Abstract
In the last decade, there has been a rapid widespread of applications that support different types of patients in self-managing some aspects concerning their health (e.g., drugs assumption) and reporting specific relevant events (e.g., symptoms) daily. Furthermore, these apps turn out to be very important for patients in social isolation and lockdown due to pandemics in which direct contact with their physicians may be hampered and not frequent. Despite the importance of such applications, patients often cease to use them for several reasons increasing the drop-out rate of clinical research. The current paper describes PatchAi, an end-to-end patient engagement solution. The mobile health solution of PatchAi has been designed and developed following a user-centric perspective, intended to support patients and doctors, reduce drop-out rates, while improving patient adherence to protocols and care schedules in clinical trials.
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References
Bahia, L.R., et al.: The costs of type 2 diabetes mellitus outpatient care in the Brazilian public health system. Value Health 14, S137e40 (2011). https://doi.org/10.1016/j.jval.2011.05.009
World Health Organization: The World Health Report 2003: reducing risks promoting healthy life. World Health Organization, Geneva (2002)
de Oliveira, S.F.D., de Duarte, Y.A.O., Lebrão, M.L., Laurenti, R.: Demanda referida e auxÃlio recebido por idosos com declÃnio cognitivo no municÃpio de São Paulo. Saúde e Sociedade 16, 81e9 (2007). https://doi.org/10.1590/S0104-12902007000100008
Oliveira, L.S., Rabelo, D.F., Caires Queroz, N.: Life style, perceived control and quality of life: a study with the aged population of Patos de Minas-MG. Estudos e Pesquisas em Psicologia 12, 416e30 (2012)
Nahar, P., Kannuri, N.K., Mikkilineni, S., Murthy, G.V.S., Phillimore, P.: mHealth and the management of chronic conditions in rural areas: a note of caution from southern India. Anthropol. Med. 24, 1e16 (2017). https://doi.org/10.1080/13648470.2016.1263824
Isakovic, M., Sedlar, U., Volk, M., Bester, J.: Usability pitfalls of diabetes mHealth apps for the elderly. J. Diabetes Res. 2016, 1604609 (2016). https://doi.org/10.1155/2016/1604609
Slater, H., Campbell, J.M., Stinson, J.N., Burley, M.M., Briggs, A.M.: End user and implementer experiences of mHealth technologies for noncommunicable chronic disease management in young adults: systematic review. J. Med. Internet Res. 19, e406 (2017). https://doi.org/10.2196/jmir.8888
Quaosar, G.M.A.A., Hoque, M.R., Bao, Y.: Investigating factors affecting elderly’s intention to use m-health services: an empirical study. Telemed. J. e Health 24, 309e14 (2018). https://doi.org/10.1089/tmj.2017.0111
Eagleson, R., et al.: Implementation of clinical research trials using web-based and mobile devices: challenges and solutions. BMC Med. Res. Methodol. 17, 43 (2017). https://doi.org/10.1186/s12874-017-0324-6
Chen, J., Bauman, A., Allman-Farinelli, M.: A study to determine the most popular lifestyle smartphone applications and willingness of the public to share their personal data for health research. Telemed. J. e Health 22, 655e65 (2016). https://doi.org/10.1089/tmj.2015.0159
Bellei, E.A., Biduski, D., Cechetti, N.P., De Marchi, A.C.B.: Diabetes mellitus m-health applications: a systematic review of features and fundamentals. Telemed. J. e Health 24, 839e52 (2018). https://doi.org/10.1089/tmj.2017.0230
Sudhir, P.M.: Advances in psychological interventions for lifestyle disorders. Curr. Opin. Psychiatr. 30, 346e51 (2017). https://doi.org/10.1097/YCO.0000000000000348
