Towards a Design Framework for Conversational Agents for Diabetes Prevention
Authors: 
Abdullah Bin Sawad, Rayed Alakhtar, Badraddin Alturki, Bhuva Narayan, Shanshan Lin, Mukesh Prasad, 
A. Baki KocaballiAuthors Info & Claims
Abdullah Bin Sawad, Rayed Alakhtar, Badraddin Alturki, Bhuva Narayan, Shanshan Lin, Mukesh Prasad, A. Baki KocaballiAuthors Info & ClaimsPages 387 - 398
Abstract
Type 2 diabetes (T2D) has emerged as a significant catalyst for various health conditions. The availability and cost of health professionals pose challenges, limiting access to personalised lifestyle support. To address this issue, utilising Conversational Agents (CAs) presents an opportunity to improve scalability and adoption by improving efficiency and engagement. Thus, this study focuses on the potential impact and response to T2D. This paper aims to develop a framework for designing CA functions that support individuals at risk of T2D to be more active and raise their awareness. The study involves a mixed methods approach, including a survey conducted among 30 participants in Sydney and Jeddah, followed by semi-structured interviews conducted with 10 participants. While descriptive statistics were used to analyse the survey, the interviews were analysed using thematic analysis. Drawing upon the interviews and relevant literature, this study proposes developing a preliminary framework to help design CAs that support individuals with prediabetes to adopt a more active lifestyle.
References
[1]
[1] [n. d.]. ([n. d.]). https://otter.ai/
[2]
C. Abras, D. Maloney-Krichmar, and J. Preece. 2004. User-Centered Design. Sage Publications.
[3]
Merav Allouch, Amos Azaria, and Rina Azoulay. 2021. Conversational agents: Goals, technologies, vision and challenges. Sensors 21, 24 (2021), 8448.
[4]
[4] Prediabetes Australia. 2016. (2016). https://www.diabetesaustralia.com.au/about-diabetes/pre-diabetes/
[5]
S. Baptista, G. Wadley, D. Bird, B. Oldenburg, and J. Speight. 2020. Acceptability of an embodied conversational agent for type 2 diabetes self-management education and support via a smartphone app: Mixed methods study. JMIR MHealth and UHealth 8 (2020), 7. https://doi.org/10.2196/17038
[6]
Jeremy Beaudry, Alyssa Consigli, Colleen Clark, and Keith J. Robinson. 2019. Getting Ready for Adult Healthcare: Designing a Chatbot to Coach Adolescents with Special Health Needs Through the Transitions of Care. Journal of Pediatric Nursing 49 (2019), 85–91. https://doi.org/10.1016/j.pedn.2019.09.004
[7]
Nicholas Bott, Sharon Wexler, Lin Drury, Chava Pollak, Victor Wang, Kathleen Scher, and Sharon Narducci. 2019. A Protocol-Driven, Bedside Digital Conversational Agent to Support Nurse Teams and Mitigate Risks of Hospitalization in Older Adults: Case Control Pre-Post Study. J Med Internet Res 21, 10 (17 Oct 2019), e13440.
[8]
Benjamin Chaix, Jean-Emmanuel Bibault, Arthur Pienkowski, Guillaume Delamon, Arthur Guillemassé, Pierre Nectoux, and Benoît Brouard. 2019. When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot. JMIR Cancer 5, 1 (02 May 2019), e12856.
[9]
N. H. Cho, J. E. Shaw, S. Karuranga, Y. Huang, da Rocha Fernandes, J. D., A. W. Ohlrogge, and B. Malanda. 2018. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Research and Clinical Practice 138 (2018), 271–281. https://doi.org/10.1016/j.diabres.2018.02.023
[10]
V. Clarke, V. Braun, and N. Hayfield. 2015. Qualitative Psychology: A Practical Guide to Research Methods. Qualitative Psychology (2015), 1–312. https://books.google.co.za/books?id=lv0aCAAAQBAJ
[11]
Simon Coghlan, Kobi Leins, Susie Sheldrick, Marc Cheong, Piers Gooding, and Simon D’Alfonso. 2023. To chat or bot to chat: Ethical issues with using chatbots in mental health. DIGITAL HEALTH 9 (2023), 20552076231183542.
