[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"adolescent-and-young-adult-cancer-survivors\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:adolescent-and-young-adult-cancer-survivors":29},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":4,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":32,"lastUpdatePostDateStruct":33,"startDateStruct":36,"completionDateStruct":38,"leadSponsor":40,"locationsCount":43},"100650098","effects-of-a-large-language-model-driven-chatbot-on-reproductive-concerns-after-cancer-100650098",false,"NCT07741266","Effects of a Large Language Model-Driven Chatbot on Reproductive Concerns After Cancer","The Feasibility and Preliminary Effectiveness of a Large Language Model-Driven Chatbot in Addressing Reproductive Concerns Among Adolescent and Young Adult Cancer Survivors: A Pilot Randomized Controlled Trial","Inclusion Criteria:\n\n(1) 15-39-year-old females; (2) cancer diagnosis between ages 15-39; (3) current or prior concerns regarding fertility; (4) proficiency in Mandarin Chinese; and (5) access to a mobile device for intervention delivery.\n\nExclusion Criteria:\n\n(1) Involvement in the chatbot co-design phases; (2) inability to provide informed consent; (3) significant sensory, cognitive, or psychological impairments precluding meaningful participation; and (4) acute illness at the time of recruitment.","FEMALE","15 Years","39 Years",{"count":20,"type":21},60,"ESTIMATED","INTERVENTIONAL",[24],"NA","Reproductive health has emerged as a critical yet overlooked concern among Adolescent and Young Adult (AYA) cancer survivors, given their compromised potential for biological parenthood in prime childbearing years. Large language models (LLMs) offer a promising solution to bridge onco-fertility service gaps by integrating evidence-based knowledge and therapeutic frameworks. This pilot randomized controlled trial aims to assess the feasibility and preliminary effectiveness of an LLM-driven chatbot versus electronic brochure in addressing reproductive concerns among AYA cancer survivors.",[27,28,29,30],"Chatbot","Large Language Model","Adolescent and Young Adult Cancer Survivors","Reproductive Health","NOT_YET_RECRUITING","2026-07-28",{"date":34,"type":35},"2026-08-03","ACTUAL",{"date":37,"type":21},"2026-09-01",{"date":39,"type":21},"2027-06-30",{"name":41,"class":42},"The Hong Kong Polytechnic University","OTHER",2]