Abstract
BACKGROUND: Existing literature has examined the connection between information addiction and purchase decisions. However, this is the first study to focus on the older adult population and health context. This study specifically investigated the mediating roles of perceived illness severity and perceived online social support in this relationship. METHODS: A cross-sectional survey was conducted among 358 individuals aged 60 years and older in China. Participants' demographic characteristics were collected. Structural equation modeling was employed to assess health information addiction, perceived illness severity, perceived online social support, and health product purchase decisions. RESULTS: The prevalence of health information addiction among the study participants was 42.7%. Perceived illness severity, perceived online social support, and health information addiction were significantly and positively correlated with health product purchase decisions (r = 0.539-0.622, p < 0.001). Health information addiction directly and positively predicted health product purchase decisions with a direct effect value of 0.147. Furthermore, perceived illness severity and perceived online social support played independent and serial multiple mediating roles in the association between health information addiction and health product purchase decisions, with indirect effect values of 0.231, 0.069, and 0.063, respectively. CONCLUSION: Health information addiction drives older adults' health product purchases by heightening perceived illness severity and increasing reliance on online social support. To mitigate this effect, interventions should focus on developing senior-centric digital platforms with enhanced accessibility to reduce addictive consumption patterns, creating moderated online health communities to provide reliable social support, and implementing digital health literacy programs to temper excessive perceptions of illness severity. Such strategies would empower older adults to make healthier purchase decisions within digital health ecosystems.