Comprehensive Summary
This study discusses how people react to chatbots and what makes them want to use them more often. The authors focused on two kinds of attraction, which were social attraction and task attraction, along with two social traits, which were perceived competence and perceived warmth. They surveyed 1,553 participants through an online questionnaire and used structural equation modeling to map how these traits connect to user behavior. The main question was how these perceptions lead to usage intention and media dependence. The study also looked at parasocial interaction, which is the feeling of a one sided relationship with the chatbot. Emotional support from chatbots was tested as another factor that might change how users respond. The results showed that stronger attraction or positive social traits made people feel more connected to the chatbot. That sense of connection increased both their intention to keep using the chatbot and their reliance on it as a media tool. Overall, emotional and social responses toward AI play a big role in shaping human chatbot interaction.
Outcomes and Implications
The findings matter for any health system using AI chatbots. If patients see a health chatbot as skilled and warm, they can build trust faster. Parasocial interaction could help patients stick to routine tasks like symptom check-ins, medication reminders, or mental health prompts. Emotional support from chatbots might also reduce stress for people dealing with chronic illness or limited social contact. At the same time, higher media dependence could lead some users to lean too heavily on automated advice instead of reaching out to clinicians. These results show the need to design supportive health chatbots while making sure medical guidance stays grounded in human oversight.