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RecruitingNCT07120802BETTER4ALLUpdated Aug 13, 2025

Better4All Personalized Intervention Pilot Study

An interventional study of BETTER4U Mobile App and Wearable Use (End-User Group) and BETTER4U Intervention Platform Testing (Implementer Group) in Obesity Prevention, sponsored by Harokopio University. Recruiting at 7 sites in 7 countries. Open to participants aged 18 Years to 65 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-08-13.

Sponsored by Harokopio University · Not applicable, Interventional, and Prevention

Phase
Not applicable
Study type
Interventional
Enrollment
490
Allocation
Non-randomized
Ages
18 Years to 65 Years
Sex
All
01

Study summary

The BETTER4U project (Preventing obesity through Biologically and bEhaviorally Tailored inTERventions for you) is funded by the European Union (EU) and involves an international consortium consisting of 28 partners across Europe, Israel, and Australia. The project started in November 2023 and will run until October 2027. The main aim of BETTER4U is to improve weight management through a tailor-made intervention, the "BETTER4ALL personalized intervention", using modern monitoring tools and artificial intelligence (AI), including machine learning (ML) practices.

In the context of the BETTER4U project, the present Pilot Study aims to a) evaluate the usability, feasibility and acceptability of the BETTER4U mobile application ("BETTER4U App") and Intervention Platform that will be used to monitor and collect data from participants in the BETTER4ALL personalized intervention (randomized controlled trial; RCT) and b) collect data to evaluate and improve the BETTER4U causal AI models for the prevention of weight gain, before deploying them at large scale, as well as test and identify the optimal ways of delivering the AI-based interventions to the participants. The study will be conducted in seven sites in Cyprus, France, Greece, Poland, Portugal, Spain, and Sweden.

The BETTER4All Pilot Study will be a longitudinal, correlational, observational study, including a total of n=490 participants, equally distributed among the seven sites (i.e. n=70 per site). Specifically, n=60 (± 3-5) "general population" participants (henceforth: "end-users" of the wearables and the BETTER4U App) and n=10 (± 3-5) healthcare or other types of providers (henceforth: potential "implementers" of the BETTER4U intervention) will constitute each site's sample.

The study will involve the following two components: a) the administration of the wearables (smartwatches) to the "end-users" and their registration to and training on the BETTER4U App, to be used for a total duration of three weeks (21 days). During this period, their lifestyle behaviours (i.e. "BETTER4U Core Behavioural Indicators - BCBIs", such as eating occasions, physical activity, sedentary time, sleep etc.) and "living environment indicators - LEIs"; (e.g. access to parks in your area, distance from your home to your work place etc.) will be recorded daily, either in an automated way via the wearables or self-reported by the end-users through the App; and b) the registration to and training on the BETTER4U Intervention Platform of the "implementers" for a total duration of one week (7 days), during which they will be asked to test the platform's functionalities using synthetic data. The implementers will also be provided with the wearables and the App (similarly to the end-users) for one week only to allow collection of additional data that will help verify the accuracy of the algorithms in the gathered data from the wearables/monitoring tools regarding BCBIs and LEIs.

Overall, the outcomes and the findings of the Pilot Study will be used to further refine, optimize, and adjust the tools for the BETTER4ALL RCT, according to the feedback received by both end-users' and implementers' perspectives.

Read the detailed description

The BETTER4All Pilot Study is a multicenter, longitudinal, observational study designed to assess the usability, feasibility, and acceptability of the BETTER4U App and BETTER4U Intervention Platform, both of which integrate real-time behavioral monitoring and artificial intelligence (AI)-driven decision support tools. Conducted in seven European countries (Cyprus, France, Greece, Poland, Portugal, Spain, and Sweden), the study includes approximately 490 adult participants split into two groups: (a) "end-users" from the general population, who will use wearable devices and the mobile App for 21 days, and (b) "implementers," healthcare professionals who will test the intervention platform for 7 days using synthetic and self-recorded data.

The BETTER4U system employs Bluetooth Low Energy (BLE) smartwatches for passive data collection, including accelerometer signals, heart rate variability, sleep structure, and geolocation data. Data from the wearables and smartphone sensors are processed using AI and machine learning algorithms to derive behavioral indicators such as physical activity, eating, sleep patterns (termed BETTER4U Core Behavioral Indicators - BCBIs), and contextual environmental factors (Living Environment Indicators - LEIs). These indicators are calculated both locally and on secure servers via structured data pipelines, ensuring privacy and GDPR compliance.

