Determinants of Depressive Symptoms Among Patients with Rheumatoid Arthritis in China: A Structural Equation Model

This study aimed to examine how personality traits, social support and clinical features including pain, disease activity, functional status, sleep quality, and fatigue influence on depressive symptoms in Chinese rheumatoid arthritis (RA) patients.

This study was conducted from November, 2022 to June, 2023 among Chinese RA patients. Pain, disease activity, functional status, sleep quality, fatigue, social support, personality traits, and depressive symptoms were assessed. The following relationships among three hypotheses were analyzed by structural equation model (SEM): H₁: clinical features have a direct effect on depressive symptoms; H₂: personality traits might work as a mediator between clinical features and depression; H₃: social support is related to depressive symptoms, being a direct effect or an indirect effect through clinical features or personality traits.

The final model including 326 RA patients presented a good fit (χ²=103, χ²/df=1.69; GFI=0.96; AGFI=0.93; CFI=0.97; TLI=0.96; RMSEA=0.046). Clinical features had a total effect of 0.59 on depressive symptoms, of which β=0.33 (P=0.013) was an indirect effect through personality traits, indicating a mediating influence between this relationship; moreover, there was a significant direct association between clinical features and depressive symptoms (β=0.26; P=0.022). Personality traits (β=-0.65; P<0.001) had a much stronger relation with depressive symptoms than with clinical features. Social support had a total effect of 0.81 on personality traits, being a direct effect of β=0.52 (P<0.001) and an indirect effect of β=0.29 (P<0.001) through clinical features. The final proposed model explained 77% of the variance of depressive symptoms.

Personality traits had a considerable influence upon depressive symptoms, while social support seemed to have a major effect on personality traits. It is necessary to apply comprehensive assessment and interventions of patients' personality traits, clinical features, as well as social support, which could optimize their mental health.