Personalised Information System for Health Eating and Weight Loss

Nurul Aminah  Kamarudin; Rafidah  Razak; Rohaya Dahari

doi:10.32890/jdsd2025.3.1.4

Authors

Nurul Aminah Kamarudin Universiti Utara Malaysia, Malaysia
Rafidah Razak Universiti Utara Malaysia, Malaysia
Rohaya Dahari Universiti Utara Malaysia, Malaysia

DOI:

https://doi.org/10.32890/jdsd2025.3.1.4

Keywords:

Personalized nutrition, weight management, healthy eating, user experience, digital health system

Abstract

The rise in health awareness has driven the need for digital solutions to support personalised dietary management and weight loss. Existing digital health solutions lack personalised dietary and weight management strategies, which limits their effectiveness. This study develops and evaluates a Personalised Information System for Healthy Eating and Weight Loss, incorporating structured health assessments, AI-driven meal planning, and exercise recommendations tailored to user-specific data such as BMI, dietary preferences, and activity levels. Using the Waterfall model, the system was designed and tested through an online survey involving 30 respondents, which assessed five key factors: ease of Use, Usefulness, User Interface Design, User Satisfaction, and System Performance. Results indicate that 78.7% of users found the system highly useful, 86.7% praised its intuitive interface, and 90% expressed overall satisfaction. Correlation analysis reveals a strong positive relationship (r = 0.72) between ease of use and perceived usefulness, underscoring the potential of this relationship to foster long-term engagement. While digital health tools often lack adaptive recommendations, this study addresses this gap by integrating real-time feedback and AI-driven customisation. Future enhancements include integrating wearable devices and expanded meal plan options to optimise the user experience.

References

Anderson, J., & Peterson, K. (2021). Data-driven approaches to personalised nutrition. Journal of Health Informatics, 18(2), 99-115.

Apple Inc. (2023). Apple Health and fitness tracking: AI-driven health insights. Apple. https://www.apple.com/healthcare

Bass, L., Clements, P., & Kazman, R. (2015). Software architecture in practice (3rd ed.). Addison-Wesley.

Bray, G. A., Heisel, W. E., Afshin, A., Jensen, M. D., Dietz, W. H., & Hu, F. B. (2020). The Science of Obesity Management: An Endocrine Society scientific statement. Endocrine Reviews, 41(1), 1-42.

Brown, A., & Miller, P. (2020). Wearable-integrated health tracking: A new frontier in personalised wellness. Journal of Health Monitoring, 10(1), 33–50.

Dachis, A. (2021). How Noom uses AI and behavioural psychology to improve weight loss. Digital Health Insights, 15(3), 45–57.

Faulkner, L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability testing. Behaviour Research Methods, Instruments, & Computers, 35(3), 379–383.

Fitbit. (2022). Fitbit health solutions: The role of wearable devices in fitness and well-being. Fitbit. https://www.fitbit.com/

Johnson, R., Smith, T., & Lee, M. (2022). Advances in personalised nutrition and digital health. Journal of Nutrition Technology, 15(4), 89–105.

Jones, M., & White, S. (2023). Data security and privacy in digital health applications. Cybersecurity in Healthcare, 10(2), 77–89.

Kim, S., Park, H., & Lee, D. (2021). AI-driven meal recommendations for personalised nutrition: A review. International Journal of Health Technology, 19(1), 34-50.

Lee, C., Tan, H., & Wong, K. (2023). Enhancing user engagement in health applications through adaptive learning. Digital Health Research, 21(2), 55-78.

Miller, T., & Roberts, J. (2023). The role of gamification in digital health applications. Digital Health Research, 20(4), 112-129.

Nielsen, J., & Landauer, T. K. (1993). A mathematical model for finding usability problems. Proceedings of the INTERACT'93 and CHI'93 Conference on Human Factors in Computing Systems, 206-213.

Pressman, R. S., & Maxim, B. (2020). Software engineering: A practitioner’s approach (9th ed.). McGraw-Hill.

Smith, A., Jones, K., & Roberts, M. (2022). The impact of mobile health apps on dietary behaviour change: A systematic review. Journal of Digital Health, 15(3), 56–72.

Virzi, R. A. (1992). Refining the test phase of usability evaluation: How many subjects are enough? Human Factors, 34(4), 457–468.

Wang, Y., Liu, X., & Zhao, P. (2021). AI-driven dietary recommendations and user adherence: A comparative study. Journal of Computational Health, 22(1), 78–95. Weight Watchers International (WW International). (2022). Digital transformation in weight loss: Personalised AI-driven health coaching. WW International. https://www.weightwatchers.com/

World Health Organization (WHO). (2021). Non-communicable diseases: Progress monitor 2021. WHO. https://www.who.int/publications/i/item/ncd-progress-monitor-2021