Data collection comprises three sources: (1) passively collected wearable/App data, (2) online questionnaires via RedCap (e.g., IPAQ, GAD-2, PHQ-2, EQ-5D-5L, PSQI, Mini-EAT), and (3) "ground truth" data logged by implementers to validate algorithmic outputs. Engagement metrics, such as app usage duration and feature interaction frequency, are also automatically recorded. Feedback on usability and feasibility is collected via validated tools, including the System Usability Scale (SUS), MAUQ, AIM, IAM, and FIM.

The primary technical aim is to verify and refine the causal AI models developed in earlier project phases (WP5), ensuring the system is optimized for personalized intervention delivery in the upcoming BETTER4ALL randomized controlled trial (WP7).

02

Conditions studied

  • Obesity Prevention

Keywords

  • weight management
  • polygenic risk score
  • artificial intelligence
  • personalized intervention
  • obesity
  • randomized controlled trial
03

Who can participate

Ages eligible
18 Years to 65 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  • Age: Participants aged 18-65 years to represent the adult general population.
  • Body Mass Index (BMI):

    • Overweight or obesity group: BMI ≥ 25 kg/m².
    • Normal weight group: BMI 18.5-24.9 kg/m².
  • Technology Use:

    • Willingness and ability to use wearable devices and an Android mobile application for the duration of the study.
    • Owning a smartphone device with the Android operating system.
  • Eating utensil technique: dominant hand gestures that correspond to handling of food via a fork or a spoon.
  • Language Proficiency: Ability to read and understand the language in which the mobile app and study materials are provided.
  • Consent: Willing to provide informed consent to participate in the study.
  • Residency: Must be a resident of one of the seven participating countries.
  • Availability: Able to participate for the full three-week duration of the study and comply with the study protocol.

Exclusion criteria

Exclusion Criteria:

  • Health Conditions: Pregnant or breastfeeding women, as they might have different lifestyle behaviours or health needs.
  • Physical Limitations: Any physical or mental condition that would prevent the participant from using the wearable device or mobile application as intended.
  • Eating utensil technique: eating food with chopsticks on a daily or regular basis.
  • Technical Incompatibility: Individuals who do not own a compatible smartphone or are unable to use the provided wearable devices for technical reasons.
04

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Non-randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
490 participants (estimated)

Study arms

  • Other
    End-users - General Population Participants

    Adults from the general population (aged 18- 65 years, with normal weight or overweight/obesity) who will use the BETTER4U mobile application and a wearable smartwatch for 21 days. During this period, lifestyle behaviors and living environment indicators will be recorded daily, either automatically via the wearable or through self-reports via the app.

    Behavioral: BETTER4U Mobile App and Wearable Use (End-User Group)

  • Other
    Implementers - Healthcare Professionals

    Healthcare professionals (e.g., medical doctors, dietitians/nutritionists, psychologists, nurses) who will use the BETTER4U Intervention Platform, mobile application, and wearable smartwatch for 7 days. During this period, they will interact daily with the Intervention Platform using synthetic data to evaluate its functionalities and usability. Additionally, they will wear the smartwatch and use the app to record lifestyle behavior and living environment indicators (LEIs). They will provide structured "growth truth" data (e.g., transportation mode, activity levels, sleep quality) to validate the accuracy of the AI algorithms. Their feedback will help optimize their intervention delivery system and AI-based tools before large-scale deployment.

    Behavioral: BETTER4U Intervention Platform Testing (Implementer Group)

Interventions

  • BehavioralBETTER4U Mobile App and Wearable Use (End-User Group)

    Participants from the general population ("end-users") will use a smartwatch and the BETTER4U mobile app for 21 days. The app passively collects data (physical activity, sleep, eating behaviors, environment), while participants may self-report certain behaviors. The goal is to assess the usability, feasibility, and acceptability of the tools and to collect real-world behavioral data for refining AI models.

  • BehavioralBETTER4U Intervention Platform Testing (Implementer Group)

    Healthcare professionals and other potential implementers will test the BETTER4U Intervention Platform and mobile app for 7 days. They will assess system usability, complete synthetic case simulations, and provide daily feedback via Google Forms. They also wear the smartwatch and use the app for data validation purposes. The goal is to evaluate platform usability and collect ground-truth data for validating AI algorithm outputs.

05

What researchers measure

Primary outcomes

  1. System Usability Scale (SUS) Score - End-Users

    Usability of the BETTER4U App as reported by end-users using the validated SUS questionnaire (10 items, total score 0-100).

