RFPM + SmartIntake App Validation for Caloric Intake

(FoodPhone2 Trial)

Overseen By Corby K Martin, PhD

Age: < 65

Sex: Any

Trial Phase: Academic

Sponsor: Pennington Biomedical Research Center

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

Compensation: Varies

Number of Visits: Unknown

Duration: 3 days

29 Participants Needed

Trial Summary

What is the purpose of this trial?

The primary aim of this small study is to test the validity of the Remote Food Photography Method and an updated SmartIntake app in a sample of adolescents. The investigators will test the validity (accuracy) of the method/app at estimating energy intake in free-living conditions over approximately three days compared to doubly labeled water. This is a small study that has low statistical power, but will provide important data nonetheless and inform future 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 data supports the effectiveness of the RFPM + SmartIntake App treatment for monitoring caloric intake?

Research shows that technology-based tools, like the SmartIntake App, can help patients accurately record their food intake, which is important for improving nutrition care. Similar tools have been validated for their accuracy and usability in healthcare settings, suggesting that the RFPM + SmartIntake App could be effective for monitoring caloric intake. ^{1 2 3 4 5}

Is the RFPM + SmartIntake App safe for human use?

The research articles reviewed do not provide specific safety data for the RFPM + SmartIntake App, but they focus on the accuracy and validation of dietary assessment apps, which are generally considered safe as they involve non-invasive data collection methods. ^{5 6 7 8 9}

How does the RFPM + SmartIntake App treatment differ from other treatments for caloric intake assessment?

The RFPM + SmartIntake App treatment is unique because it combines a smartphone app with image-based dietary records to improve the accuracy of caloric intake assessment. This approach reduces the burden on users by automating dietary tracking and providing a more reliable method compared to traditional self-reported dietary recalls. ^{5 7 9 10 11}

Research Team

Corby K Martin, PhD

Principal Investigator

Pennington Biomedical Research Center

Eligibility Criteria

Adolescents aged 12-18, with parental support for participants under 18, are eligible for this study. They must be willing to use the RFPM/SmartIntake app for about three days and respond to study staff when needed. The trial is open to boys and girls of any race.

Inclusion Criteria

You are between 12 and 18 years old.

When using the RFPM/SmartIntake app, study staff may prompt participants for additional information when needed

Almost all of the participants in the study had parental support of the project, except for 18-year-olds.

Exclusion Criteria

Individuals may not qualify for this study based on other eligibility criteria not listed. The study coordinator determine this on a case-by-case basis

Timeline

Screening

Participants are screened for eligibility to participate in the trial

1 week

Treatment

Participants use the Remote Food Photography Method and SmartIntake app to measure energy intake over three days

3 days

Follow-up

Participants are monitored for accuracy of energy intake measurement after the initial data collection

1 week

Treatment Details

Interventions

• Tests of the validity of the RFPM and SmartIntake app

Trial Overview The trial tests the accuracy of the Remote Food Photography Method (RFPM) and SmartIntake app in estimating adolescents' energy intake over several days against a scientific standard called doubly labeled water.

Participant Groups

Group I: Study sample Experimental Treatment 1 Intervention

Individuals who participate in this validation study

Who Is Running the Clinical Trial?

Pennington Biomedical Research Center

Lead Sponsor

Trials

314

Recruited

183,000+

Findings from Research

A study comparing nutrient intake calculations from five popular nutrition tracking apps with a research-grade dietary analysis software (NDSR) found that the apps generally reported lower nutrient values, including protein, fat, sodium, and cholesterol.

Correlations between the apps and NDSR were strong for energy and macronutrients (0.73 to 0.96), but significant discrepancies were noted for specific nutrients, indicating that while the apps can be useful, they may underestimate actual nutrient intake.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Griffiths, C., Harnack, L., Pereira, MA.[2023]

References

1. France pubmed.ncbi.nlm.nih.gov

The My Meal Intake Tool (M-MIT): Validity of a Patient Self- Assessment for Food and Fluid Intake at a Single Meal. [2019]

2. England pubmed.ncbi.nlm.nih.gov

A tailored automated nutrition screening tool for rapid identification of risk in acute-care hospital settings. [2019]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Using Technology to Promote Patient Engagement in Nutrition Care: A Feasibility Study. [2021]

4. England pubmed.ncbi.nlm.nih.gov

Validation of an electronic food intake tool and its usability and efficacy in the healthcare setting. [2022]

5. England pubmed.ncbi.nlm.nih.gov

'My Meal Mate' (MMM): validation of the diet measures captured on a smartphone application to facilitate weight loss. [2022]

6. United States pubmed.ncbi.nlm.nih.gov

Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints. [2023]

7. United States pubmed.ncbi.nlm.nih.gov

A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps. [2023]

8. England pubmed.ncbi.nlm.nih.gov

Demographic and psychosocial correlates of measurement error and reactivity bias in a four-day image-based mobile food record among adults with overweight and obesity. [2023]

9. Switzerland pubmed.ncbi.nlm.nih.gov

Dietary Intake Reporting Accuracy of the Bridge2U Mobile Application Food Log Compared to Control Meal and Dietary Recall Methods. [2021]

10. England pubmed.ncbi.nlm.nih.gov

Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. [2023]

11. Switzerland pubmed.ncbi.nlm.nih.gov

Relative Validity and Reliability of the Remind App as an Image-Based Method to Assess Dietary Intake and Meal Timing in Young Adults. [2023]