A Mobile Application to Improve Procurement and Distribution of Healthful Foods & Beverages in Baltimore City
NCT ID: NCT05010018
Last Updated: 2026-01-14
Study Results
Outcome measurements, participant flow, baseline characteristics, and adverse events have been published for this study.
View full resultsBasic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
NA
310 participants
INTERVENTIONAL
2021-10-29
2024-06-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Cardiovascular Risk Reduction for Adults With Food Insecurity Using Structured Incentives
NCT06818669
Healthy Foods and Education to Treat Diabetes
NCT03991026
The Efficacy of Front-of-package Labelling Schemes: an Experimental Study
NCT03290118
Dietary Behavior Intervention in African Americans at Risk for Cardiovascular Disease
NCT04305431
Medically Tailored Meals for Cardiovascular Health
NCT06550297
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
The study team has worked for more than 17 years in Baltimore to develop, implement, and evaluate chronic disease prevention programs by improving the food environment in low-income communities. The investigators' preliminary formative research assessed the initial acceptability of a mobile app that will enable small urban food store owners to access a range of healthy foods from local wholesalers and producers, and facilitate affordable delivery to their stores. The study team found high acceptability for an app that would leverage the collective purchasing power of digitally-networked small food stores and introduce cost efficiencies into food delivery. For this NHLBI Clinical Trial Pilot Study (R34), the investigators propose to develop a working web-based Baltimore Urban food Distribution (BUD) app, pilot the app, and evaluate its feasibility and impact on the availability, prices and distribution of healthful foods and beverages in East Baltimore, with the following primary aims: 1) To develop and optimize a technically stable and functional digital strategy to overcome small retail food system constraints common in low-income urban food settings; 2) To pilot the BUD app with Baltimore-based producers/wholesalers and corner stores, and assess its feasibility (i.e., acceptability, operability, perceived sustainability, user satisfaction); and 3) To evaluate the impact of the BUD app on corner store stocking (availability, timeliness, quality), prices, and sales of healthy and unhealthy foods and beverages in a pilot study employing a randomized controlled trial design of 38 corner stores. Secondary aims will examine impact on consumers and a cost-benefit analysis for participating retailers and producers.
Findings will permit the investigators to: 1) produce a functional and acceptable web-based app, 2) provide preliminary data needed for power calculations for the full-scale trial, 3) generate and refine process evaluation instruments and set standards for implementation, and 4) establish protocols and demonstrate the study team's ability to recruit and retain large numbers of wholesalers, producers, corner stores and consumers. The study team will assess generalizability of the app by conducting feasibility assessments of the developed app with small store owners and suppliers in other urban settings. The findings from this R34 application are essential to support a full-scale clinical trial, which will test a multi-city deployment of the BUD app and assess its impact on obesity and diet.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
RANDOMIZED
PARALLEL
PREVENTION
NONE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Intervention
We will pilot the BUD app in 19 intervention corner stores over an 8-month period in East Baltimore. During this time, we will collect data from corner store owners, producers, whole salers, and consumers.
Web-based application connecting small food store owners and suppliers of healthier foods and beverages
The primary intervention is a web-based app that connects small food store owners in low income Baltimore with suppliers of healthier foods and beverages. To reduce costs associated with small purchasing quantities by corner stores, and high delivery charges, the BUD app uses collective purchasing and shared delivery strategies. BUD will be implemented in four stages, where each stage promotes different food/beverage items and introduces new features. The app will be bundled with a small subsidy in stages 1-2 to encourage initial use, increase familiarity with the app and reduce risk. Trainings in the use of the app will take place at the beginning of each phase. BUD will use collective purchasing at stage 2 of implementation (BuddyUp!). The BuddyLift! feature will start in stage 3, enabling small store owners to deliver BuddyUp! deals to other stores for an additional discount. Participating stores and wholesalers will receive point of purchase materials to promote BUD products.
Control
We will collect data from 19 control corner stores over the same 8-month period. They will not receive any form of intervention or delay intervention.
No interventions assigned to this group
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Web-based application connecting small food store owners and suppliers of healthier foods and beverages
The primary intervention is a web-based app that connects small food store owners in low income Baltimore with suppliers of healthier foods and beverages. To reduce costs associated with small purchasing quantities by corner stores, and high delivery charges, the BUD app uses collective purchasing and shared delivery strategies. BUD will be implemented in four stages, where each stage promotes different food/beverage items and introduces new features. The app will be bundled with a small subsidy in stages 1-2 to encourage initial use, increase familiarity with the app and reduce risk. Trainings in the use of the app will take place at the beginning of each phase. BUD will use collective purchasing at stage 2 of implementation (BuddyUp!). The BuddyLift! feature will start in stage 3, enabling small store owners to deliver BuddyUp! deals to other stores for an additional discount. Participating stores and wholesalers will receive point of purchase materials to promote BUD products.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
Store owner/manager willing to attend in-store trainings in the use of the BUD App
Store located in a low-income neighborhood considered as a Healthy Food Priority Area by the Johns Hopkins Center for a Livable Future111 in East Baltimore
Store located \>0.25 miles from a supermarket
Store classified as a small food store (\< 4 aisles, \< 2 cash registers)
Store owner/manager is English, Korean, Spanish or Mandarin-speaking for first language
Provide service to Baltimore City (e.g., for producers, this could mean participating in Baltimore City-based farmers markets)
Willing to use the BUD app, including posting and maintaining data on a minimum number of products
Willing to participate with delivery services arranged
* Regular customers of the store (purchase food items at least once a week in the store) identified by the small food store owner/manager enrolled in the study
* Adult (between 21 years old and 75 years old)
* Live/work within a 1/2 mile radius from one of the 38 small food stores participating in the study
* Live in a household of at least 2 persons (criteria intended to provide a more stable sample, to reduce loss to follow-up)
Exclusion Criteria
* Pregnant (due to changes in diet, weight and body composition)
21 Years
75 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
National Heart, Lung, and Blood Institute (NHLBI)
NIH
Johns Hopkins Bloomberg School of Public Health
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Joel Gittlesohn, PhD
Role: PRINCIPAL_INVESTIGATOR
Johns HopkinsUniversity
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Johns Hopkins University
Baltimore, Maryland, United States
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
Lewis EC, Zhu S, Oladimeji AT, Igusa T, Martin NM, Poirier L, Trujillo AJ, Reznar MM, Gittelsohn J. Design of an innovative digital application to facilitate access to healthy foods in low-income urban settings. Mhealth. 2023 Nov 3;10:2. doi: 10.21037/mhealth-23-30. eCollection 2024.
Gittelsohn J, Lewis EC, Martin NM, Zhu S, Poirier L, Van Dongen EJI, Ross A, Sundermeir SM, Labrique AB, Reznar MM, Igusa T, Trujillo AJ. The Baltimore Urban Food Distribution (BUD) App: Study Protocol to Assess the Feasibility of a Food Systems Intervention. Int J Environ Res Public Health. 2022 Jul 26;19(15):9138. doi: 10.3390/ijerph19159138.
Provided Documents
Download supplemental materials such as informed consent forms, study protocols, or participant manuals.
Document Type: Study Protocol and Statistical Analysis Plan: Study Protocol with Stat Plan
Other Identifiers
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.