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Exploring the Potential of Virtual Agents in Atrial Fibrillation Management: Insights from a Randomized Trial

Published: 26 December 2024 Publication History

Abstract

Smartphone-based conversational agents offer a convenient way to deliver health education, particularly for managing complex health conditions such as chronic diseases. The present study explores using a smartphone-based virtual agent system to aid patients with a chronic heart condition—atrial fibrillation—to manage their health by encouraging the use of a heart rhythm sensor integrated with their smartphones. We report the results of a randomized clinical trial with 240 patients experiencing atrial fibrillation who were provided with smartphones and heart rhythm sensors for 4 months. Participants in the intervention group interacted with a virtual agent, while the control group received general health education via the WebMD app. Intervention participants completed a median 91 interactions with the agent over the 4 months of the study period, and agent features designed to increase engagement–such as storytelling–were effective at increasing use. The agent’s promotion of heart rhythm sensor use was effective, with intervention participants taking significantly more heart rhythm readings compared to those in the control group. Participants were followed for 8 months thereafter to assess the sustainability of the effects, specifically focusing on medication adherence.

References

[1]
Jordi Alonso, Montserrat Ferrer, Barbara Gandek, John E Ware, Neil K Aaronson, Paola Mosconi, Niels K Rasmussen, Monika Bullinger, Shunichi Fukuhara, Stein Kaasa, 2004. Health-related quality of life associated with chronic conditions in eight countries: results from the International Quality of Life Assessment (IQOLA) Project. Quality of life research 13 (2004), 283–298.
[2]
Ryan R Bailey. 2019. Goal setting and action planning for health behavior change. American journal of lifestyle medicine 13, 6 (2019), 615–618.
[3]
Cristina Battaglino and Timothy Bickmore. 2015. Increasing the engagement of conversational agents through co-constructed storytelling. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, Vol. 11. 9–15.
[4]
Timothy Bickmore and Justine Cassell. 1999. Small talk and conversational storytelling in embodied conversational interface agents. In AAAI fall symposium on narrative intelligence. 87–92.
[5]
Timothy Bickmore and Daniel Mauer. 2006. Modalities for building relationships with handheld computer agents. In CHI’06 extended abstracts on Human factors in computing systems. 544–549.
[6]
Timothy W Bickmore, Everlyne Kimani, Ha Trinh, Alexandra Pusateri, Michael K Paasche-Orlow, and Jared W Magnani. 2018. Managing chronic conditions with a smartphone-based conversational virtual agent. In Proceedings of the 18th International Conference on Intelligent Virtual Agents. 119–124.
[7]
Abdullah Bin Sawad, Bhuva Narayan, Ahlam Alnefaie, Ashwaq Maqbool, Indra Mckie, Jemma Smith, Berkan Yuksel, Deepak Puthal, Mukesh Prasad, and A Baki Kocaballi. 2022. A systematic review on healthcare artificial intelligent conversational agents for chronic conditions. Sensors 22, 7 (2022), 2625.
[8]
Axel Brandes, Stavros Stavrakis, Ben Freedman, Sotiris Antoniou, Giuseppe Boriani, A John Camm, Clara K Chow, Eric Ding, Johan Engdahl, Michael M Gibson, 2022. Consumer-led screening for atrial fibrillation: frontier review of the AF-SCREEN international collaboration. Circulation 146, 19 (2022), 1461–1474.
[9]
C Buttorf, T Ruder, and M Bauman. 2017. Multiple Chronic Conditions in the United States. Report. Rand Corp. https://www.rand.org/content/dam/rand/pubs/tools/TL200/TL221/RAND_TL221.pdf
[10]
Justine Cassell, Hannes Högni Vilhjálmsson, and Timothy Bickmore. 2001. Beat: the behavior expression animation toolkit. In SIGGRAPH. ACM.
[11]
Susan Colilla, Ann Crow, William Petkun, Daniel E Singer, Teresa Simon, and Xianchen Liu. 2013. Estimates of current and future incidence and prevalence of atrial fibrillation in the US adult population. The American journal of cardiology 112, 8 (2013), 1142–1147.
[12]
Lien Desteghe, Kiki Kluts, Johan Vijgen, Pieter Koopman, Dagmara Dilling-Boer, Joris Schurmans, Paul Dendale, Hein Heidbuchel, 2017. The health buddies app as a novel tool to improve adherence and knowledge in atrial fibrillation patients: a pilot study. JMIR mHealth and uHealth 5, 7 (2017), e7420.
[13]
