198. The consumption behavior of patients with mental disorders IN the environment of online marketing

Abstract Background With the rapid development of e-commerce and social media, online marketing has been deeply integrated into the daily consumption decision-making process of individuals. Compared to general consumers, individuals with mental disorders exhibit certain functional limitations in emotional regulation, impulse control, and risk assessment, making them more susceptible to the high-frequency information stimulation and emotional induction prevalent in online marketing environments. Existing research primarily focuses on the psychological mechanisms of online marketing effects on the general population, while studies addressing the consumption behavior characteristics and influencing factors of this special group remain relatively limited. Based on this, the present study aims to explore the consumption behavior characteristics and influencing factors of individuals with mental disorders in online marketing environments, providing a scientific basis for improving online consumption protection mechanisms and related mental health interventions for special populations. Methods This study employed a cross-sectional survey design, selecting 180 patients with mental disorders from a follow-up management program at a mental health medical institution in a certain city. The participants ranged in age from 20 to 55 years, all possessed basic internet usage skills, and were in a stable phase of their condition. Structured questionnaires were used to collect demographic information, internet usage habits, and consumption behavior characteristics. The primary measurement tools included the Online Marketing Susceptibility Scale (OMSS), the Impulsiveness Scale (Barratt Impulsiveness Scale, BIS-11), and a consumption behavior questionnaire. The relationship between online marketing factors and consumption behavior was analyzed using independent samples t-test, Pearson correlation analysis, and multiple linear regression analysis. The statistical significance level was set at p