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

NCT07458997 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100

Last updated 2026-03-09

No results posted yet for this study

Summary

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.

Conditions

  • Diabetes, Gestational
  • Pre-eclampsia
  • AI Chatbot for Prenatal Nutrition Guidance

Interventions

BEHAVIORAL

a culturally tailored nutrition AI chatbot for pregnant women

A culturally tailored nutrition AI chatbot for pregnant women , and the AI chatbot support will be available 24/7

Sponsors & Collaborators

  • Hong Kong Metropolitan University

    lead OTHER

Principal Investigators

  • Bronya Luk, DHSc · School of Nursing and Health Sciences, Hong Kong Metropolitan University

Study Design

Allocation
NON_RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-01-31
Completion
2027-01-31

Countries

  • Hong Kong

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07458997 on ClinicalTrials.gov