Digital Nutrition Intervention for Malnutrition

Overseen By Tianou Zhang, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: The University of Texas at San Antonio

Disqualifiers: Blind, Terminal illness, Dementia, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a digital nutrition program designed to help older adults access better nutrition through technology. It aims to improve food security and diet quality for individuals who rely on congregate meal centers but lack access to or knowledge of technology. Participants will learn to use digital tools for nutrition and social connection. Individuals aged 60 or older who face food insecurity and have limited tech access or knowledge may be well-suited for this trial. As an unphased trial, this study provides a unique opportunity to enhance nutrition and tech skills while contributing to valuable research.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this digital nutrition intervention is safe for older adults?

Research shows that digital nutrition programs are generally safe, though specific safety information remains limited. These programs are typically easy to manage because they don't involve medication or medical procedures. Instead, they focus on teaching and supporting individuals through technology.

The program aims to provide nutrition education and support using digital tools, avoiding the usual risks associated with drug treatments. Its main goal is to help older adults improve food security and diet quality by teaching them to use technology effectively. While this approach is unlikely to cause physical harm, it relies on participants' ability to access and use digital devices.

Overall, despite the lack of detailed safety information, the program's nature suggests it should be quite safe for participants. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Digital Nutrition Intervention for malnutrition because it leverages technology to deliver personalized dietary guidance. Unlike traditional approaches that often rely on generic dietary plans or in-person consultations, this intervention uses digital platforms to provide tailored nutritional advice directly to users. This method not only increases accessibility and convenience but also allows for real-time adjustments based on the user's progress and needs. By integrating technology into nutrition management, this intervention has the potential to improve adherence and outcomes in malnutrition treatment.

What evidence suggests that this digital nutrition intervention is effective for improving food security and diet quality?

Research has shown that digital tools for nutrition can help people improve their diets and feel more confident about their food choices. Studies have found that e-health technologies can encourage people to eat less fat and more fruits and vegetables. This trial will evaluate a Digital Nutrition Intervention, designed to make nutrition information and education more accessible. Cohort 1 will begin the intervention immediately after randomization, while Cohort 2 will serve as the control and start the intervention after Cohort 1 concludes. This digital method has been linked to better health outcomes, such as reducing the risk of poor nutrition and enhancing overall quality of life, which is particularly beneficial for older adults who may be less familiar with digital tools. Overall, digital interventions appear promising in improving eating habits and health. ^{2 6 7 8 9}

Who Is on the Research Team?

Sarah L Ullevig, PhD

Principal Investigator

University of Texas at San Antonio

Are You a Good Fit for This Trial?

This trial is for older adults aged 60 or above who are facing malnutrition, have a sedentary lifestyle, and feel socially isolated. Participants should lack technology like computers or smartphones, have poor internet access at home, or not know how to use these technologies. They must be able to read and write in English or Spanish and cannot have dementia, Alzheimer's disease, blindness, or any terminal illness.

Inclusion Criteria

Inadequate or no working technology device (computer, smart-phone, tablet), no or poor internet connectivity at home, or lack of knowledge and usage of technology

You do not have regular access to enough nutritious food.

60 years of age

Exclusion Criteria

You have been diagnosed with dementia or Alzheimer's disease.

Unable to read or write in English or Spanish

You have a visual impairment that limits your ability to see.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Technology Training

Participants undergo 5 weeks of technology training, including internet access and devices

5 weeks

Online sessions

Nutrition Intervention

Participants receive a 15-week culturally tailored nutrition intervention via online sessions

15 weeks

Online sessions

Follow-up

Participants are monitored for changes in diet quality, food security, physical activity, technology use, social isolation, and loneliness

6 months

What Are the Treatments Tested in This Trial?

Interventions

• Digital Nutrition Intervention
• Technology intervention

Trial Overview The study tests a digital nutrition intervention aimed at improving food security and diet quality among older adults. It will also assess the impact on their tech knowledge and usage, physical activity levels, as well as feelings of social isolation. The trial uses a stepped-wedge cluster design involving community partners for implementation.