Bashshur, R.L., Shannon, G., Krupinski, E.A., Grigsby, J.: Sustaining and realizing the promise of telemedicine. Telemed. J. E Health 19(5), 339–345 (2013). https://doi.org/10.1089/tmj.2012.0282. [Medline: 23289907]
Granja, C., Janssen, W., Johansen, M.A.: Factors determining the success and failure of eHealth interventions: systematic review of the literature. J. Med. Internet Res. 20(5), e10235 (2018)
Neville, R., Greene, A., McLeod, J., Tracey, A., Tracy, A., Surie, J.: Mobile phone text messaging can help young people manage asthma. Br. Med. J. 325(7364), 600 (2002). https://doi.org/10.1136/bmj.325.7364.600/a. [Medline: 12228151]
Hall, A.K., Cole-Lewis, H., Bernhardt, J.M.: Mobile text messaging for health: a systematic review of reviews. Ann. Rev. Public Health 36, 393–415 (2015). https://doi.org/10.1146/annurev-publhealth-031914-122855. [Medline: 25785892]
Rathbone, A.L., Prescott, J.: The use of mobile apps and SMS messaging as physical and mental health interventions: systematic review. J. Med. Internet Res. 19(8), e295 (2017). https://doi.org/10.2196/jmir.7740. [Medline: 28838887]
Car, L.T., et al.: Conversational agents in health care: scoping review and conceptual analysis. J. Med. Internet Res. 22(8), e17158 (2020)
Hoermann, S., McCabe, K.L., Milne, D.N., Calvo, R.A.: Application of synchronous text-based dialogue systems in mental health interventions: systematic review. J. Med. Internet Res. 19(8), e267 (2017). https://doi.org/10.2196/jmir.7023. [Medline: 28784594]
Tropea, P., et al.: Rehabilitation, the great absentee of virtual coaching in medical care: scoping review. J. Med. Internet Res. 21(10), e12805 (2019). https://doi.org/10.2196/12805. [Medline: 31573902]
Provoost, S., Lau, H.M., Ruwaard, J., Riper, H.: Embodied conversational agents in clinical psychology: a scoping review. J. Med. Internet Res. 19(5), e151 (2017). https://doi.org/10.2196/jmir.6553. [Medline: 28487267]
Pereira, J., DÃaz, O.: Using health chatbots for behavior change: a mapping study. J. Med. Syst. 43(5), 135 (2019). https://doi.org/10.1007/s10916-019-1237-1. [Medline: 30949846]
Xing, Z., et al.: Conversational interfaces for health: bibliometric analysis of grants, publications, and patents. J. Med. Internet Res. 21(11), e14672 (2019). https://doi.org/10.2196/14672. [Medline: 31738171]
Følstad, A., Brandtzæg, P.B.: Chatbots and the new world of HCI. Interactions 24(4), 38–42 (2017)
Grosz, A.J., et al.: Artificial Intelligence and Life in 2030: One Hundred Year Study on Artificial Intelligence. Stanford University (2016)
Radziwill, N.M., Benton, M.C.: Evaluating Quality of Chatbots and Intelligent Conversational Agents, April 2017
Wolters, M.K., Kelly, F., Kilgour, J.: Designing a spoken dialogue interface to an intelligent cognitive assistant for people with dementia. Health Inform. J. 22(4), 854–866 (2016)
Bickmore, T.W., Schulman, D., Sidner, C.: Automated interventions for multiple health behaviors using conversational agents. Patient Educ. Couns. 92(2), 142–148 (2013)
Denecke, K., Tschanz, M., Dorner, T., May, R.: Intelligent conversational agents in healthcare: hype or hope? Stud. Health Technol. Inform. 259, 77–84 (2019)
Barak, A., Klein, B., Proudfoot, J.G.: Defining internet-supported therapeutic interventions. Ann. Behav. Med. 38(1), 4–17 (2009). https://doi.org/10.1007/s12160-009-9130-7. ID: Barak2009
Goldstein, I.M., Lawrence, J., Miner, A.S.: Human-machine collaboration in cancer and beyond: the centaur care model. JAMA Oncol. 3, 1303–1304 (2017)
