Ignite Creation Date:
2026-03-26 @ 3:15 PM
Ignite Modification Date:
2026-03-31 @ 12:27 AM
Study NCT ID:
NCT07478068
Status:
RECRUITING
Last Update Posted:
2026-03-17
First Post:
2026-03-04
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Can Personalised Digital Feedback Help Increase Plant Food Intake?
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 315}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-05-14', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-03', 'completionDateStruct': {'date': '2026-03-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-03-13', 'studyFirstSubmitDate': '2026-03-04', 'studyFirstSubmitQcDate': '2026-03-13', 'lastUpdatePostDateStruct': {'date': '2026-03-17', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-03-17', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-03-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Plant Food Intake', 'timeFrame': 'Change from baseline', 'description': 'Daily consumption of plant foods measured in grams per day and servings per day'}], 'secondaryOutcomes': [{'measure': 'Attitudes, Habits, and Knowledge', 'timeFrame': 'Change from baseline', 'description': 'Attitudes, habits, and knowledge regarding plant food cooking and intake measured via questionnaires (Health and Taste Attitude Scales, Roinine et al., 2001)'}, {'measure': 'Mood', 'timeFrame': 'Change from baseline', 'description': 'Negative and positive mood, vitality, flourishing and flourishing behaviours measured via questionnaires (Connor et al., 2017)'}, {'measure': 'Stress', 'timeFrame': 'Change from baseline', 'description': 'Perceived stress measured via the Perceived Stress Scale questionnaire'}, {'measure': 'Sleep', 'timeFrame': 'Change from baseline', 'description': 'Sleep quality measured via Pittsburgh Sleep Quality Index. Sleep onset, wake after sleep onset, morning wake time, and total sleep time derived from smartwatch data'}, {'measure': 'Interstitial Glucose Concentration', 'timeFrame': 'Change from baseline', 'description': 'Interstitial glucose concentration measured every minute using a continuous glucose monitor'}, {'measure': 'Salivary Cortisol', 'timeFrame': 'Change from baseline', 'description': 'Salivary cortisol will be assessed upon waking using a biosynthetic swab in the mechanistic subset of participants'}, {'measure': 'Blood Lipids', 'timeFrame': 'Change from baseline', 'description': 'Blood lipids in the mechanistic subset will be analysed using an automated analyser (Daytona; Randox Lab, Crumlin, UK). Samples will be obtained following an overnight fast'}, {'measure': 'Plasma Glucose', 'timeFrame': 'Change from baseline', 'description': 'Plasma glucose in the mechanistic subset will be analysed using an automated analyser (Daytona; Randox Lab, Crumlin, UK). Samples will be obtained following an overnight fast'}, {'measure': 'Plasma Uric Acid', 'timeFrame': 'Change from baseline', 'description': 'Plasma uric acid in the mechanistic subset will be analysed using an automated analyser (Daytona; Randox Lab, Crumlin, UK). Samples will be obtained following an overnight fast'}, {'measure': 'Plasma Insulin', 'timeFrame': 'Change from baseline', 'description': 'Plasma insulin in the mechanistic subset will be ascertained using commercially available enzyme-linked immunosorbent assays (ELISA). Samples will be obtained following an overnight fast'}, {'measure': 'Serum Carotenoids', 'timeFrame': 'Change from baseline', 'description': 'Serum carotenoids in the mechanistic subset will be quantified using high-performance liquid chromatography. Samples will be collected following an overnight fast'}, {'measure': 'Plasma Cytokines', 'timeFrame': 'Change from baseline', 'description': 'Plasma cytokines (adiponectin, IL-6, IL-10) in the mechanistic subset will be ascertained via ELISA. Samples will be collected following an overnight fast'}, {'measure': 'Immune Cell Activation', 'timeFrame': 'Change from baseline', 'description': 'Immune cell activation in the mechanistic subset will be assessed using whole blood stimulation. Samples will be collected following an overnight fast'}, {'measure': 'Plasm C-reactive Protein', 'timeFrame': 'Change from baseline', 'description': 'Plasma C-reactive Protein in the mechanistic subset will be quantified using ELISA. Samples will be collected following an overnight fast'}, {'measure': 'Plasma Ferritin', 'timeFrame': 'Change from baseline', 'description': 'Plasma ferritin in the mechanistic subset will be quantified via ELISA. Samples will be collected following an overnight fast'}, {'measure': 'Attitudes, Habits, and Knowledge', 'timeFrame': 'Change from baseline', 'description': 'Attitudes, habits, and knowledge regarding plant food cooking and intake measured via questionnaires (Food Neophobia Scale, Pliner \\& Hobden, 1992)'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Plant Food Intake']}, 'descriptionModule': {'briefSummary': 'Inadequate plant food intake is a leading modifiable risk factor for non-communicable disease. However, on average, 88% of individuals do not consume adequate amounts of vegetables. Using digital technology may help improve health behaviours , with this potentially providing an accessible route to increasing plant food intake. However, uptake and engagement with applications designed to influence health behaviours is generally poor , and few studies have examined the main factors supporting user engagement and retention. Personalised dietary feedback, such as the provision of personalised advice or recipes, has the potential to enhance this process. However, whether nutritional interventions utilising personalised dietary feedback support user interaction, engagement, and retention remains to be studied.\n\nHence, the proposed project is a proof-of-concept study aiming to assess the effectiveness of using an application with personalised dietary feedback to support increased healthy plant food intake. 315 healthy males and females, between the ages of 18- and 45-years who self-report less than 50% of the recommended intake of vegetable consumption will participate in the study.