Skip to main content

Designing a Large Language Model-Based Coaching Intervention for Lifestyle Behavior Change

  • Conference paper
  • First Online:
Design Science Research for a Resilient Future (DESRIST 2024)

Abstract

Adopting and maintaining healthy lifestyle behaviors such as regular exercise and balanced nutrition remain challenging despite their well-documented benefits for preventing chronic diseases and promoting overall well-being. Motivational Interviewing (MI) has emerged as a promising technique to address ambivalence and facilitate behavior change. However, traditional face-to-face delivery of MI interventions is limited by scalability and accessibility issues. Leveraging recent advancements in LLMs, this paper proposes an innovative approach to deliver MI-based coaching for lifestyle behavior change digitally. Following a problem-centered DSR approach, we created an initial prototype based on MI theory and qualitative user interviews using ChatGPT (GPT-3.5). We evaluated our prototype in a qualitative study. Our research outcomes include five design principles and thirteen system requirements. This research enhances the design knowledge base in LLM-based health coaching. It marks an essential first step towards designing LLM-based MI interventions, contributing valuable insights for future research in this emerging field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Warburton, D.E.R., Nicol, C.W., Bredin, S.S.D.: Health benefits of physical activity: the evidence. CMAJ 174, 801–809 (2006). https://doi.org/10.1503/cmaj.051351

    Article  Google Scholar 

  2. Franz, M.J., Boucher, J.L., Rutten-Ramos, S., VanWormer, J.J.: Lifestyle weight-loss intervention outcomes in overweight and obese adults with type 2 diabetes: a systematic review and meta-analysis of randomized clinical trials. J. Acad. Nutr. Diet. 115, 1447–1463 (2015). https://doi.org/10.1016/j.jand.2015.02.031

    Article  Google Scholar 

  3. WHO: Obesity and overweight. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed 30 Oct 2023

  4. OECD, European Union: Health at a Glance: Europe 2022: State of Health in the EU Cycle. OECD (2022). https://doi.org/10.1787/507433b0-en

  5. Davis, S.: New Year’s Resolutions Statistics 2023. https://www.forbes.com/health/mind/new-years-resolutions-statistics/. Accessed 30 Oct 2023

  6. Hettema, J., Steele, J., Miller, W.R.: Motivational interviewing. Annu. Rev. Clin. Psychol. 1, 91–111 (2005). https://doi.org/10.1146/annurev.clinpsy.1.102803.143833

    Article  Google Scholar 

  7. Miller, W.R.: Motivational interviewing with problem drinkers. Behav. Psychother. 11, 147–172 (1983). https://doi.org/10.1017/S0141347300006583

    Article  Google Scholar 

  8. Miller, W.R.: Motivational Interviewing : Helping People Change (2013)

    Google Scholar 

  9. Patel, M.L., Wakayama, L.N., Bass, M.B., Breland, J.Y.: Motivational interviewing in eHealth and telehealth interventions for weight loss: a systematic review. Prev. Med. 126, 105738 (2019). https://doi.org/10.1016/j.ypmed.2019.05.026

    Article  Google Scholar 

  10. Pedamallu, H., Ehrhardt, M.J., Maki, J., Carcone, A.I., Hudson, M.M., Waters, E.A.: Technology-delivered adaptations of motivational interviewing for the prevention and management of chronic diseases: scoping review. J. Med. Internet Res. 24, e35283 (2022). https://doi.org/10.2196/35283

    Article  Google Scholar 

  11. Demszky, D., et al.: Using large language models in psychology. Nat. Rev. Psychol. 1–14 (2023). https://doi.org/10.1038/s44159-023-00241-5

  12. Peffers, K., Tuunanen, T., Rothenberger, M., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24, 45–77 (2007)

    Article  Google Scholar 

  13. Oinas-Kukkonen, H., Harjumaa, M.: Persuasive systems design: key issues, process model, and system features. CAIS 24 (2009). https://doi.org/10.17705/1CAIS.02428

  14. Channon, S., Smith, V., Gregory, J.: A pilot study of motivational interviewing in adolescents with diabetes. Arch. Dis. Child. 88, 680–683 (2003). https://doi.org/10.1136/adc.88.8.680

    Article  Google Scholar 

  15. Bommasani, R., et al.: On the opportunities and risks of foundation models (2022). http://arxiv.org/abs/2108.07258. https://doi.org/10.48550/arXiv.2108.07258

  16. Dwivedi, Y., et al.: “So what if ChatGPT wrote it?”: multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int. J. Inf. Technol. Manag. 71 (2023). https://doi.org/10.1016/j.ijinfomgt.2023.102642

  17. Stade, E.C., et al.: Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation. PsyArXiv (2023). https://doi.org/10.31234/osf.io/cuzvr

  18. Sison, A.J.G., Daza, M.T., Gozalo-Brizuela, R., Garrido-Merchán, E.C.: ChatGPT: more than a “weapon of mass deception” ethical challenges and responses from the human-centered artificial intelligence (HCAI) perspective. Int. J. Hum.–Comput. Interact. 1–20 (2023).https://doi.org/10.1080/10447318.2023.2225931

  19. Gregor, S., Chandra Kruse, L., Seidel, S.: The anatomy of a design principle. J. Assoc. Inf. Syst. 21, 1622–1652 (2020). https://doi.org/10.17705/1jais.00649

  20. Gioia, D.A., Corley, K.G., Hamilton, A.L.: Seeking qualitative rigor in inductive research: notes on the gioia methodology. Organ. Res. Methods 16, 15–31 (2013). https://doi.org/10.1177/1094428112452151

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sophia Meywirth .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Meywirth, S. (2024). Designing a Large Language Model-Based Coaching Intervention for Lifestyle Behavior Change. In: Mandviwalla, M., Söllner, M., Tuunanen, T. (eds) Design Science Research for a Resilient Future. DESRIST 2024. Lecture Notes in Computer Science, vol 14621. Springer, Cham. https://doi.org/10.1007/978-3-031-61175-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-61175-9_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-61174-2

  • Online ISBN: 978-3-031-61175-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics