Emerging technologies and virtual medicine in obesity management

Authors

  • F H Van Zyl Private practice and Clinical Projects Research Trial Centre, Worcester; Mediclinic Worcester Hospital, Western Cape, South Africa
  • M Noeth Zuid-Afrikaans Hospital, Pretoria; Department of Internal Medicine, University of Pretoria, South Africa https://orcid.org/0000-0002-0563-5617
  • P N Diab Atrium Diabetes Centre, Gillitts, KwaZulu-Natal; Department of Family Medicine, University of Pretoria, South Africa https://orcid.org/0009-0004-9896-4576
  • M Conradie-Smit Division of Endocrinology, Department of Medicine, Stellenbosch University and Tygerberg Academic Hospital, Cape Town, South Africa
  • W May Cape Town Bariatric Clinic, Life Kingsbury Hospital, Cape Town, South Africa https://orcid.org/0009-0004-8573-224X

DOI:

https://doi.org/10.7196/SAMJ.2025.v115i9b.3699

Keywords:

Technology, Obesity, Guideline, South Africa

Abstract

RECOMMENDATIONS

1. Implementation of strategies in the management of obesity can be delivered through web-based platforms (e.g. online education on medical nutrition therapy and physical activity) or mobile devices (e.g. daily weight reporting through a smartphone phone application) (Level 2a, Grade B).

2. We suggest that healthcare providers incorporate individualised feedback and follow-up (e.g. personalised coaching or feedback via phone or email) into technology-based management strategies to improve weight loss outcomes (Level 4, Grade D).

3. The use of wearable activity-tracking technology should be part of a comprehensive strategy for weight loss (Level 1a, Grade A).

 

References

1. Afshin A, Babalola D, McLean M, et al. Information technology and lifestyle: A systematic evaluation of internet and mobile interventions for improving diet, physical activity, obesity, tobacco, and alcohol use. J Am Heart Assoc 2016;5(9):e003058. https://doi.org/10.1161/JAHA.115.003058

2. BakerJS,SupriyaR,DutheilF,GaoY.Obesity:Treatments,conceptualizations,andfuturedirectionsfor a growing problem. Biology (Basel) 2022;11(2):160. https://doi.org/10.3390/biology11020160

3. Bays HE, Fitch A, Cuda S, et al. Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023. Obes Pillars 2023;6:100065. https://doi. org/10.1016/j.obpill.2023.100065

4. Bedi S, Liu Y, Orr-Ewing L, et al. Testing and evaluation of health care applications of large language models: A systematic review. JAMA 2025;333(4):319-328. https://doi.org/10.1001/jama.2024.21700

5. Cheatham SW, Stull KR, Fantigrassi M, Motel I. The efficacy of wearable activity tracking technology as part of a weight loss program: A systematic review. J Sports Med Phys Fitness 2018;58(4):534-548. https:// doi.org/10.23736/S0022-4707.17.07437-0

6. Coons MJ, Demott A, Buscemi J, et al. Technology interventions to curb obesity: A systematic review of the current literature. Curr Cardiovasc Risk Rep 2012;6(2):120-134. https://doi.org/10.1007/s12170- 012-0222-8

7. FreshwaterM,ChristensenS,OshmanL,BaysHE.Behavior,motivationalinterviewing,eatingdisorders, and obesity management technologies: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022. Obes Pillars 2022;2:1000014. https://doi.org/10.1016/j.obpill.2022.100014

8. Kahan S, Look M, Fitch A. The benefit of telemedicine in obesity care. Obesity (Silver Spring) 2022;30(3):577-586. https://doi.org/10.1002/oby.23382

9. Protano C, de Giorgi A, Valeriani F, et al. Can digital technologies be useful for weight loss in individuals with overweight or obesity? A systematic review. Healthcare (Basel) 2024;12(6):670. https://doi. org/10.3390/healthcare12060670

10. RaoG,BurkeLE,SpringBJ,etal.Newandemergingweightmanagementstrategiesforbusyambulatory settings: A scientific statement from the American Heart Association endorsed by the Society of Behavioral Medicine. Circulation 2011;124(10):1182-1203. https://doi.org/10.1161/CIR.0b013e31822b9543

11. Rogers RJ, Lang W, Barone Gibbs B, et al. Applying a technology‐based system for weight loss in adults with obesity. Obes Sci Pract 2016;2(1):3-12. https://doi.org/10.1002/osp4.18

12. Seo DC, Niu J. Evaluation of internet-based interventions on waist circumference reduction: A meta- analysis. J Med Internet Res 2015;17(7):e181. https://doi.org/10.2196/jmir.3921

13. Woessner MN, Tacey A, Levinger-Limor A, Parker AG, Levinger R, Levinger I. The evolution of technology and physical inactivity: The good, the bad, and the way forward. Front Public Health 2021;9:655491. https://doi.org/10.3389/fpubh.2021.655491

14. World Health Organization. Global strategy on digital health 2020-2025. Geneva: WHO, 2021. https:// www.who.int/publications/i/item/9789240020924 (accessed March 2025).

15. Hinchliffe N, Capehorn MS, Bewick M, Feenie J. The potential role of digital health in obesity care. Adv Ther 2022;39(10):4397-4412. https://doi.org/10.1007/s12325-022-02265-4

16. ASOI Adult Obesity Clinical Practice Guideline adaptation (ASOI version 1, 2022) by: Tully L, Gibson I, Glynn L. Chapter adapted from: Tytus R, Divalentino D, Naji L. https://asoi.info/guidelines/technologies/ (accessed March 2025).

17. South African Government. Protection of Personal Information Act 4 of 2013. https://www.gov.za/ documents/protection-personal-information-act (accessed March 2025).

18. StauntonC,AdamsR,AndersonD,etal.ProtectionofPersonalInformationAct2013anddataprotection for health research in South Africa. Int Data Priv Law 2020;10(2):160-179. https://doi.org/10.1093/idpl/ ipz024

19. Gudzune KA, Bleich SN, Clark JM. Efficacy of commercial weight-loss programs. Ann Intern Med 2015;163(5):399. https://doi.org/10.7326/l15-5130-3

20. Finkelstein EA, Kruger E. Meta- and cost-effectiveness analysis of commercial weight loss strategies. Obesity (Silver Spring) 2014;22(9):1942-1951. https://doi.org/10.1002/oby.20824

21. Wadden TA, Berkowitz RI, Womble LG, et al. Randomized trial of lifestyle modification and pharmacotherapy for obesity. N Engl J Med 2005;353(20):2111-2120. https://doi.org/10.1056/ NEJMoa050156

22. Huang J, Yu H, Marin E, Brock S, Carden D, Davis T. Physicians’ weight loss counseling in two public hospital primary care clinics. Acad Med 2004;79(2):156-161. https://doi.org/10.1097/00001888- 200402000-00012

23. Cooper Z, Doll HA, Hawker DM, et al. Testing a new cognitive behavioural treatment for obesity: A randomized controlled trial with three-year follow-up. Behav Res Ther 2010;48(8):706-713. https://doi. org/10.1016/j.brat.2010.03.008

24. Jeffery RW, Drewnowski A, Epstein LH, et al. Long-term maintenance of weight loss: Current status. Health Psychol 2000;19(1S):5-16. https://doi.org/10.1037/0278-6133.19.suppl1.5

25. Turk MW, Yang K, Hravnak M, Sereika SM, Ewing LJ, Burke LE. Randomized clinical trials of weight loss maintenance: A review. J Cardiovasc Nurs 2009;24(1):58-80. https://doi.org/10.1097/01. JCN.0000317471.58048.32

26. Taylor P. Smartphone users in South Africa 2014-2023. Statistica, 2023. https://www.statista.com/ statistics/488376/forecast-of-smartphone-users-in-south-africa/ (accessed March 2025).

27. Gur BA, Kulesza J. Equitable access to satellite broadband services: Challenges and opportunities for developing countries. Telecomm Policy 2024;48(5):102731. https://doi.org/10.1016/j.telpol.2024.102731

28. Jones KL, Allison AL. Game changer: The great convergence and the future of satellite-enabled direct-to- device. Aerospace Center for Space Policy and Strategy, 21 September 2023. https://csps.aerospace.org/ papers/game-changer-great-convergence-and-future-satellite-enabled-direct-device (accessed March 2025).

29. Mohan N, Ferguson AE, Cech H, et al. A multifaceted look at Starlink performance. In: Proceedings of the ACM Web Conference 2024, pp. 2723-2734. https://doi.org/10.1145/3589334.3645328 (accessed March 2025).

30. Shaengchart Y, Kraiwanit T. Starlink satellite project impact on the internet provider service in emerging economies. Res Glob 2023;6:100132. https://doi.org/10.1016/j.resglo.2023.100132

31. Raaijmakers LC, Pouwels S, Berghuis KA, Nienhuijs SW. Technology-based interventions in the treatment of overweight and obesity: A systematic review. Appetite 2015;95:138-151. https://doi. org/10.1016/j.appet.2015.07.008

32. Kodama S, Saito K, Tanaka S, et al. Effect of web-based lifestyle modification on weight control: A meta-analysis. Int J Obes (Lond) 2012;36(5):675-685. https://doi.org/10.1038/ijo.2011.121

