Research on the Process and Influencing Factors of Online Diabetes Information Users' Avoidance Behavior: A...

Users' avoidance behavior of health information has received growing attention recently, but research into users' avoidance behavior of diabetes information remains limited. This paper aims to reveal the process and the factors of avoiding online diabetes information. The interview, conducted with the critical incident technique, and the diary methods were used to collect 40 true incidents of online diabetes information avoidance from 17 participants. Based on the thematic analysis method and grounded theory, the data were analyzed to identify the key phases of the avoidance process and obtain the factors influencing the occurrence of avoidance behavior. The results showed that the macro-process of online diabetes information avoidance comprised three phases: pre-encountering, encountering, and avoiding after encountering. First, browsing, searching, or social interaction provide the context for encountering; second, the encountering occurrence consists of three steps-noticing the stimuli, reacting to stimuli, and examining the content; and third, to avoid the online diabetes information encountered, users will adopt avoidance strategies, such as avoiding information sources, controlling attention, delaying access, forgetting information, and denying information, which is manifested as general avoidance and strong avoidance, and has positive, negative, or no effect on users. The 14 influencing factors of avoidance behavior obtained were divided into four clusters. User-related factors include demographic characteristics, health-behavior perception, perceived threat, perceived control, and information sufficiency; information-related factors include information quality, information overload, and information dissemination; environment-related factors include context type, behavior place, time pressure, and social factors, and emotion-related factors include the pre-encountering and post-encountering emotional states. These findings can guide the intervention of information avoidance behavior.