[12]
J. Creswell. 2014. A concise introduction to mixed methods research [Book Review] | Evaluation Journal of Australasia. https://search-informit-org.ezproxy.lib.uts.edu.au/doi/abs/10.3316/ielapa.083474155462333
[13]
C. Darviri, E. C. Alexopoulos, A. K. Artemiadis, X. Tigani, C. Kraniotou, P. Darvyri, and G. P. Chrousos. 2014. The Healthy Lifestyle and Personal Control Questionnaire (HLPCQ): A novel tool for assessing self-empowerment through a constellation of daily activities. BMC Public Health 14, 1 (2014), 1–10. https://doi.org/10.1186/1471-2458-14-995/TABLES/6
[14]
Katherine Easton, Stephen Potter, Remi Bec, Matthew Bennion, Heidi Christensen, Cheryl Grindell, Bahman Mirheidari, Scott Weich, Luc de Witte, Daniel Wolstenholme, and Mark S Hawley. 2019. A Virtual Agent to Support Individuals Living With Physical and Mental Comorbidities: Co-Design and Acceptability Testing. J Med Internet Res 21, 5 (30 May 2019), e12996.
[15]
Stephanie Greer, Danielle Ramo, Yin-Juei Chang, Michael Fu, Judith Moskowitz, and Jana Haritatos. 2019. Use of the Chatbot “Vivibot” to Deliver Positive Psychology Skills and Promote Well-Being Among Young People After Cancer Treatment: Randomized Controlled Feasibility Trial. JMIR Mhealth Uhealth 7, 10 (31 Oct 2019), e15018. https://doi.org/10.2196/15018
[16]
Martin Hasal, Jana Nowaková, Khalifa Ahmed Saghair, Hussam Abdulla, Václav Snášel, and Lidia Ogiela. 2021. Chatbots: Security, privacy, data protection, and social aspects. Concurrency and Computation: Practice and Experience 33, 19 (2021), e6426.
[17]
Sandra Hauser-Ulrich, Hansjörg Künzli, Danielle Meier-Peterhans, and Tobias Kowatsch. 2020. A Smartphone-Based Health Care Chatbot to Promote Self-Management of Chronic Pain (SELMA): Pilot Randomized Controlled Trial. JMIR Mhealth Uhealth 8, 4 (3 Apr 2020), e15806. http://mhealth.jmir.org/2020/4/e15806/
[18]
Linwei He, Divyaa Balaji, Reinout W Wiers, Marjolijn L Antheunis, and Emiel Krahmer. 2023. Effectiveness and acceptability of conversational agents for smoking cessation: A systematic review and meta-analysis. Nicotine and Tobacco Research 25, 7 (2023), 1241–1250.
[19]
Ahmad Ishqi Jabir, Laura Martinengo, Xiaowen Lin, John Torous, Mythily Subramaniam, and Lorainne Tudor Car. 2023. Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments. Journal of Medical Internet Research 25 (2023), e44548.
[20]
Tobias Kowatsch, Theresa Schachner, Samira Harperink, Filipe Barata, Ullrich Dittler, Grace Xiao, Catherine Stanger, Florian v Wangenheim, Elgar Fleisch, Helmut Oswald, 2021. Conversational agents as mediating social actors in chronic disease management involving health care professionals, patients, and family members: multisite single-arm feasibility study. Journal of medical Internet research 23, 2 (2021), e25060.
[21]
L. L. Kramer, Ter Stal, Mulder S., B. C., E. De Vet, and L. Van Velsen. 2020. Developing embodied conversational agents for coaching people in a healthy lifestyle: Scoping review. Journal of Medical Internet Research 22, 2 (2020), 1–11. https://doi.org/10.2196/14058
[22]
L. Laranjo, A. G. Dunn, H. L. Tong, A. B. Kocaballi, J. Chen, R. Bashir, D. Surian, B. Gallego, F. Magrabi, A. Y. S. Lau, and E. Coiera. 2018. Conversational agents in healthcare: A systematic review. Journal of the American Medical Informatics Association 25, 9 (2018), 1248–1258. https://doi.org/10.1093/jamia/ocy072
[23]
Daniel G Morrow, H Chad Lane, and Wendy A Rogers. 2021. A framework for design of conversational agents to support health self-care for older adults. Human Factors 63, 3 (2021), 369–378.
[24]
Mark A. Neerincx, Willeke van Vught, Olivier Blanson Henkemans, Elettra Oleari, Joost Broekens, Rifca Peters, Frank Kaptein, Yiannis Demiris, Bernd Kiefer, Diego Fumagalli, and Bert Bierman. 2019. Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management. Frontiers in Robotics and AI 6 (2019). https://doi.org/10.3389/frobt.2019.00118
[25]
Australian Institute of Health andWelfare. 2018. 3.3 Chronic conditions. Chapter 15, 16 (2018), 1–9.
