The Self-Compassion Scale: Validation and Psychometric Properties within the Exploratory Structural Equation Modeling Framework

The Self-Compassion Scale (SCS) is one of the several tools for measuring compassionate self-attitude. Despite its popularity, there is an ongoing controversy regarding its factor structure. Previous studies employing exploratory structural equation modeling (ESEM) found support for the single-bifactor (one general and six group factors) model over the competing two-bifactor (two general factors representing compassionate and uncompassionate self-responding and six group factors) model. Here, we replicated and extended previous ESEM studies through examining the validity and dimensionality of different bifactor models in a sample of UK adults. Model fit was examined across two estimators: maximum likelihood and weighted least square mean and variance adjusted. Finally, we investigated whether one or two observed scores of the SCS can better identify cases of depression, anxiety, and mental wellbeing. Both bifactor models showed good fit to the data irrespective of the estimators used, but only the single-bifactor model demonstrated satisfactory convergent and criterion validity and unidimensionality. The total observed SCS score detected depression, anxiety and high mental wellbeing with higher accuracy than any of the two scores. Overall, we propose to use the total score of the SCS in further research and practice.