The Effect of an mHealth Intervention on Physical Activity and Nutrition: the FutureMe Trial

The Effect of a Future-Self Avatar mHealth Intervention on Physical Activity and Nutrition: the FutureMe Randomized Controlled Trial

This study is a randomized controlled trial (RCT) which investigates the effect of a Future-Self Avatar intervention (FutureMe App) on physical activity (PA) and nutrition. The Health Action Process Approach (HAPA) and principles from consumer behavior theory were used to guide the development of the intervention.

The study investigates the impact of avatar-based interventions on PA and food purchasing behavior and aims to understand if avatars can help increase the stand-alone effectiveness of mHealth interventions.

Study Overview

• Status: Completed
• Conditions: Healthy
• Intervention / Treatment: Behavioral: FutureMe App; Behavioral: Conventional TrackingApp

Detailed Description

Consumer behavior is a key determinant for chronic disease risk. Mobile health (mHealth) technologies are promising in addressing the rise in risky lifestyle behaviors, as they can be leveraged in large population samples without high human resource or monetary requirements. However, research shows that mHealth technologies are less effective when used stand-alone, meaning without intervention components that require human to human interaction. Leveraging virtual reality in mHealth applications could help increase their stand-alone effectiveness.

Building on behavioral biases, and the health-action-process approach (HAPA), this trial investigates the use of a future-self avatar smartphone intervention (FutureMe app) on consumers' physical activity and food purchasing behavior. A 12-week field experiment aims to show that avatar-based health applications can support behavior change towards more active lifestyles and healthier food choices.

The FutureMe trial has the following objectives:

1. To understand if avatar-based applications are more effective in promoting physical activity and improving food purchasing behavior compared to conventional tracking applications.
2. To understand if providing individualized shopping tips promotes self-efficacy.
3. To understand if providing consequential health behavior feedback increases behavior- related control over future health (outcome expectancy).
4. To understand if avatar-based applications increase intrinsic motivation compared to conventional health-tracking applications.
5. To understand if self-efficacy, outcome expectancy, user engagement or specific types of motivation moderate the effect on PA and foor purchasing.

The study participants recruitment process is supported by a large Swiss health insurance company. The insurer only provides access to potential study participants and is not involved in the design or execution of the study. The insurer has no access to participant study data. Participants are randomized into two groups and either receive the innovative FutureMe intervention or a control intervention consisting of a more conventional nutrition and physical activity tracking app (numeric feedback). Participants will download the respective apps to their personal mobile phone.

Step counts and food purchasing data is collected continuously throughout the trial. The respective psychological constructs (see outcome overview) are collected at baseline and after 12 weeks (end of intervention) via an online questionnaire.

The results of this study enable the evidence-based development of scalable interventions for sustainable physical activity and nutrition behavior change and advance the understanding of the psychological processes behind health behavior change.

• Study Type: Interventional
• Enrollment (Actual): 95
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Switzerland
  • Saint Gallen, Switzerland, 9000
    • University of St. Gallen

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Living in Switzerland
• German speaking
• Participating in at least one grocery loyalty program (Migros Cumulus and/or Coop SuperCard)
• Apple or Android smartphone
• Healthy (self-declaration)

Exclusion Criteria

• <18 years
• Increasing PA or adjusting nutrition creates health risk (e.g. diabetic)
• Not living in Switzerland
• Not German speaking
• Not using a grocery loyalty card