\n\nBefore the intervention, participants will receive web-based instruction on the use of the smartphone application. Subsequently, participants will log all meals for two-weeks using the application to generate a baseline plant food consumption profile. In the baseline period, participants will wear a continuous glucose monitor. This will inform their individualised goals and possible feedback for the intervention period. The intervention will be 4-weeks in duration, consisting of the use of a personalised dietary program application, which will provide both recipes and feedback. Those randomised to the control will only have access to the meal logging feature. Throughout this period, participants will wear a smartwatch to track sleep metrics such as sleep onset and duration. Following the four-week intervention period, participants will be able to continue using the app for a six-week period, during which engagement with the application over time will be ascertained via telemetry. At the end of the follow-up, participants will receive an exit questionnaire to provide insight on their experience with the application, attitudes, habits and knowledge regarding consumption of plant foods, and self-perceived impact on health and dietary habits.\n\nTo provide mechanistic insight, a subset of participants (n = 50) will visit the laboratory at the University of Bath on two occasions (approximately 45 minutes each) - baseline and post-intervention. During laboratory visits, participants will provide blood pressure and body weight measurements, as well as saliva and venous blood samples. Saliva samples will be assessed for salivary cortisol, and blood samples will be assessed for the following: plasma glucose \\& insulin; plasma uric acid; plasma ascorbic acid; plasma tocopherols; serum carotenoids; plasma cytokines; plasma CRP and ferritin; F2-Isoprostanes; immune cell inflammatory capacity; HbA1c.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '45 Years', 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Healthy males and females, age at start of the study ≥ 18 and ≤ 45 years;\n* Non-rejectors of Knorr (due to the recipes in the PDP application);\n* Currently cooking or intending to cook (\\*themselves or partner) at least one main meal at home for at least five days a week;\n* Indicated desire to eat more vegetables;\n* In possession of an Android or iOS-based smartphone;\n* Willing to use an app to receive information and log all meals daily;\n* Currently using or willing to use a smartwatch;\n* Able to provide informed consent.\n\nExclusion Criteria:\n\n* High reported baseline veg intake (participants need to self-report less than 50% of the UK rec / self-reported intake above the UK adult average (206 g/2.6 servings));\n* Reported participation in another nutritional or biomedical trial within 1 month before the screening or during the study;\n* Planned frequent travel (\\>2/month) and travel to countries with time zone \\>GMT +04:00 during the study period;\n* Habitual consumption of \\>14 units (female participants) and \\>21 units (male participants) alcoholic drinks in a typical week;\n* Reported start or change in use of any nicotine containing products directly preceding the study or during the study itself;\n* If female, is pregnant (or has been pregnant during the last \\<3 months) or will be planning pregnancy during the study period;\n* If female, is lactating or has been lactating in the 6 weeks before screening and/or during the study period;\n* Reported dietary habits: medically prescribed diet, slimming diet, any condition or self-prescribed diet that restricts consumption of vegetables, not used to eating at least 3 meals a day;\n* Reported body mass loss/gain (\\>5%) in the last 3 months before the study. Self-reported history of major depressive disorders and/or current use antidepressive/antianxiety medication;\n* Clinically diagnosed sleep disorders and/or use prescribed sleep medication. Taking medication (including traditional medicines and or dietary supplements) which may pose undue personal risk or introduce bias into study measurements, as judged by the PI;\n* An allergy to adhesives, which would prevent proper attachment of the CGM;\n* Being an employee of any company developing personalised diet applications, including Salus Optima or Unilever.'}, 'identificationModule': {'nctId': 'NCT07478068', 'acronym': 'D4M', 'briefTitle': 'Can Personalised Digital Feedback Help Increase Plant Food Intake?', 'organization': {'class': 'OTHER', 'fullName': 'University of Bath'}, 'officialTitle': 'Supporting Increased Plant Food Intake Using Personalised Digital Feedback', 'orgStudyIdInfo': {'id': '8028-11785'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Personalised Feedback', 'description': 'Participants allocated to the "Personalised Feedback" condition will receive personalised dietary feedback such as the provision of personalised advice or recipes', 'interventionNames': ['Behavioral: Personalised Feedback']}, {'type': 'PLACEBO_COMPARATOR', 'label': 'Control', 'description': 'Participants allocated to the "Control" arm will only use the application to log dietary intake and will receive no feedback or personalised advice.', 'interventionNames': ['Behavioral: Control']}], 'interventions': [{'name': 'Personalised Feedback', 'type': 'BEHAVIORAL', 'description': 'Personalised dietary feedback, such as the provision of personalised advice or recipes', 'armGroupLabels': ['Personalised Feedback']}, {'name': 'Control', 'type': 'BEHAVIORAL', 'description': 'Will only use the application to log meal and will receive no feedback or advice.', 'armGroupLabels': ['Control']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'BA2 7AY', 'city': 'Bath', 'state': 'Somerset', 'status': 'RECRUITING', 'country': 'United Kingdom', 'contacts': [{'name': 'Max Davis', 'role': 'CONTACT', 'email': 'md959@bath.ac.uk', 'phone': '01225 388388'}], 'facility': 'Univeristy of Bath', 'geoPoint': {'lat': 51.3751, 'lon': -2.36172}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Bath', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Max Davis', 'investigatorAffiliation': 'University of Bath'}}}}