Home-delivered produce with optional AI meal helper for high-risk pregnant women
Official title: Enhancing the Effectiveness of Home-delivery Based Produce Prescription Program Implementation Strategies
Run by The University of Texas Health Science Center, Houston · NCT06114199 · Data updated 2026-11-12
This program tests whether giving Medicaid-eligible, high-risk pregnant women in Harris County home-delivered produce plus an AI chat helper helps them use the food and eat healthier.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years to 44 Years |
| Sex | Women only |
| Enrollment | 200 (estimated) |
| Sponsor | The University of Texas Health Science Center, Houston Academic / other |
| Locations | 1 site (Houston, Texas) |
| Status | Recruiting |
| Started | July 26, 2024 |
| Main results expected | November 25, 2025 |
| Study ends | November 25, 2025 |
| Registry record updated | July 15, 2025 |
| Trial ID | NCT06114199 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Medicaid-eligible pregnant women within the program delivery zip codes who are ≤20 weeks pregnant, receiving care at high-risk obstetric clinics, and classified as high-risk due to age ≥35, prepregnancy overweight/obesity (BMI ≥25), or prior pregnancy hypertension or gestational diabetes.
✕Probably not a fit
Women medically advised to have bed rest, current substance users, those outside the delivery zip code, or people not enrolled in Medicaid are unlikely to be eligible or receive benefit from this program.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Harris Health System, GoldiFresh, and Brighter Bites are piloting a home-delivery based produce prescription program that provides regular fruit and vegetable baskets and nutrition education to Medicaid-eligible pregnant women at high risk of adverse birth outcomes. Participants receive the standard PPRx home deliveries and access a smartphone app, and a subset also receives an interactive AI conversational agent designed to turn provided foods into healthy meal ideas. The study will track utilization of food basket contents and measure changes in diet quality during pregnancy. Outcomes will compare utilization and diet quality between those with and without AI support to determine whether the AI increases conversion of produce into healthy meals.
Why it matters
Potential benefit: If successful, this could help high-risk pregnant women eat more fruits and vegetables, improve diet quality during pregnancy, and potentially lower risks tied to poor prenatal nutrition.
How similar studies have gone: Previous produce prescription programs have shown modest improvements in fruit and vegetable intake and diet quality, while using an AI conversational agent to convert produce into meals is a newer approach with limited prior evidence.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * receiving prenatal care at high-risk obstetric clinics * \<= 20 weeks medically-confirmed viable pregnancy * designated as high risk \[Age\>=35 years, or obese or overweight (BMI\>=25.0 at pre pregnancy self-report), or prior history of pregnancy hypertension or gestational diabetes\] * within the zip code delivery radius Exclusion Criteria: * women who were medically recommended bed rest through pregnancy * substance users
Where it's running
-
The University of Texas Health Science Center at Houston
Houston, Texas, United States Recruiting
Study contacts
- Principal investigator: Nanlini Ranjit, PhD — The University of Texas Health Science Center, Houston
- Study coordinator: Nalini Ranjit, PhD
- Email: Nalini.Ranjit@uth.tmc.edu
- Phone: (512) 391-2527
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.