โก Quick Summary
The PROTEIN mobile application, developed under the European Union H2020 project, utilizes artificial intelligence (AI) to provide personalized dietary and physical activity recommendations. A study involving 579 users across five European countries revealed that weight loss-related goals significantly enhance user engagement and meal adherence.
๐ Key Details
- ๐ Participants: 579 users from Belgium, Germany, Greece, Portugal, and the United Kingdom
- ๐งฉ Focus: Personal goals, user engagement, and meal adherence
- โ๏ธ Technology: AI-based personalized recommendations
- ๐ Study Duration: Data collected through user database and end-user questionnaire
๐ Key Takeaways
- ๐ Weight loss goals are the most common and engaging among users.
- ๐ช Health and physical activity goals are crucial for improving meal adherence.
- ๐ฅ User demographics (age and gender) influence goal congruency and adherence.
- ๐ Personalization is key to enhancing user experience in nutrition apps.
- ๐ The study informs future development of nutrition mobile applications.
- ๐ Data analysis utilized chi-square tests to identify associations.
- ๐ค AI technology integrates user preferences with expert knowledge for tailored recommendations.
๐ Background
The rise of mobile applications has transformed the landscape of health interventions, particularly in promoting healthy eating habits. The PROTEIN project aims to leverage AI technology to create a personalized user experience that encourages healthier lifestyle choices. By focusing on individual goals and preferences, the application seeks to enhance user engagement and adherence to dietary recommendations.
๐๏ธ Study
The study analyzed data from the PROTEIN app, which was piloted across various user groups in five European countries. The research aimed to explore the relationship between personal goals, meal recommendations, and adherence to those recommendations. A total of 446 end-user questionnaires were evaluated to gain insights into user engagement and the effectiveness of personalized recommendations.
๐ Results
The findings revealed that users with weight loss-related goals exhibited higher engagement levels and meal adherence. Additionally, health and physical activity goals were identified as significant factors contributing to meal adherence. The study highlighted the importance of aligning user goals with personalized recommendations to enhance overall effectiveness.
๐ Impact and Implications
The outcomes of this study have profound implications for the future of nutrition mobile applications. By emphasizing the importance of personalization and user intent, developers can create more effective tools that cater to specific user needs. This research not only contributes to the field of nutrition but also sets a precedent for integrating AI in health interventions, ultimately promoting healthier lifestyles across diverse populations.
๐ฎ Conclusion
The PROTEIN project showcases the potential of AI-driven personalized nutrition applications in enhancing user engagement and meal adherence. By focusing on individual goals and preferences, these applications can significantly improve health outcomes. As we move forward, continued research and development in this area will be essential for creating effective health interventions that resonate with users.
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Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity.
Abstract
Mobile applications have been shown to be an effective and feasible intervention medium for improving healthy food intake in different target groups. As part of the PeRsOnalized nutriTion for hEalthy livINg (PROTEIN) European Union H2020 project, the PROTEIN mobile application was developed as an end-user environment, aiming to facilitate healthier lifestyles through artificial intelligence (AI)-based personalised dietary and physical activity recommendations. Recommendations were generated by an AI advisor for different user groups, combining users’ personal information and preferences with a custom knowledge-based system developed by experts to create personalised, evidence-based nutrition and activity plans. The PROTEIN app was piloted across different user groups in five European countries (Belgium, Germany, Greece, Portugal, and the United Kingdom). Data from the PROTEIN app’s user database (n = 579) and the PROTEIN end-user questionnaire (n = 446) were analysed using the chi-square test of independence to identify associations between personal goals, meal recommendations, and meal adherence among different gender, age, and user groups. The results indicate that weight loss-related goals are more prevalent, as well as more engaging, across all users. Health- and physical activity-related goals are key for increased meal adherence, with further differentiation evident between age and user groups. Congruency between user groups and their respective goals is also important for increased meal adherence. Our study outcomes, and the overall research framework created by the PROTEIN project, can be used to inform the future development of nutrition mobile applications and enable researchers and application designers/developers to better address personalisation for specific user groups, with a focus on user intent, as well as in-app features.
Author: [‘Patra E’, ‘Kokkinopoulou A’, ‘Wilson-Barnes S’, ‘Hart K’, ‘Gymnopoulos LP’, ‘Tsatsou D’, ‘Solachidis V’, ‘Dimitropoulos K’, ‘Rouskas K’, ‘Argiriou A’, ‘Lalama E’, ‘Csanalosi M’, ‘Pfeiffer AFH’, ‘Cornelissen V’, ‘Decorte E’, ‘Dias SB’, ‘Oikonomidis Y’, ‘Marรญa Botana J’, ‘Leoni R’, ‘Russell D’, ‘Mantovani E’, ‘Aleksiฤ M’, ‘Brkiฤ B’, ‘Hassapidou M’, ‘Pagkalos I’]
Journal: Life (Basel)
Citation: Patra E, et al. Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity. Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity. 2024; 14:(unknown pages). doi: 10.3390/life14101238