Structural Equation Modeling of Self-Compassion and Self-Care in Cancer Care in Iran

Abstract Purpose Self-compassion is theorized to facilitate self-care, yet its structural relationship with self-care behaviors in cancer patients remains underexplored. This study examined the latent constructs of self-compassion and self-care using structural equation modeling (SEM) in Iranian patients with cancer. Methods In this cross-sectional study, 301 cancer patients from Zanjan, Iran (December 2022–September 2023) completed the Self-care Agency Scale for Cancer Patients (SAC) and the Self-Compassion Scale–Short Form (SCS-SF). SEM was applied to examine the latent dimensions of self-compassion (self-kindness, mindfulness, common humanity, self-judgment, isolation, and over-identification) and self-care (adjusting one’s way of living, staying connected and obtaining vital power, and controlling physical condition). Model fit was evaluated using the Root Mean Square Error of Approximation (RMSEA), the Standardized Root Mean Square Residual (SRMR), the Comparative Fit Index (CFI), and the Tucker-Lewis Index (TLI). Multivariable regression identified predictors of self-care. Results SEM demonstrated excellent model fit (CFI = 0.98, RMSEA = 0.06). Self-compassion significantly predicted self-care (β = 0.85, 95% CI: 0.78–0.92, p < .001), explaining 77% of its variance. Mindfulness was the most substantial self-compassion component (β = 0.78–1.09), and “adjusting one’s way of living” was the dominant self-care factor (β = 0.90). Regression analysis revealed that self-compassion, education, cancer duration, and diagnosis awareness collectively accounted for 23% of the variance in self-care (p < .001). Conclusions This study shows that self-compassion, particularly mindfulness, is a strong predictor of self-care among cancer patients. Targeted interventions that foster self-compassion may enhance an individual's capacity for self-care. Further research should examine the cultural and temporal influences on these relationships.