience and stress and whether it would be mediated by self-esteem. Participants include 462 undergraduates (314 males and 148 females) from Indian university completed mindfulness, self-esteem, resilience and stress scales. Structural Equation Modeling (SEM) indicated that self-esteem acted as a full mediator of the association between mindfulness and resilience. Self-esteem also acted as a partial mediator between mindfulness and stress. A multi-group analysis also indicated that the paths in the mediational model were not moderated by gender, supporting the robustness of the model. The findings suggest that mindfulness and self-esteem play an influential role in mental health promotion. Mindfulness may foster resilience as higher mindfulness levels in people make them able to respond to difficult situations without reacting in non-adaptive and automated ways. Mindful people can better cope with difficult emotions and thoughts without becoming overwhelmed, as they tend to be more creative and are open to new perceptual categories (Langer & Moldoveanu, 2000; Wallace & Shapiro, 2006). Mindfulness may lead to less rumination and habitual worrying, leading to higher resilience (Shapiro et al, 2007; Verplanken & Fisher, 2014). Thompson, Arnkoff, and Glass (2011) reported in a review of mindfulness and resilience to trauma; that mindfulness promotes psychological resilience following trauma by an accepting orientation toward experiences. First, an initial correlational analysis was used to examine the relationships between mindfulness, self-esteem, resilience, and stress. The mediation role of self-esteem was tested using twostep Structural equation modeling (SEM) procedure using AMOS 18.0. A bias-corrected bootstrapping procedure was also employed to test the significance of the mediation effects of self-esteem. 10000 bootstrapping samples were generated according to random sampling using the data set (N=462). Firstly, the measurement model was calculated. After getting satisfactory results of the measurement model, we tested the structural model in the AMOS Software. The fit of the model to data was evaluated by calculating some indices recommended by Hu and Bentler (1999) and Kline (2011). Accordingly, goodness-of-fit criteria were used in the current study that acknowledged the potential for acceptable fit (χ2/df0.90, SRMR0.95). As each latent factor was having multiple items, we divided the items into parcels to control inflated measurement errors. Parcels were created using an item-to-construct balance approach (Little et al., 2002). We divided the items for each of the mindfulness, self-esteem, and resilience latent factors into three parcels and for stress latent factor two parcels were formed.