Usability Evaluation of Gen AI-based Nutrition Chatbot for Pregnant Women

Brief summary (registry, in English)

Background: Pregnancy imposes significant physical demands, with complications like gestational diabetes (GDM) and pre-eclampsia posing serious risks. Nutrition is crucial for mitigation, but accessing reliable guidance remains challenging. This study evaluates the feasibility of an AI chatbot providing nutritional guidance for managing these conditions. Methods: In a quasi-experimental design, 100 pregnant women will self-select into either the intervention group (n=50, using an AI chatbot) or control group (n=50, receiving standard care). The primary outcome is usability measured by the System Usability Scale (SUS) at 12 weeks, with an expected mean difference of ≥13 points. Secondary outcomes include technology acceptance (Technology Acceptance Model), user engagement, information accuracy, and changes in dietary knowledge/behaviors. Quantitative data will be analyzed using intention-to-treat and t-tests. Semi-structured interviews with 20 participants will explore user experiences through thematic analysis. Expected Results: The AI chatbot is anticipated to demonstrate superior usability and high user acceptance (TAM \>5.0/7), with improvements in dietary knowledge and behavior. Qualitative findings will provide insights into benefits, barriers, and engagement factors. Conclusion: This study will establish an evidence base on AI chatbot feasibility and acceptance for prenatal nutrition, informing tool optimization and future large-scale trials.

What you commit to

• Study type: Interventional
• Planned participants: 100
• From 1 Dec 2026 to the primary completion date, 31 Aug 2027
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

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Who cannot take part

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Who the study is looking for

Age in the registry: 18 years to - · Sex: Female · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

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