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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.
Hence, 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.
Before 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.
To 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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Personalised Feedback | Experimental | Participants allocated to the "Personalised Feedback" condition will receive personalised dietary feedback such as the provision of personalised advice or recipes |
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| Control | Placebo Comparator | Participants allocated to the "Control" arm will only use the application to log dietary intake and will receive no feedback or personalised advice. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Personalised Feedback | Behavioral | Personalised dietary feedback, such as the provision of personalised advice or recipes |
|
| Measure | Description | Time Frame |
|---|---|---|
| Plant Food Intake | Daily consumption of plant foods measured in grams per day and servings per day | Change from baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Attitudes, Habits, and Knowledge | Attitudes, habits, and knowledge regarding plant food cooking and intake measured via questionnaires (Health and Taste Attitude Scales, Roinine et al., 2001) | Change from baseline |
| Mood |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Univeristy of Bath | Recruiting | Bath | Somerset | BA2 7AY | United Kingdom |
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| Control | Behavioral | Will only use the application to log meal and will receive no feedback or advice. |
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Negative and positive mood, vitality, flourishing and flourishing behaviours measured via questionnaires (Connor et al., 2017)
| Change from baseline |
| Stress | Perceived stress measured via the Perceived Stress Scale questionnaire | Change from baseline |
| Sleep | 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 | Change from baseline |
| Interstitial Glucose Concentration | Interstitial glucose concentration measured every minute using a continuous glucose monitor | Change from baseline |
| Salivary Cortisol | Salivary cortisol will be assessed upon waking using a biosynthetic swab in the mechanistic subset of participants | Change from baseline |
| Blood Lipids | 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 | Change from baseline |
| Plasma Glucose | 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 | Change from baseline |
| Plasma Uric Acid | 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 | Change from baseline |
| Plasma Insulin | 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 | Change from baseline |
| Serum Carotenoids | Serum carotenoids in the mechanistic subset will be quantified using high-performance liquid chromatography. Samples will be collected following an overnight fast | Change from baseline |
| Plasma Cytokines | Plasma cytokines (adiponectin, IL-6, IL-10) in the mechanistic subset will be ascertained via ELISA. Samples will be collected following an overnight fast | Change from baseline |
| Immune Cell Activation | Immune cell activation in the mechanistic subset will be assessed using whole blood stimulation. Samples will be collected following an overnight fast | Change from baseline |
| Plasm C-reactive Protein | Plasma C-reactive Protein in the mechanistic subset will be quantified using ELISA. Samples will be collected following an overnight fast | Change from baseline |
| Plasma Ferritin | Plasma ferritin in the mechanistic subset will be quantified via ELISA. Samples will be collected following an overnight fast | Change from baseline |
| Attitudes, Habits, and Knowledge | Attitudes, habits, and knowledge regarding plant food cooking and intake measured via questionnaires (Food Neophobia Scale, Pliner & Hobden, 1992) | Change from baseline |