    Time frame: Day 21 (end of participation period for end-users)

  2. System Usability Scale (SUS) Score - Implementers

    Usability of the BETTER4U App and Intervention Platform as reported by implementers using the validated SUS questionnaire. Unit of Measure: Mean SUS score (0-100).

    Time frame: Day 7 (end of participation period for implementers

  3. Acceptability of Intervention Measure (AIM) Score - End-Users

    Acceptability of the BETTER4U App rated by end-users using the AIM (4 items, 5-point Likert scale). Unit of Measure: Mean AIM score (1-5)

    Time frame: Day 21

  4. AIM Score - Implementers

    Acceptability of the BETTER4U Intervention Platform rated by implementers using AIM. Mean AIM score (1-5)

    Time frame: Day 7

  5. Feasibility of Intervention Measure (FIM) Score - End-Users

    Feasibility of the BETTER4U App as perceived by end-users. Mean FIM score (1-5)

    Time frame: Day 21

  6. FIM Score - Implementers

    Feasibility of the BETTER4U Intervention Platform as perceived by implementers. Mean FIM score (1-5).

    Time frame: Day 7

  7. Intervention Appropriateness Measure (IAM) Score - End-Users

    Appropriateness of the BETTER4U App as rated by end-users. Mean IAM score (1-5).

    Time frame: Day 21

  8. IAM Score - Implementers

    Appropriateness of the BETTER4U Intervention Platform as rated by implementers.Mean IAM score (1-5)

    Time frame: Day 7

Secondary outcomes

  1. mHealth App Usability Questionnaire (MAUQ) Score - Implementers

    Usability of the Intervention Platform among implementers, assessed with the adapted MAUQ.

    Time frame: Day 7

  2. App Usage - Number of Logins (End-Users)

    App engagement as measured by the number of logins during the study. Mean number of logins per participant

    Time frame: Day 21

  3. App Usage - Time Spent per Module (End-Users)

    Engagement measured by the average time (in minutes) spent per module within the BETTER4U App. Mean time (minutes) per module.

    Time frame: Day 21

  4. Thematic Analysis of Open Feedback (Qualitative)

    Qualitative analysis of open-ended feedback provided by participants regarding the usability and content of the BETTER4U tools.

    Time frame: Day 21 (end-users) / Day 7 (implementers)

06

Study locations

7 of 7 sites recruiting
  • University of Cyprus (Ucy)
    Nicosia, 2109, Cyprus
    • Constantinos Deltas, Professor · Contact
    Recruiting
  • Universite Lyon 1 Claude Bernard (Ucbl)
    Villeurbanne, 69622 CEDEX, France
    • Julie-Anne Nazare · Contact
    Recruiting
  • Harokopio University
    Athens, Aticca 17676, Greece
    Recruiting
  • Uniwersytet Swps (Swps)
    Wroclaw, 53-238, Poland
    • Aleksandra L, Professor · Contact
    Recruiting
  • Centro de Estudos E Investigacao Em Dinamicas Sociais E Saude Associacao Sem Fins Lucrativos (Ceidss)
    Lisbon, 1649-016, Portugal
    • Ana Isabel Rito, Professor · Contact
    Recruiting
  • Universidad de Navarra (Unav)
    Pamplona, Navarre 31008, Spain
    • Mai Bes-Rastrollo, Professor · Contact
    Recruiting
  • Karolinska Institutet
    Huddinge, 141 83, Sweden
    • Ioannis Ioakeimidis · Contact
    Recruiting
07

References and documents

Individual participant data

Plan to share: Undecided

08

Registry details

Key details

Study ID
NCT07120802
Lead sponsor
Harokopio University
Collaborators
University of Navarra, University of Cyprus, Karolinska Institutet, University SWPS, Claude Bernard University, CENTRO DE ESTUDOS E INVESTIGACAO EM DINAMICAS SOCIAIS E SAUDE ASSOCIACAO SEM FINS LUCRATIVOS (CEIDSS)
Responsible party
Yannis Manios (Professor, Harokopio University) — Principal investigator
First posted
Aug 13, 2025
Start date
Jun 1, 2025
Primary completion
Sep 30, 2025 (estimated)
Completion
Sep 30, 2025 (estimated)
Last update
Aug 13, 2025

Study contacts

Yannis Manios, Professor
Contact
manios@hua.gr
2109549156 ext. +30
Yannis Manios, Professor
principal investigator · Department of Nutrition and Dietetics, School of Health Science & Education, Harokopio University, Athens, Greece

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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