Trajectories and predictors of social avoidance in female patients with breast cancer

Abstract

Background: Social avoidance plays an important role in influencing quality of life among patients with breast cancer. Social avoidance behaviors change with treatment periods. However, the trajectory patterns and the predictive factors have not been fully studied. Objective: This study examined the growth trajectory of social avoidance and its predictors in patients with breast cancer. Materials and methods: A total of 176 patients with breast cancer in a university hospital in Shaanxi Province, China, were followed up four times over 6 months following surgery, and data from the final 144 patients were analyzed. The growth mixed model (GMM) was used to identify the trajectory categories, and the predictive factors of the trajectory types were analyzed by logistic regression. Results: The best-fit growth mixture modeling revealed three class models: persistent high social avoidance group (Class 1), social avoidance increased first and then decreased group (Class 2), and no social avoidance group (Class 3), accounting for 13.89, 31.94, and 54.17% of patients, respectively. Single-factor analysis showed that family income per capita, residence, and temperament type were related to the social avoidance trajectory. Logistic regression analysis showed that only temperament type was an independent predictor of the social avoidance trajectory, and patients with melancholia were more likely to have persistent high social avoidance. Conclusion: Our study proved the heterogeneity of social avoidance behaviors and the influencing effect of temperament type on the development of social avoidance behaviors in Chinese patients with breast cancer. Health professionals should pay more attention to patients who are at higher risk of developing a persistent social avoidance pattern and provide target interventions.