Ignite Creation Date:
2025-12-24 @ 11:57 PM
Ignite Modification Date:
2025-12-25 @ 9:54 PM
Study NCT ID:
NCT04256551
Status:
COMPLETED
Last Update Posted:
2020-07-08
First Post:
2020-02-01
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Effects of a Novel Machine Learning Mobile App on Diet Adherence in Individuals Following the Low Fodmap Diet
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D043183', 'term': 'Irritable Bowel Syndrome'}], 'ancestors': [{'id': 'D003109', 'term': 'Colonic Diseases, Functional'}, {'id': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Randomized Controlled Trial'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 58}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-01-23', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-07', 'completionDateStruct': {'date': '2020-06-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-07-07', 'studyFirstSubmitDate': '2020-02-01', 'studyFirstSubmitQcDate': '2020-02-03', 'lastUpdatePostDateStruct': {'date': '2020-07-08', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-02-05', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-06-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Rome IV', 'timeFrame': 'Change from Baseline at week 6', 'description': 'A diagnostic tool to determine severity of gastrointestinal dysfunction and the most updated method to diagnose IBS. Participants will complete the self-administered online survey. Based on the results of the survey, we will identify the IBS category. \\[e.g., IBS with constipation (IBS-C), IBS with diarrhea (IBS-D), IBS mixed typed (IBS-M), or IBS unsubtyped (IBS-U)\\]'}, {'measure': 'IBS-SSS', 'timeFrame': 'Change from Baseline at week 6', 'description': 'A symptom severity screener validated by Francis et al. The IBS-SSS is a short survey filled out by participants which categorizes them into one of four categories based on their responses: \\>75-no symptoms, 75 to \\<175-mild IBS, 175 to \\<300-moderate IBS, and ≥300-severe IBS.23'}], 'secondaryOutcomes': [{'measure': 'Low FODMAP dietary adherence (LFDA)', 'timeFrame': 'Change from Baseline at week 6', 'description': 'short Food Frequency Questionnaire (FFQ)'}, {'measure': 'Low FODMAP dietary knowledge (LFDK)', 'timeFrame': 'Change from Baseline at week 6', 'description': "short survey composed of a series of questions to determine participants' knowledge of the LFD"}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['high fermented, oligio-, di-, monosaccharide, and polyols', 'mobile app', 'irritable bowel syndrome'], 'conditions': ['IBS - Irritable Bowel Syndrome']}, 'referencesModule': {'references': [{'pmid': '33650977', 'type': 'DERIVED', 'citation': 'Rafferty AJ, Hall R, Johnston CS. A Novel Mobile App (Heali) for Disease Treatment in Participants With Irritable Bowel Syndrome: Randomized Controlled Pilot Trial. J Med Internet Res. 2021 Mar 2;23(3):e24134. doi: 10.2196/24134.'}]}, 'descriptionModule': {'briefSummary': '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.', 'detailedDescription': '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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '65 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* IBS-SSS score ≥ 175 (moderate to severe IBS)\n* meet the Rome IV criteria for IBS of any type including those with IBS with constipation (IBS-C), IBS with diarrhea (IBS-D), IBS mixed typed (IBS-M), or IBS unsubtyped (IBS-U), and had symptoms for the past 3 months or greater\n* own an I-phone\n* have not used a dietary application or elimination diet for IBS in the past 6 months\n* must be willing to participate in the low FODMAP diet intervention over a 4-week period with a monitoring period of 2-weeks\n* agree to complete online questionnaires as frequently as once per week from study start.\n\nExclusion Criteria:\n\n* individuals with food allergies (not food intolerances)\n* smokers\n* those with history of chronic disease (other than gastrointestinal dysfunction)\n* nutrition student or professional\n* prescription medication is permitted unless the medication is to treat IBS (which includes steroids).'}, 'identificationModule': {'nctId': 'NCT04256551', 'briefTitle': 'Effects of a Novel Machine Learning Mobile App on Diet Adherence in Individuals Following the Low Fodmap Diet', 'organization': {'class': 'OTHER', 'fullName': 'Arizona State University'}, 'officialTitle': 'Effects of a Novel Machine Learning Mobile App on Diet Adherence in Individuals Following the Low Fodmap Diet: A Randomized Controlled Trial', 'orgStudyIdInfo': {'id': 'FODMAP/APP'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Machine Learning App + Registered Dietitian facilitator', 'description': '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. Group will receive a link to resources regarding the Low FODMAP diet: website is located at http://www.myginutrition.com/news.html and operated by the University of Michigan Health System', 'interventionNames': ['Other: Heali mobile application + Registered Dietitian', 'Other: Heali mobile application', 'Other: Standard Dietary Education']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Machine Learning App', 'description': 'The ML-APP group receives access to the Heali mobile dietary application. Group will receive a link to resources regarding the Low FODMAP diet: website is located at http://www.myginutrition.com/news.html and operated by the University of Michigan Health System', 'interventionNames': ['Other: Heali mobile application', 'Other: Standard Dietary Education']}, {'type': 'PLACEBO_COMPARATOR', 'label': 'Standard Dietary Education', 'description': 'Group will receive a link to resources regarding the Low FODMAP diet: website is located at http://www.myginutrition.com/news.html and operated by the University of Michigan Health System', 'interventionNames': ['Other: Standard Dietary Education']}], 'interventions': [{'name': 'Heali mobile application + Registered Dietitian', 'type': 'OTHER', 'description': "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.", 'armGroupLabels': ['Machine Learning App + Registered Dietitian facilitator']}, {'name': 'Heali mobile application', 'type': 'OTHER', 'description': "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.", 'armGroupLabels': ['Machine Learning App', 'Machine Learning App + Registered Dietitian facilitator']}, {'name': 'Standard Dietary Education', 'type': 'OTHER', 'description': '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.', 'armGroupLabels': ['Machine Learning App', 'Machine Learning App + Registered Dietitian facilitator', 'Standard Dietary Education']}]}, 'contactsLocationsModule': {'locations': [{'zip': '85004', 'city': 'Phoenix', 'state': 'Arizona', 'country': 'United States', 'facility': 'Arizona State University', 'geoPoint': {'lat': 33.44838, 'lon': -112.07404}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Arizona State University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor and Associate Dean', 'investigatorFullName': 'Carol Johnston', 'investigatorAffiliation': 'Arizona State University'}}}}