Clinical trial · Interventional
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
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Adolescent and Young Adult Cancer Survivors | — | UNRESOLVED | — |
| Chatbot | — | UNRESOLVED | — |
| Large Language Model | — | UNRESOLVED | — |
| Reproductive Health | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Chatbot | Other | — | UNRESOLVED |
| Electronic brochure | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- Chatbot
- interventionNames
- Other: Chatbot
- type
- ACTIVE_COMPARATOR
- label
- Electronic brochure
- interventionNames
- Other: Electronic brochure
Primary outcomes (3)
- measure
- Total interaction time
- timeFrame
- At 4 weeks, 8 weeks
- description
- The cumulative time spent interacting with the chatbot or reading the electronic brochure during the study period.
- measure
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 15 Years
- Maximum age
- 39 Years
Show eligibility criteria text
Inclusion Criteria: (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. Exclusion Criteria: (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.
References
Publications (0)
Data not yet available