Factors influencing intentional non-utilization of healthcare: a study using the Andersen model

This study aims to investigate the factors influencing residents' healthcare utilization behavior and provide a scientific basis for enhancing the overall efficiency of healthcare utilization.

A comprehensive analysis was conducted using data from the China General Social Survey (CGSS) project. Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM) were utilized to examine the influences and interrelationships of the three core factors of the Andersen Healthcare Utilization Model (Predisposing Factors, Enabling Resources, and Need), as well as the two extended factors (health behaviors and Medical-service Experience), on residents' decisions regarding the utilization of healthcare services.

A total of 2,230 participants were enrolled in this study. Most were male (55.74%), were married (85.38%), and had junior- and senior-high school educations (45.29%). Mean age was 52.39 years, and 56.32% of participants reported an annual income of <30,000 RMB. EFA distilled influencing factors into four domains: Predisposing and Enabling, Need, Health Behaviors, and Medical-service Experience. The results of the revised SEM indicated that the influence coefficients of Predisposing and Enabling, Need, and Medical-service Experience on Decision to Utilize Health Services (DUHS) were 0.095, -0.104, and 0.093 respectively. Mediation effect test results demonstrated that the indirect effects of Predisposing and Enabling, Need, and Health Behaviors on DUHS were -0.098, 0.024, and -0.017, respectively, all of which were statistically significant. Finally, the fit indices of the modified model indicated an acceptable model fit.

This study showed that unmarried individuals with lower income and job instability exhibit reduced healthcare utilization due to economic barriers and lack of social support. Furthermore, medical service experience is another crucial factor affecting health service utilization. Notably, our findings suggest the need for targeted interventions, including enhanced insurance coverage, improving the quality of medical services and health education campaigns to mitigate disparities in access to health services.