How Is the Trial Designed?

Group I: Cohort 1 Experimental Treatment 2 Interventions

Cohort 1 will start the intervention directly after randomization.

Group II: Cohort 2 Active Control 2 Interventions

Cohort 2 will serve as the control while cohort 1 is in the intervention stage. Cohort 2 will start the intervention after cohort 1 concludes the intervention.

Who Is Running the Clinical Trial?

The University of Texas at San Antonio

Lead Sponsor

Trials

24

Recruited

7,600+

Older Adult Technology Services

Collaborator

Trials

1

Recruited

370+

City of San Antonio Department of Human Services

Collaborator

Trials

1

Recruited

370+

Agile Analytics, LLC

Collaborator

Trials

1

Recruited

370+

National Institute of Nursing Research (NINR)

Collaborator

Trials

623

Recruited

10,400,000+

Published Research Related to This Trial

Between 2005 and 2009, about 75% of studies showed that e-health technologies effectively helped reduce fat intake and increase fruit and vegetable consumption in behavioral nutrition interventions.

By 2010, interventions began to focus more on body weight management and included personalized features like self-monitoring, but there has been limited progress in using objective dietary behavior measures instead of self-reports.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Behavioral Nutrition Interventions Using e- and m-Health Communication Technologies: A Narrative Review. Olson, CM.[2019]

Digital health interventions using Computerized Decision Support (CDS) and Machine Learning (ML) have shown promise in the prevention and treatment of childhood obesity, with all identified studies reporting statistically significant outcomes.

CDS tools, particularly those utilizing Electronic Health Records and BMI alerts, can aid in self-management of obesity, while ML algorithms like decision trees and artificial neural networks are effective for predicting obesity risk, highlighting the potential for smart interventions in childhood obesity care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature. Triantafyllidis, A., Polychronidou, E., Alexiadis, A., et al.[2021]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12492931/

Digital intervention targeting nutrition and physical activity ... The increasing accessibility of digital technologies suggests the potential for improving health behaviours among young and adult populations.

2. withpower.com withpower.com/trial/digital-nutrition-intervention-for-malnutrition-2fb7d

Digital Nutrition Intervention for Malnutrition Between 2005 and 2009, about 75% of studies showed that e-health technologies effectively helped reduce fat intake and increase fruit and vegetable consumption ...

3. cancer.jmir.org cancer.jmir.org/2025/1/e67108

Digital Health Intervention to Reduce Malnutrition Among ... We also assessed patient-reported outcomes, including malnutrition risk, health-related quality of life, and weight-related measures. Methods: ...

4. sciencedirect.com sciencedirect.com/science/article/pii/S2451865424000188

A study protocol for a pilot randomized controlled trial We will collect preliminary data on outcomes that may be associated with the intervention including malnutrition, quality of life, treatment outcomes, and ...

5. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11011329/

A Conceptual Study on Characterizing the Complexity ... The primary objective of this study is to systematically categorize nutritional interventions into simple or complex, based on their resource allocation, ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12463344/

A Culturally Tailored Digital Education Intervention to ... The study aims (1) to test the impact of a digital nutrition education intervention on the primary outcomes of food security and diet quality; ( ...

7. sciencedirect.com sciencedirect.com/science/article/pii/S2405457724012932

Efficiency of a technology-assisted nutritional screening ... This study evaluates the system's efficiency in detecting and assessing patients at nutritional risk upon hospital admission.

8. bmchealthservres.biomedcentral.com bmchealthservres.biomedcentral.com/articles/10.1186/s12913-023-09227-8

Intervention-related, contextual and personal factors affecting ... Malnutrition in elderly institutionalized patients is a significant challenge associated with adverse health outcomes.

9. researchprotocols.org researchprotocols.org/2024/1/e50922

Digital Intervention (Keep-On-Keep-Up Nutrition) to ... The study will collect a range of data including anthropometry (height and weight), dietary intake (3-day food diary), physical function (grip ...