33. Thomas JG, Bond DS, Raynor HA, Papandonatos GD, Wing RR. Comparison of smartphone‐based behavioral obesity treatment with gold standard group treatment and control: A randomized trial. Obesity (Silver Spring) 2019;27(4):572-580. https://doi.org/10.1002/oby.22410

34. Chen M, Peng X. The evolution and effects of mobile health (mHealth) intervention on weight management among healthy overweight/obese populations in China: A systematic review and meta- analysis. J Public Health Emerg 2022;6. https://doi.org/10.21037/jphe-22-54

35. Cheah KJ, Manaf ZA, Mat Ludin AF, Razalli NH. Potential role of hybrid weight management intervention: A scoping review. Digit Health 2024;10:20552076241258366. https://doi. org/10.1177/20552076241258366

36. Adebile TV, Adebile TM, Oloyede TF, et al. Telemedicine for obesity management among United States adults: A systematic and meta-analysis of intervention studies. J Telemed Telecare 2024:1357633X241247240. https://doi.org/10.1177/1357633X241247240

37. LeeS,LindquistR.Areviewoftechnology-basedinterventionstomaintainweightloss.TelemedJE Health 2015;21(3):217-232. https://doi.org/10.1089/tmj.2014.0052

38. MackenzieRM,EllsLJ,SimpsonSA,LogueJ.Coreoutcomesetforbehaviouralweightmanagement interventions for adults with overweight and obesity: Standardised reporting of lifestyle weight management interventions to aid evaluation (STAR‐LITE). Obes Rev 2020;21(2):e12961. https:// doi.org/10.1111/obr.12961

39. Rubino F, Batterham RL, Koch M, et al. Lancet Diabetes & Endocrinology Commission on the Definition and Diagnosis of Clinical Obesity. Lancet Diabetes Endocrinol 2023;11(4):226-228. https://doi.org/10.1016/S2213-8587(23)00058-X

40. Rubino F, Cummings DE, Eckel RH, et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol 2025;13(3):221-262. https://doi.org/10.1016/S2213-8587(24)00316-4

41. Burke LE, Styn MA, Sereika SM, et al. Using mHealth technology to enhance self-monitoring for weight loss: A randomized trial. Am J Prev Med 2012;43(1):20-26. https://doi.org/10.1016/j. amepre.2012.03.016

42. Hurkmans E, Matthys C, Bogaerts A, Scheys L, Devloo K, Seghers J. Face-to-face versus mobile versus blended weight loss program: Randomized clinical trial. JMIR Mhealth Uhealth 2018;6(1):e14. https://doi.org/10.2196/mhealth.7713

43. Cai X, Qiu SH, Yin H, et al. Pedometer intervention and weight loss in overweight and obese adults with type 2 diabetes: A meta‐analysis. Diabet Med 2016;33(8):1035-1044. https://doi. org/10.1111/dme.13104World Health Organization. Monitoring and evaluating digital health interventions. Geneva: WHO, 2016. https://www.who.int/publications/i/item/9789241511766 (accessed March 2025).

44. Eysenbach G; CONSORT-EHEALTH Group. CONSORT-EHEALTH: Improving and standardizing evaluation reports of web-based and mobile health interventions. J Med Internet Res 2011;13(4):e126. https://doi.org/10.2196/jmir.1923

45. Cappuccio ML, Sandoval EB, Mubin O, Obaid M, Velonaki M. Can robots make us better humans? Int J Soc Robot 2021;13(1):7-22. https://doi.org/10.1007/s12369-020-00700-6

46. Chew HSJ, Chew NW, Loong SSE, et al. Effectiveness of an artificial intelligence-assisted app for improving eating behaviors: Mixed methods evaluation. J Med Internet Res 2024;26:e46036. https:// doi.org/10.2196/46036

47. Zhang J, Oh YJ, Lange P, Yu Z, Fukoka Y. Artificial intelligence chatbot behavior change model for designing artificial intelligence chatbots to promote physical activity and a healthy diet: Viewpoint. J Med Internet Res 2020;22(9):e22845. https://doi.org/10.2196/22845

48. SafaeiM,SundararajanEA,DrissM,BoulilaW,Shapi’iA.Asystematicliteraturereviewonobesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity. Comput Biol Med 2021;136:104754. https://doi.org/10.1016/j. compbiomed.2021.104754

49. Sallam M. ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare (Basel) 2023;11(6):887. https://www.mdpi. com/2227-9032/11/6/887

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Published

2025-11-04

Issue

Section

Obesity Guideline

How to Cite

1.
Van Zyl FH, Noeth M, Diab PN, Conradie-Smit M, May W. Emerging technologies and virtual medicine in obesity management. S Afr Med J [Internet]. 2025 Nov. 4 [cited 2025 Nov. 12];115(10b):e3699. Available from: https://samajournals.co.za/index.php/samj/article/view/3699