Research on health information avoidance behavior and influencing factors of cancer patients-an empirical analysis...

To explore the health information avoidance behaviors and influencing factors of cancer patients, and to construct a structural equation model to analyze the mediating roles of self-efficacy and negative emotions in the process of generating health information avoidance behaviors of cancer patients.

A face-to-face electronic questionnaire was used to collect data. Applying a chi-square test and multivariate logistic regression model to analyze the role of different socio-demographic factors in influencing health information avoidance behavior of cancer patients; applying structural equation modeling to analyze the role mechanism of health information avoidance behavior of cancer patients.

The results of multivariate logistic regression analysis revealed that socio-demographic factors of per capita monthly household income, marital status, occupation, treatment modality, years of use of smart devices, and weekly hours of reading health information had an impact on health information avoidance behavior of cancer patients. All fit indices of the structural equation model were within acceptable limits,(CMIN/DF = 2.285,RMSEA = 0.045,CFI = 0.949,IFI = 0.949,RFI = 0.902,TLI = 0,942).The results of the mediating effect found that self-efficacy mediated the paths of information overload and privacy concern to health information avoidance behavior, respectively; negative emotions mediated the paths of information overload and privacy concern to health information avoidance behavior, respectively; and self-efficacy mediated the path from social support to health information avoidance behavior.

Sociodemographic factors influencing cancer patients' health information avoidance behaviors include per capita monthly household income, occupation, treatment modality, number of years of smart device use, and number of hours per week reading health information. Self-efficacy and negative emotions mediated the analytic model of health information avoidance behavior in cancer patients, respectively.