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Quadruple

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: FutureMe; Participants use the FutureMe app for 12 weeks. The app has the following functionality: Opportunity to personalize one's avatar; Tracking of PA (steps) and nutrition (purchasing behavior at food retailers); Feedback on health behaviors represented through a Future-self avatar (consequential and visual feedback); Individualized shopping tipps	Behavioral: FutureMe App; The FutureMe app provides visual and consequential feedback through a future-self avatar, meaning that the avatar changes its body shape and some additional characteristics based on the participants' activity and food purchasing behaviors. The app tracks participants physical activity behavior (steps) by means of their smartphone (integration to GoogleFit and AppleHealth) and motivates them to increase their step counts. The app also connects to participants' grocery loyalty cards to evaluate their food shopping behavior leveraging the Nutri-score concept. The app motivates participants to improve their food purchases through concrete shopping tips provided in-app.
Active Comparator: Control; Participants use the a control app for 12 weeks. The control app has the following functionality: Tracking of PA (steps) and nutrition (purchasing behavior at food retailers); Feedback on health behaviors represented through conventional dashboards (numeric & text feedback); Individualized shopping tipps	Behavioral: Conventional TrackingApp; The Control Conventional Tracking app provides numeric and factual feedback through conventional data-dashboards. The app tracks participants physical activity behavior (steps) by means of their smartphone (integration to GoogleFit and AppleHealth) and motivates them to increase their step counts. The app also connects to participants' grocery loyalty cards to evaluate their food shopping behavior leveraging the Nutri-score concept. The app motivates participants to improve their food purchases through concrete shopping tips provided in-app.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Physical Activity	Steps will be measured daily via the GoogleFit or Apple Health application using the Smartphone's built-in accelerometer.	12 weeks
Nutri-Score	Nutri-Score calculated based on total food purchases; Minimum Value: -15 (A=Very Good), Maximum Value: 40 (E=Very Bad). Nutriscore will be measured by shopping basket, continuously over 12 weeks.	12 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Food Purchasing Behavior - Salt	Salt in grams (g) per 100g food purchases (based on loyalty card data). Salt purchases will be measured by shopping basket, continuously over 12 weeks.	12 weeks
Food Purchasing Behavior - Proteins	Proteins in grams (g) per 100g food purchases (based on loyalty card data). Protein purchases will be measured by shopping basket, continuously over 12 weeks.	Continuous measurement during study (12 weeks)
Food Purchasing Behavior - Fibers	Fibers in grams (g) per 100g food purchases (based on loyalty card data). Fiber purchases will be measured by shopping basket, continuously over 12 weeks.	Continuous measurement during study (12 weeks)
Food Purchasing Behavior - Saturated Fats	Saturated Fats in grams (g) per 100g food purchases (based on loyalty card data). Saturated fat purchases will be measured by shopping basket, continuously over 12 weeks.	Continuous measurement during study (12 weeks)
User Engagement 1	Number of app openings during 12 week intervention period. App openings will be measured daily directly via tracking mechanisms in the app.	12 weeks from beginning to end of intervention
User Engagement 2	Time spent in app measured in seconds during 12 week intervention period. Time spent in app will be measured daily directly via tracking mechanisms in the app.	12 weeks from beginning to end of intervention
Food Purchasing Behavior - Fruit & Vegetable Purchases	Fruits and Vegetables in grams (g) per 100g food purchases (based on loyalty card data). Fruit and Vegetable purchases will be measured by shopping basket, continuously over 12 weeks.	12 weeks
Food Purchasing Behavior - Sugar (excluding Fructose & Lactose)	Sugar in grams (g) per 100g food purchases (based on loyalty card data). Sugar purchases will be measured by shopping basket, continuously over 12 weeks.	12 weeks
Motivational Self-Efficacy	Motivational Self-Efficacy scale adjusted from Schwarzer et al. 2007; Minimum Value: 1 (totally disagree), Maximum Value: 7 (totally agree)	12 weeks
Recovery Self-Efficacy	Recovery Self-Efficacy scale adjusted from Schwarzer et al. 2007; Minimum Value: 1 (totally disagree), Maximum Value: 7 (totally agree)	12 weeks
Perceived behavior-related control over future health	Perceived behavior-related control scale adjusted from Renner and Schwarzer, 2005; Minimum Value: 1 (totally disagree), Maximum Value: 7 (totally agree)	12 weeks
Autonomous Motivation	Treatment Self-Regulation Questionnaire (TSRQ); Minimum Value: 1 (totally disagree), Maximum Value: 7 (totally agree)	12 weeks
Controlled Motivation	Treatment Self-Regulation Questionnaire (TSRQ); Minimum Value: 1 (totally disagree), Maximum Value: 7 (totally agree)	12 weeks

Collaborators and Investigators

• Sponsor: Annette Mönninghoff
• Collaborators: ETH Zurich; Helsana Zusatzversicherungen AG
• Investigators: Principal Investigator: Annette Mönninghoff, University of St. Gallen, Institute for Customer Insight

Publications and helpful links

General Publications

• Steinemann N, Grize L, Ziesemer K, Kauf P, Probst-Hensch N, Brombach C. Relative validation of a food frequency questionnaire to estimate food intake in an adult population. Food Nutr Res. 2017 Mar 29;61(1):1305193. doi: 10.1080/16546628.2017.1305193. eCollection 2017.
• Schwarzer R, Schuz B, Ziegelmann JP, Lippke S, Luszczynska A, Scholz U. Adoption and maintenance of four health behaviors: theory-guided longitudinal studies on dental flossing, seat belt use, dietary behavior, and physical activity. Ann Behav Med. 2007 Apr;33(2):156-66. doi: 10.1007/BF02879897.
• Monninghoff A, Fuchs K, Wu J, Albert J, Mayer S. The Effect of a Future-Self Avatar Mobile Health Intervention (FutureMe) on Physical Activity and Food Purchases: Randomized Controlled Trial. J Med Internet Res. 2022 Jul 7;24(7):e32487. doi: 10.2196/32487.

Helpful Links

• Renner and Schwarzer, 2005

Study record dates

Study Major Dates

• Study Start (Actual): November 17, 2020
• Primary Completion (Actual): March 9, 2021
• Study Completion (Actual): April 30, 2021

Study Registration Dates

• First Submitted: June 26, 2020
• First Submitted That Met QC Criteria: August 6, 2020
• First Posted (Actual): August 10, 2020

Study Record Updates

• Last Update Posted (Actual): May 6, 2021
• Last Update Submitted That Met QC Criteria: May 5, 2021
• Last Verified: May 1, 2021

More Information

Terms related to this study

• Keywords: Physical Activity; Randomized controlled trial; Motivation; Nutrition; mHealth; Self-efficacy; Avatar; Self-competence; Perceived behavior related control
• Other Study ID Numbers: FSA2020

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Based on the data privacy statement of the study and the ethic's commission application, data cannot be analyzed or shared on an individual participant basis.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No