ArticleBMC psychology2025
Effects of attractions and social attributes on peoples' usage intention and media dependence towards chatbot: The mediating role of parasocial interaction and emotional support.
Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- [Effect of network literacy on depression levels among young adults: an analysis based on China Family Panel Studies].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026Article
- A scoping review on the mental health harms of LLM-based chatbots.NPJ digital medicine · 2026Article
- Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026Article
- Loneliness and AI chatbot dependence in young adults: the mediating role of perceived social support.BMC psychology · 2026Article
- The effects of responsiveness, perceived warmth, and anthropomorphism on university students' use of conversational AI for learning support: a chain mediation analysis based on S-O-R framework.Frontiers in psychology · 2026Article
- Differential pathways linking social interaction and Loneliness among university students in the age of artificial intelligence: the mediating role of Social Capital.Frontiers in psychology · 2026Article
- The stereotypical effect of gendered nicknames on prosocial behavior in online interactions: a chain mediation model.Frontiers in psychology · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
purposeIt is important to explore the relationship between humans and chatbots to improve human-robot interaction in the era of artificial intelligence. This study aims to explore the effects of attractions and social attributes of chatbots on users' media dependency and usage intention of chatbots, as well as the role of users' para-social interaction and emotional support gained from chatbots.
methodsA total of 1,553 responses were collected based on a cross-sectional online survey. Utilizing the structural equation modeling approach, this study tested the relationships among exogenous variables (social attraction/task attraction, perceived competence/perceived warmth), endogenous variables (usage intention/media dependence), and mediating variables (para-social interaction/emotional support).
resultsThe results show that the attraction and social attributes of chatbots, represented by ChatGPT, enable users to construct para-social interaction and obtain emotional support when chatting with them. Meanwhile, para-social interaction and emotional support can link users' perceptions of chatbots to their media dependency on and usage intention of them. This study provides theoretical and methodological references for examining the human-robot interaction relationship and offers insights into exploring the human-robot emotional connection.
conclusionsThis study explores chatbots from the perspective of emotional connections, emphasizing how users' perceptions of chatbot attraction and social attributes facilitate para-social interaction and emotional support. Theoretically, it extends the application of para-social interaction theory and emotional support into the domain of human-chatbot communication, enriching the understanding of affective mechanisms in human-AI relationships. Methodologically, the study employs structural equation modeling (SEM) to test a multidimensional mediation model using large-scale survey data, examining psychological pathways linking chatbot characteristics to users' behavioral responses. These findings offer new insights for the optimization of human-computer interaction applications and the improvement of chatbot design in practice.
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