[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82271-en":3,"doc-seo-82271-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82271,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","LLMs for health Perceived benefits risks intention to use AI chatbots willingness to self-disclose across sensitive health topics","AI chatbots are increasingly used to answer health-related questions. This study tests how the discussion topic type (physical vs psychological) and topic sensitivity (low vs high) influence perceived benefits and risks, intention to use AI chatbots, and willingness to self-disclose health information. Using a Dutch representative online experiment (N=1,388), results show benefits increase intention and self-disclosure, while risks reduce them. Higher intentions emerge for low-sensitive topics, and perceptions and willingness vary with individual characteristics, linking outcomes primarily to perceived benefits and risks.","LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topics  \nGwenn Beets1*, Anniek Jansen1*, Saar Hommes1,2, Ruben D. Vromans1, Leonie Westerbeek3, Supraja Sankaran1, Julia C.M. van Weert3, Emiel J. Krahmer1,2, and Nadine Bol1  \n1 Department of Communication and Cognition, Tilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, The Netherlands  \n2 Academic Collaborative Center for Digital Health and Mental Wellbeing, Department of Communication and Cognition, Tilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, The Netherlands  \n3 Amsterdam School of Communication Research (ASCoR), Department of Communication Science, University of Amsterdam, Amsterdam, The Netherlands  \n* Authors contributed equally.  \nCorresponding author: Gwenn Beets, Department of Communication and Cognition, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, [g.beets@tilburguniversity.edu](g.beets@tilburguniversity.edu)  \nAbstract  \nAI chatbots are increasingly used for answering health-related questions. This study examines the role of topic type discussed with an AI chatbot and individual characteristics on perceived benefits and risks, intention to use an AI chatbot, and willingness to self-disclose health information. We conducted an online experiment with a 2 (topic type: physical versus psychological, between-subjects)× 2 (topic sensitivity: low versus high, within-subjects) mixed design among a Dutch representative sample (N = 1,388). Results showed that perceived benefits were positively associated with intention and willingness to self-disclose, while perceived risks were negatively associated. Moreover, participants reported higher usage intentions for low-sensitive topics compared to high-sensitive topics. Furthermore, perceptions, intention, and willingness to self-disclose varied by individual characteristics. Overall, our findings suggest that intentions to use AI chatbots and self-disclosure of health-related information are primarily related to perceived benefits and risks and to personal characteristics rather than to topic type.  \nKeywords: AI chatbots, Large Language Models, topic sensitivity, perceived benefits, perceived risks, health communication  \n1 Introduction  \nPeople often worry about their mental and physical health, and may (increasingly) seek health-related information online (Xiao et al., 2024; Yun and Bickmore, 2025) . With the recent rapid uptake of AI chatbots, chatbots based on Large Language Models (LLMs; i.e., language generation models trained on text), such as ChatGPT and DeepSeek, asking health-related questions online has begun to shift from static web searches to interactive dialogues (Xiao et al., 2024; Haensch, 2025; Yun and Bickmore, 2025) . While search engines remain the primary source for health-related information, it is shown that AI chatbots are used by 37% of the Dutch population, according to a population-based study (de León et al., 2024) . The increasing popularity of using AI chatbots for physical and psychological health-related information raises fundamental questions. Are chatbot users aware of  \nbenefits and risks? And if so, do these impact their intention to use chatbots and willingness to share personal sensitive health information with them? To what extent does this depend on the topic of discussion? In this paper, we tackle these questions using a large-scale online experiment among a representative Dutch sample.  \nResearch has identified several benefits and risks to using AI chatbots for health-related questions (e.g., Singg and Pena, 2025) . It remains unclear, however, how such perceived benefits and risks are associated with the intentions to use an AI chatbot and willingness to self-disclose personal information, and whether the topic of discussion plays a role for the general public. Research has suggested that people are more willing to accept AI chatbo","cbCaic0EU3zN1mPb","https://ap.wps.com/l/cbCaic0EU3zN1mPb","pdf",1482776,1,21,"English","en",105,"# Abstract\n# Introduction\n# Theoretical framework\n## Trade-off between perceived benefits and risks","[{\"question\":\"How do perceived benefits and perceived risks relate to intention to use AI chatbots and self-disclosure?\",\"answer\":\"Perceived benefits are positively associated with both intention to use AI chatbots and willingness to self-disclose. Perceived risks are negatively associated with these outcomes.\"},{\"question\":\"Do topic sensitivity and topic type affect usage intention?\",\"answer\":\"Usage intentions are higher for low-sensitive topics than for high-sensitive topics. The findings indicate that intentions and self-disclosure relate more to perceived benefits and risks and personal characteristics than to topic type overall.\"},{\"question\":\"What role do individual characteristics play in these outcomes?\",\"answer\":\"Perceptions, intention to use, and willingness to self-disclose vary by individual characteristics. The overall pattern suggests personal characteristics influence outcomes alongside perceived benefits and risks.\"}]",1784179301,53,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"llms-for-health-perceived-benefits-risks-intention-to-use-ai-chatbots-willingness-to-self-disclose-across-sensitive-health-topics","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/llms-for-health-perceived-benefits-risks-intention-to-use-ai-chatbots-willingness-to-self-disclose-across-sensitive-health-topics/82271/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"How do perceived benefits and perceived risks relate to intention to use AI chatbots and self-disclosure?","Question",{"text":74,"@type":75},"Perceived benefits are positively associated with both intention to use AI chatbots and willingness to self-disclose. Perceived risks are negatively associated with these outcomes.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"Do topic sensitivity and topic type affect usage intention?",{"text":79,"@type":75},"Usage intentions are higher for low-sensitive topics than for high-sensitive topics. The findings indicate that intentions and self-disclosure relate more to perceived benefits and risks and personal characteristics than to topic type overall.",{"name":81,"@type":72,"acceptedAnswer":82},"What role do individual characteristics play in these outcomes?",{"text":83,"@type":75},"Perceptions, intention to use, and willingness to self-disclose vary by individual characteristics. 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