There has recently been increased interest in chatbots addressing health-related needs. Chatbots are software that simulate a human conversation, through text or voice. There is substantial potential for chatbots to improve the quality of healthcare services as they can be applied in a wide range of services within this area, like symptom checking, providing medical- and health-information, as well as patient support and follow-up. However, as the development of chatbots within healthcare is still in its emergence, there is a knowledge gap as to what makes users want to use chatbots in the health domain. We need this knowledge in order for developers to be able to adjust chatbots to the user’s needs and pave way for future adoption. This thesis aims to contribute with knowledge on this area by exploring factors that affects intention to use a chatbot for health information. This was implemented as an interview-study involving 16 women in the target group of a chatbot for health information. The study used an exploratory approach, guided by general theory on technology acceptance and chatbot use. The literature suggested four factors to be of importance: usefulness, ease of use, hedonic value and trust. The interview data was analyzed using Thematic Analysis and gave insight into important aspects of each of the factors and their relation to intention to use. The findings suggest that usefulness may be of particular importance for users’ intention to use a chatbot for health information, and that it is mostly related to its ability to provide the users guidance and practical advice. The ease of use of such a chatbot seems closely related to how easily available, learnable and efficient the users perceived it. The hedonic value was strongly linked to its role as a health chatbot, suggesting the content and look of such chatbots should reflect this. Trust was in particular related to the first impressions of the chatbot, its perceived expertise, sense of respectfulness and the anonymity and perceived risk in using it. Supportiveness was identified as a fifth factor, and it was particularly the informational and emotional supportiveness such a chatbot could provide. This study contributes new knowledge regarding what affects intention to use health information chatbots. This knowledge may inform future theory building as well as development of chatbots in this domain.