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Cross-sectional psychometric evaluation demonstrates optimal fit for a six-factor model of the Self-Compassion Scale Short Form, suggesting the value of subscale scoring over total scores.
Objectives The purpose of this study was to examine the factor structure and construct validity of the Self-Compassion Scale Short Form (SCS-SF) in a US convenience sample recruited during the SARS-CoV-2 pandemic. Given prior mixed findings and concerns about the factor structure and the appropriate use (e.g., reliance on the total score) of the SCS-SF across populations, this study aimed to assess whether the scale’s factor structure in this sample aligns with previously hypothesized models. Method Four models proposed in the literature were tested using confirmatory factor analysis (CFA). Model 1 was a six-factor correlated model, Model 2 was a higher-order model with six first-order subscale factors and one second-order self-compassion factor, Model 3 was a two-factor correlated model, and Model 4 was a one-factor model. Results The CFA indicated that the six-factor correlated model demonstrated the best overall descriptive fit, with the two-factor model showing acceptable fit. There were significant correlations between self-compassion and symptoms of depression and anxiety, compassion for others, and perceived stress. Conclusions Results from the CFA and correlational analyses suggest that reporting subscale or composite scores may provide a more nuanced understanding of the links between self-compassion and mental health outcomes, rather than relying solely on a total SCS-SF score. Preregistration This study is not preregistered.
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Manjanatha et al. (2026) studied this question.
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