Eric Ding, Dongqi Liu, Apurv Soni, Oluwaseun Adaramola, Dong Han, Syed Khairul Bashar, Yeonsik Noh, Ki H Chon, and David D McManus. 2017. Impressions of older patients with cardiovascular diseases to smart devices for heart rhythm monitoring. In 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE, 270–271.
[14]
Eric Y Ding, Gregory M Marcus, and David D McManus. 2020. Emerging technologies for identifying atrial fibrillation. Circulation research 127, 1 (2020), 128–142.
[15]
Stacie B Dusetzina, Robert J Besaw, Christine C Whitmore, T Joseph Mattingly, Anna D Sinaiko, Nancy L Keating, and Jordan Everson. 2023. Cost-related medication nonadherence and desire for medication cost information among adults aged 65 years and older in the US in 2022. JAMA Network Open 6, 5 (2023), e2314211–e2314211.
[16]
Ashley C Griffin, Zhaopeng Xing, Saif Khairat, Yue Wang, Stacy Bailey, Jaime Arguello, and Arlene E Chung. 2020. Conversational agents for chronic disease self-management: a systematic review. In AMIA Annual Symposium Proceedings, Vol. 2020. American Medical Informatics Association, 504.
[17]
Martine WJ Huygens, Ilse CS Swinkels, Judith D de Jong, Monique JWM Heijmans, Roland D Friele, Onno CP van Schayck, and Luc P de Witte. 2017. Self-monitoring of health data by patients with a chronic disease: does disease controllability matter?BMC family practice 18 (2017), 1–10.
[18]
Razan Jaber and Donald McMillan. 2020. Conversational user interfaces on mobile devices: Survey. In Proceedings of the 2nd Conference on Conversational User Interfaces. 1–11.
[19]
Zhili Jiang, Xiting Huang, Zhiqian Wang, Yang Liu, Lihua Huang, and Xiaolin Luo. 2024. Embodied Conversational Agents for Chronic Diseases: Scoping Review. Journal of Medical Internet Research 26 (2024), e47134.
[20]
Sin-Hwa Kang, Andrew W Feng, Anton Leuski, Dan Casas, and Ari Shapiro. 2015. The effect of an animated virtual character on mobile chat interactions. In Proceedings of the 3rd International Conference on Human-Agent Interaction. 105–112.
[21]
Saskia M Kelders, Julia EWC Van Gemert-Pijnen, Andrea Werkman, Nicol Nijland, and Erwin R Seydel. 2011. Effectiveness of a Web-based intervention aimed at healthy dietary and physical activity behavior: a randomized controlled trial about users and usage. Journal of medical Internet research 13, 2 (2011), e1624.
[22]
Leonie FM Kohl, Rik Crutzen, and Nanne K de Vries. 2013. Online prevention aimed at lifestyle behaviors: a systematic review of reviews. Journal of medical Internet research 15, 7 (2013), e146.
[23]
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.
[24]
Dennis H Lau, Stanley Nattel, Jonathan M Kalman, and Prashanthan Sanders. 2017. Modifiable risk factors and atrial fibrillation. Circulation 136, 6 (2017), 583–596.
[25]
Lena Mamykina, Elizabeth M Heitkemper, Arlene M Smaldone, Rita Kukafka, Heather Cole-Lewis, Patricia G Davidson, Elizabeth D Mynatt, Jonathan N Tobin, Andrea Cassells, Carrie Goodman, 2016. Structured scaffolding for reflection and problem solving in diabetes self-management: qualitative study of mobile diabetes detective. Journal of the American Medical Informatics Association 23, 1 (2016), 129–136.
[26]
Juan Martínez-Miranda, Ariadna Martínez, Roberto Ramos, Héctor Aguilar, Liliana Jiménez, Hodwar Arias, Giovanni Rosales, and Elizabeth Valencia. 2019. Assessment of users’ acceptability of a mobile-based embodied conversational agent for the prevention and detection of suicidal behaviour. Journal of medical systems 43, 8 (2019), 246.
[27]
Graeme Mattison, Oliver Canfell, Doug Forrester, Chelsea Dobbins, Daniel Smith, Juha Töyräs, and Clair Sullivan. 2022. The influence of wearables on health care outcomes in chronic disease: systematic review. Journal of Medical Internet Research 24, 7 (2022), e36690.
[28]
Adam S Miner, Liliana Laranjo, and A Baki Kocaballi. 2020. Chatbots in the fight against the COVID-19 pandemic. NPJ digital medicine 3, 1 (2020), 65.
[29]
Vasileios Nittas, Chiara Zecca, Christian P Kamm, Jens Kuhle, Andrew Chan, and Viktor von Wyl. 2023. Digital health for chronic disease management: An exploratory method to investigating technology adoption potential. Plos one 18, 4 (2023), e0284477.
[30]
S Olafsson, D Parmar, E Kimani, T O’Leary, and T Bickmore. 2021. ‘More like a person than reading text in a machine’: Predicting Choice of Embodied Agents over Conventional GUIs on Smartphones. In CHI.
[31]
Rian Adi Pamungkas, Andi Mayasari Usman, Kanittha Chamroonsawasdi, 2022. A smartphone application of diabetes coaching intervention to prevent the onset of complications and to improve diabetes self-management: A randomized control trial. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 16, 7 (2022), 102537.
