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

NCT07458997 | Not Yet Recruiting DMC

• 1 other identifier: HE-RD/2025/2.34
• Study Type: interventional
• Target: 100
• Locations: 1 country
• Sites: 1

Brief 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

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

Keywords

AI chatbot; prenatal nutrition; gestational diabetes; pre-eclampsia; feasibility; usability; technology acceptance; mixed methods

Outcome Measures

Primary Outcomes (1)

• System Usability Scale (SUS)

  Usability will be assessed using the System Usability Scale (SUS), a 10-item questionnaire with five-point Likert responses. SUS yields a total score ranging from 0 to 100, with higher scores indicating better perceived usability. Scores will be compared between groups at 12 weeks.

  12weeks

Secondary Outcomes (5)

• Mean Score on the Technology Acceptance Model (TAM) Questionnaire

  12 weeks

• Proportion of Participants Achieving Adequate Engagement Adherence

  12 weeks

• Mean Number of Platform Logins per Week

  12 weeks

• Mean Number of Queries Submitted per Participant

  12 weeks

• Proportion of Chatbot Responses Rated as Accurate by Clinical Expert Panel

  12 weeks

Study Arms (2)

The intervention group

EXPERIMENTAL

The intervention group will access the the nutrition AI chatbot.

Behavioral: a culturally tailored nutrition AI chatbot for pregnant women

The control group

NO INTERVENTION

The control group will receive routine care along with access to a standardized WeChat information service. To ensure a fair comparison, the WeChat service for the control group will be operated by a trained research assistant using a pre-defined script and protocol. The assistant will respond to enquiries during two pre-scheduled windows per day (e.g., 10:00-12:00 and 14:00-16:00) by providing information directly quoted or paraphrased from the official nutritional leaflets.

Interventions

a culturally tailored nutrition AI chatbot for pregnant women BEHAVIORAL

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

The intervention group

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Pregnant women aged 18 years or older
• Able to provide informed consent in the study language
• Own a smartphone with internet access and the WeChat application

You may not qualify if:

• Current enrollment in other nutrition intervention studies
• Severe mental health conditions that may impair technology use or ability to provide informed consent

Sponsors & Collaborators

• Hong Kong Metropolitan University: lead

Study Sites (1)

Hong Kong Metropolitan University

Hong Kong, Hong Kong

Location

Related Links

• Caropreso, L., de Azevedo Cardoso, T., Eltayebani, M., \& Frey, B. N. (2020). Preeclampsia as a risk factor for postpartum depression and psychosis: a systematic review and meta-analysis. Archives of Women's Mental Health, 23(4), 493-505.
• Charlton, M. (2016). The evolving management of gestational diabetes. The Hong Kong Practitioner, 38(2).
• Feghali, M. N., Abebe, K. Z., Comer, D. M., Caritis, S., Catov, J. M., \& Scifres, C. M. (2018). Pregnancy outcomes in women with an early diagnosis of gestational diabetes mellitus. Diabetes Research and Clinical Practice, 138, 177-186.
• Hyzy, M., Bond, R., Mulvenna, M., Bai, L., Dix, A., Leigh, S., \& Hunt, S. (2022). System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis. JMIR MHealth and UHealth, 10(8).

MeSH Terms

Conditions

Diabetes, Gestational; Pre-Eclampsia

Condition Hierarchy (Ancestors)

Pregnancy Complications; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Hypertension, Pregnancy-Induced

Study Officials

• Bronya Luk, DHSc

  School of Nursing and Health Sciences, Hong Kong Metropolitan University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Bronya Luk, DHSc

CONTACT

+852 39708758; bluk@hkmu.edu.hk

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor

Model Details: A quasi-experimental design will be employed with two groups of 50 pregnant women. The intervention group will access the AI chatbot in addition to routine care, while the control group will receive routine care along with access to a standardized WeChat information service.

Study Record Dates

• First Submitted: February 24, 2026
• First Posted: March 9, 2026
• Study Start: June 1, 2026
• Primary Completion (Estimated): January 31, 2027
• Study Completion (Estimated): January 31, 2027
• Last Updated: March 9, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

HK (1)