Impact of Personalized Mobile Applications on Digital Behavior Change for Lifestyle Disease Prevention among Youth

References

[1] A. Afshin, M. H. Forouzanfar, M. B. Reitsma, et al., “Health Effects of Overweight and Obesity in 195 Countries over 25 Years,” N Engl J Med, vol. 377, no. 1, pp. 13–27, 2017.

[2] R. Dobbs, C. Sawers, and F. Thompson, “Overcoming obesity: an initial economic analysis,” McKinsey Global Institute, 2014.

[3] R. A. Hammond and R. Levine, “The economic impact of obesity in the United States,” Diabetes Metab Syndr Obes, vol. 3, pp. 285–295, 2010.

[4] Y. T. Lagerros and S. Ro¨ssner, “Obesity management: what brings success?” Therap Adv Gastroenterol, vol. 6, no. 1, pp. 77–88, 2013.

[5] M. de Jong, N. Jansen, and M. van Middelkoop, “A systematic review of patient barriers and facilitators for implementing lifestyle interventions targeting weight loss in primary care,” Obes Rev, vol. 24, no. 8, p. e13571, 2023.

[6] World Health Organization, “mHealth: New horizons for health through mobile technologies,” Global Observatory for eHealth series, vol. 3, 2011.

[7] S. J. Li, Y. Zhou, Y. Tang, et al., “Behavior Change Resources Used in Mobile Application-Based Interventions: A Systematic Review and Meta-Analysis of Weight-Related, Behavioral, and Metabolic Outcomes in Randomized Controlled Trials for Overweight and Obese Adults,” JMIR mHealth and uHealth, vol. 13, 2025.

[8] S. Michie, M. Richardson, M. Johnston, et al., “The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions,” Ann Behav Med, vol. 46, no. 1, pp. 81–95, 2013.

[9] S. Michie and C. Abraham, “Interventions to change health behaviours: evidence-based or evidence-inspired?” Psychol Health, vol. 19, no. 1, pp. 29–49, 2004.

[10] M. M. Michaelsen and T. Esch, “Functional Mechanisms of Health Behavior Change Techniques: A Conceptual Review,” Front Psychol, vol. 13, p. 725644, 2022.

[11] H. S. J. Chew, N. N. Rajasegaran, Y. H. Chin, et al., “Effectiveness of Combined Health Coaching and Self-Monitoring Apps on Weight- Related Outcomes in People With Overweight and Obesity: Systematic Review and Meta-analysis,” J Med Internet Res, vol. 25, p. e42432, 2023.

[12] J. Antoun, H. Itani, N. Alarab, et al., “The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis,” JMIR Mhealth Uhealth, vol. 10, no. 4, p. e35479, 2022.

[13] World Health Organization, “Noncommunicable diseases,” WHO Fact Sheets, 2023. [Online]. Available: https://www.who.int/news-room/ fact-sheets/detail/noncommunicable-diseases

[14] B. J. Fogg, “A Behavior Model for Persuasive Design,” in Proceedings of the 4th International Conference on Persuasive Technology, 2009, pp. 1–7.

[15] D. Johnson, S. Deterding, K. A. Kuhn, et al., “Gamification for Health and Wellbeing: A Systematic Review of the Literature,” Internet Inter- ventions, vol. 6, pp. 89–106, 2016.

@article{1712671,
      author = {Roopali Gupta, Anshu, Govind Kashyap, Kanchan Kumari, Priya Raj},
      title = {Impact of Personalized Mobile Applications on Digital Behavior Change for Lifestyle Disease Prevention among Youth},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {6},
      pages = {753-760},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712671.pdf},
      abstract = {The prevalence of lifestyle-related diseases including diabetes, obesity, and hypertension continues to escalate among young adults due to sedentary behavior patterns, nutritional deficiencies, and insufficient physical engagement. While mobile health (mHealth) applications present opportunities for promoting behavioral modifications, current solutions often deliver standardized recommendations that fail to address the unique requirements of youth populations. This research proposes the design and assessment of a tailored mobile application specifically targeting individuals aged 18?30 years to foster healthy lifestyle practices, enhance awareness of disease risk factors, and facilitate sustained behavioral transformation. We examine how customization enhances user participation, compliance rates, and preventive health actions through an integrated framework combining exercise programming, dietary counseling, and health education. Drawing upon contemporary systematic reviews demonstrating the efficacy of comprehensive behavior modification strategies, we propose implementing multiple evidence-based behavior change techniques spanning three resource categories. Our methodology encompasses a six-month randomized trial involving 180 participants, contrasting customized versus standardized mHealth approaches. Anticipated results suggest the personalized intervention may yield 1.5?2.0 kg additional weight reduction, alongside marked improvements in sustained engagement and health literacy.},
      keywords = {Behavior Modification, Chronic Disease Prevention, Mobile Health Technology, User Personalization, Young Adult Health, Digital Interventions},
      month = {December},
      doi = {https://doi.org/10.64388/IREV9I6-1712671}
  }