Structural validation of the Self-Compassion Scale with a German general population sample

Area of Science:

• Psychological assessment
• Psychometrics
• Personality psychology

Background:

• Published validation studies report varying factor structures for the Self-Compassion Scale (SCS).
• Previous research has not consistently identified a definitive factor structure for the SCS across diverse populations.

Purpose of the Study:

• To assess the factor structure of the Self-Compassion Scale (SCS) in a large, representative German general population sample.
• To determine the most appropriate scoring method for the SCS in this population.

Main Methods:

• Confirmatory factor analysis (CFA) was employed using MPlus to test multiple proposed models of the SCS.
• Six established models and three novel bifactor models were evaluated in a German general population sample.

Main Results:

• The two-factor and six-factor models demonstrated acceptable fit, with comparable indices.
• Bifactor models supported a two-factor structure (positive and negative aspects of self-compassion).
• One-factor, three-factor, and one bifactor model showed poor fit, indicating inadequacy.

Conclusions:

• The two-factor model, comprising positive and negative self-compassion dimensions, is recommended for the German SCS in general population samples.
• The study advises against using a total SCS score due to lack of meaningful variance beyond the two primary factors.
• The positive and negative subscale scores provide a more reliable and meaningful representation of self-compassion.