NCT04256551

Effects of a Novel Machine Learning Mobile App on Diet Adherence in Individuals Following the Low Fodmap Diet

Effects of a Novel Machine Learning Mobile App on Diet Adherence in Individuals Following the Low Fodmap Diet: A Randomized Controlled Trial

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 58 (actual)
• Sponsor: Arizona State University · Academic / Other
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Not accepted

Summary

A high fermented, oligio-, di-, monosaccharide, and polyols (FODMAP) diet has been shown to exacerbate the symptoms of irritable bowel syndrome (IBS). Previous literature has shown significant improvement in IBS symptoms after adherence to a low FODMAP diet (LFD); hence, LFD is a viable treatment method for IBS and IBS-like symptoms. However, adherence to the LFD has proven to be difficult with participants stating that information provided by medical practitioners is generalized and nonspecific requiring them to search for supplementary information to fit their individual needs. Notably, studies that have used a combination of online and in-person methods for treatment have shown improved adherence to the LFD. The purpose of this study is to determine whether a novel machine learning dietary mobile application (ML-App) will improve adherence to the LFD compared to a standard online dietary intervention in populations with IBS or IBS-like symptoms over a 4 week period.

Detailed description

Subjects will be residents of California or Arizona and recruited to the study via response to the study recruitment questionnaire advertised through online flyers, social media platforms (i.e., facebook and instagram), list serves, and recruitment services across all Arizona State University (ASU) campuses. This 6-week randomized controlled experimental study consists of a 4-week intervention period that immediately follows a 2-week baseline symptom monitoring period. The trial is conducted completely online. Data analyses will begin immediately once the trial is initiated and is expected to occur for up to one year after study completion. Following a 2-week monitoring period, participants will be randomized (via a number draw randomization method) into one of three groups: Machine Learning (ML) App + Registered Dietitian (RD) facilitator (ML-RD), ML mobile application (ML-App), or Standard Dietary Education (CON). The ML-RD group will be provided access to the Heali mobile application as well as a personal RD to provide nutrition support and answer any questions through a real-time messaging system within the mobile app. The ML-APP group receives access to the Heali mobile dietary application only. All groups will receive a link to resources regarding the LFD including an educational guide to the implementation of the elimination and reintroduction phases of the diet, a suitable/unsuitable food guide, 19 substitutes for unsuitable foods, a guide of example meals (i.e., breakfast-6 recipes, lunch-8 recipes, dinner-12 recipes, and snacks/beverages-13 recipes), and tips for reading labels and eating a balanced diet while following the LFD. The website is located at http://www.myginutrition.com/news.html and operated by the University of Michigan Health System.

Conditions

• IBS - Irritable Bowel Syndrome

Interventions

Type	Name	Description
OTHER	Heali mobile application + Registered Dietitian	The Heali mobile application is a dietary resource validated by RD's which uses AI and ML to scan menus and barcodes to provide individuals with information regarding nutritive content and applicability to one's diet using an overall food score and traffic light system. Users have the ability to choose a number of therapeutic diets including LFD, SCD, GERD, and Lectin Free to name a few, but for this study, the app will be isolated to only the LFD. RDs employed by Heali provide real-time messaging to users. For this study, participants will be given access via cell phone login and password (names will not be used). Participant usage information will be de-identified and automatically sent to excel for study authors to perform statistical analysis.
OTHER	Heali mobile application	The Heali mobile application is a dietary resource validated by RD's which uses AI and ML to scan menus and barcodes to provide individuals with information regarding nutritive content and applicability to one's diet using an overall food score and traffic light system. Users have the ability to choose a number of therapeutic diets including LFD, SCD, GERD, and Lectin Free to name a few, but for this study, the app will be isolated to only the LFD. For this study, participants will be given access via cell phone login and password (names will not be used). Participant usage information will be de-identified and automatically sent to excel for study authors to perform statistical analysis.
OTHER	Standard Dietary Education	An educational guide to the implementation of the elimination and reintroduction phases of the diet, a suitable/unsuitable food guide, 19 substitutes for unsuitable foods, a guide of example meals (i.e., breakfast-6 recipes, lunch-8 recipes, dinner-12 recipes, and snacks/beverages-13 recipes), and tips for reading labels and eating a balanced diet while following the LFD. The website is located at http://www.myginutrition.com/news.html and operated by the University of Michigan Health System.

Timeline

• Start date: 2020-01-23
• Primary completion: 2020-06-01
• Completion: 2020-06-01
• First posted: 2020-02-05
• Last updated: 2020-07-08

Locations

1 site across 1 country: United States