[32]
Dominique A Reinwand, Rik Crutzen, Iman Elfeddali, Francine Schneider, Daniela Nadine Schulz, Eline Suzanne Smit, Nicola Esther Stanczyk, Huibert Tange, Viola Voncken-Brewster, Michel Jean Louis Walthouwer, 2015. Impact of educational level on study attrition and evaluation of web-based computer-tailored interventions: results from seven randomized controlled trials. Journal of medical Internet research 17, 10 (2015), e228.
[33]
Dominique A Reinwand, Daniela N Schulz, Rik Crutzen, Stef PJ Kremers, and Hein de Vries. 2015. Who follows eHealth interventions as recommended? A study of participants’ personal characteristics from the experimental arm of a randomized controlled trial. Journal of medical Internet research 17, 5 (2015), e3932.
[34]
Theresa Schachner, Roman Keller, and Florian v Wangenheim. 2020. Artificial intelligence-based conversational agents for chronic conditions: systematic literature review. Journal of medical Internet research 22, 9 (2020), e20701.
[35]
John Spertus, Paul Dorian, Rosemary Bubien, Steve Lewis, Donna Godejohn, Matthew R Reynolds, Dhanunjaya R Lakkireddy, Alan P Wimmer, Anil Bhandari, and Caroline Burk. 2011. Development and validation of the Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) Questionnaire in patients with atrial fibrillation. Circulation: Arrhythmia and Electrophysiology 4, 1 (2011), 15–25.
[36]
Stavros Stavrakis, Julie A Stoner, Joel Kardokus, Paul J Garabelli, Sunny S Po, and Ralph Lazzara. 2017. Intermittent vs. Continuous Anticoagulation theRapy in patiEnts with Atrial Fibrillation (iCARE-AF): a randomized pilot study. Journal of Interventional Cardiac Electrophysiology 48 (2017), 51–60.
[37]
Megan Streur. 2019. Atrial fibrillation symptom perception. The Journal for Nurse Practitioners 15, 1 (2019), 60–64.
[38]
R Trivedi, T Shaw, CK Chow, and L Laranjo. 2023. Conversational artificial intelligence intervention to support patients with atrial fibrillation: process evaluation of a randomised controlled trial. European Heart Journal 44, Supplement_2 (2023), ehad655–2995.
[39]
Isaac Vaghefi, Bengisu Tulu, 2019. The continued use of mobile health apps: insights from a longitudinal study. JMIR mHealth and uHealth 7, 8 (2019), e12983.
[40]
Celien Van der Mispel, Louise Poppe, Geert Crombez, Maïté Verloigne, and Ilse De Bourdeaudhuij. 2017. A self-regulation-based eHealth intervention to promote a healthy lifestyle: investigating user and website characteristics related to attrition. Journal of medical Internet research 19, 7 (2017), e241.
[41]
Sudip Vhaduri and Temiloluwa Prioleau. 2020. Adherence to personal health devices: A case study in diabetes management. In Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare. 62–72.
[42]
Barry D Weiss, Mary Z Mays, William Martz, Kelley Merriam Castro, Darren A DeWalt, Michael P Pignone, Joy Mockbee, and Frank A Hale. 2005. Quick assessment of literacy in primary care: the newest vital sign. The Annals of Family Medicine 3, 6 (2005), 514–522.
[43]
Anna Weston, Leanne Morrison, Lucy Yardley, Max Van Kleek, and Mark Weal. 2015. Measurements of engagement in mobile behavioural interventions? (2015).
[44]
Lucy Yardley, Bonnie J Spring, Heleen Riper, Leanne G Morrison, David H Crane, Kristina Curtis, Gina C Merchant, Felix Naughton, and Ann Blandford. 2016. Understanding and promoting effective engagement with digital behavior change interventions. American journal of preventive medicine 51, 5 (2016), 833–842.

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      cover image ACM Conferences
      IVA '24: Proceedings of the 24th ACM International Conference on Intelligent Virtual Agents
      September 2024
      337 pages
      This work is licensed under a Creative Commons Attribution International 4.0 License.

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      Published: 26 December 2024

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      1. Mobile Applications
      2. Virtual Agents

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      • U.S. National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI)

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      IVA '24
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      IVA '24: ACM International Conference on Intelligent Virtual Agents
      September 16 - 19, 2024
      GLASGOW, United Kingdom

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