[26]
World Health Organisation. 2016. Global Report on Diabetes. https://www.who.int/health-topics/diabetes#tab=tab_2
[27]
Andreia Pinto, Diogo Martinho, João Matos, David Greer, Ana Vieira, André Ramalho, Goreti Marreiros, and Alberto Freitas. 2023. Recommendation systems to promote behavior change in patients with diabetes mellitus type 2: A Systematic Review. Expert Systems with Applications (2023), 120726.
[28]
Margherita Rampioni, Vera Stara, Elisa Felici, Lorena Rossi, and Susy Paolini. 2021. Embodied conversational agents for patients with dementia: thematic literature analysis. JMIR mHealth and uHealth 9, 7 (2021), e25381.
[29]
Ubaid Ur Rehman, Dong Jin Chang, Younhea Jung, Usman Akhtar, Muhammad Asif Razzaq, and Sungyoung Lee. 2020. Medical instructed real-time assistant for patient with glaucoma and diabetic conditions. Applied Sciences 10, 7 (2020), 2216.
[30]
Hyeyoung Ryu, Soyeon Kim, Dain Kim, Sooan Han, Keeheon Lee, and Younah Kang. 2020. Simple and steady interactions win the healthy mentality: designing a chatbot service for the elderly. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (2020), 1–25.
[31]
Avinash Saravanan, Maria Tsfasman, Mark A Neerincx, and Catharine Oertel. 2022. Giving Social Robots a Conversational Memory for Motivational Experience Sharing. In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE, 985–992.
[32]
Bin Sawad, Narayan A., Alnefaie B., Maqbool A., Mckie A., Smith I., Yuksel J., Puthal B., and Prasad D.2022. B. A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions 22 (2022), 7. https://doi.org/10.3390/s22072625
[33]
T. Schachner, R. Keller, and F. v. Wangenheim. 2020. Artificial intelligence-based conversational agents for chronic conditions: Systematic literature review. Journal of Medical Internet Research 22 (2020), 9. https://doi.org/10.2196/20701
[34]
Sofia Schöbel, Anuschka Schmitt, Dennis Benner, Mohammed Saqr, Andreas Janson, and Jan Marco Leimeister. 2023. Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers. Information Systems Frontiers (2023), 1–26.
[35]
[35] Australian National Diabetes Strategy. 2020. (2020), 2016–2020.
[36]
Diabetes Victoria. 2015. Diabetes Victoria. (2015). http://www.diabetesvic.org.au/
[37]
V. Wangenheim, J. Louise, R. Keller, J. Yao, G. Wilhelm, and S. Hartmann. 2021. Digital Health Services for the Management and Prevention of.
Index Terms
- Towards a Design Framework for Conversational Agents for Diabetes Prevention
Recommendations
Informing the design of question-asking conversational agents for reflection
AbstractReflecting on everyday experiences offers valuable insights and has the potential to enhance psychological well-being. Yet, only some have access to a facilitator for reflection. Conversational agents hold promise as companions for these ...
Using Experience-Based Participatory Approach to Design Interactive Voice User Interfaces for Delivering Physical Activity Programs with Older Adults
HAI '23: Proceedings of the 11th International Conference on Human-Agent InteractionVoice User Interfaces (VUIs) are popular among older adults, who find them easy to use and perceive them as social companions. However, there is a lack of research on voice-based applications to support physical activities for older adults. To address ...
Adopting the sensemaking perspective for chronic disease self-management
Display Omitted Health self-monitoring technologies call for new theories of health behaviors.The sensemaking perspective is adopted to chronic disease self-management.We conduct meta-synthesis of qualitative studies of diabetes self-management.The meta-...
Comments
Information & Contributors
Information
Published In
December 2023
733 pages
ISBN:9798400717079
DOI:10.1145/3638380
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 10 May 2024
Check for updates
Author Tags
Qualifiers
- Short-paper
- Research
- Refereed limited
Conference
OzCHI 2023
Acceptance Rates
Overall Acceptance Rate 362 of 729 submissions, 50%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 65Total Downloads
- Downloads (Last 12 months)65
- Downloads (Last 6 weeks)16
Reflects downloads up to 25 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format