Cameron, G., et al.: Towards a Chatbot for digital counselling. In: Proceedings of the 31st British Computer Society Human Computer Interaction Conference (HCI 2017). BCS Learning & Development Ltd., Swindon, UK, pp. 24:1–24:7 (2017). https://doi.org/10.14236/ewic/HCI2017.24
Kumar, V.M., Keerthana, A., Madhumitha, M., Valliammai, S. Vinithasri, V.:Sanative Chatbot For Health Seekers (2016)
Lokman, A.S., Zain, J.M., Komputer, F.S., Perisian, K.: Designing a Chatbot for diabetic patients (2009)
Comendador, B.E.V., Francisco, B.M.B., Medenilla, J.S., Mae, S.: Pharmabot: a pediatric generic medicine consultant chatbot. J. Autom. Control Eng. 3(2) (2015)
Ilić, D.T., Marković, B.: Possibilities, Limitations and economic aspects of artificial intelligence applications in healthcare. Ecoforum J. 5(1) (2016)
Bibault, J.E., Chaix, B., Nectoux, P., Pienkowski, A., Guillemasé, A., Brouard, B.: Healthcare ex Machina: are conversational agents ready for prime time in oncology? Clin. Transl. Radiat. Oncol. 16, 55–59 (2019)
Aha, D.W., Breslow, L.A., Muñoz-Avila, H.: Conversational case-based reasoning. J. Appl. Intell. 14(1), 9–32 (2001). https://doi.org/10.1023/a:1008346807097
Thompson, C.A., Goker, M.H., Langley, P.: A personalized system for conversational recommendations. J. Artif. Intell. Res. 21, 393–428 (2004). https://doi.org/10.1613/jair.1318
Rich, E.: User modeling via stereotypes. In: Maybury, M.T., Wahlster, W. (eds.) Readings in Intelligent User Interfaces, pp. 329–342. Morgan Kaufmann Publishers Inc., San Francisco (1998)
Chen, L., Pu, P.: Critiquing-based recommenders: survey and emerging trends. User Model. User-Adap. Inter. 22(1–2), 125–150 (2012). https://doi.org/10.1007/s11257-011-9108-6
Kim, Y., Bang, J., Choi, J., Ryu, S., Koo, S., Lee, G.G.: Acquisition and Use of Long-Term Memory for Personalized Dialog Systems. In: Böck, R., Bonin, F., Campbell, N., Poppe, R. (eds.) Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction. MA3HMI 2014. LNCS, vol. 8757, pp. 78–87. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-15557-9_8
Levin, E., Levin, A.: Evaluation of spoken dialogue technology for real-time health data collection. J. Med. Internet Res. 8(4), e30 (2006). https://doi.org/10.2196/jmir.8.4.e30. [Medline: 17213048]
Kocaballi, A.B., et al. The personalization of conversational agents in health care: systematic review. J. Med. Internet Res. 21(11), e15360 (2019). https://doi.org/10.2196/15360. [Medline: 31697237]
Pargellis, A., Kuo, H., Lee, C.: An automatic dialogue generation platform for personalized dialogue applications. Speech Commun. 42(3–4), 329–351 (2004). https://doi.org/10.1016/j.specom.2003.10.003
Litman, D.J., Pan, S.: Designing and evaluating an adaptive spoken dialogue system. User Model. User-Adap. Inter. 2–3, 111–137 (2002). https://doi.org/10.1023/A:1015036910358
Sharp, H., Rogers, Y., Preece, J.: Interaction Design: Beyond Human-Computer Interaction, 5th edn. Wiley (2019)
Alahäivälä, T., Oinas-Kukkonen, H.: Understanding persuasion contexts in health gamification: a systematic analysis of gamified health behavior change support systems literature. Int. J. Med. Inform. 96, 62–70 (2016)
Sardi, L., Idri, A., Fernández-Alemán, J.L.: A systematic review of gamification in e-Health. J. Biomed. Inform. 71, 31–48 (2017)
Baumeister, H., Kraft, R., Baumel, A., Pryss, R., Messner, E.-M.: Persuasive e-health design for behavior change. In: Baumeister, H., Montag, C. (eds.) Digital Phenotyping and Mobile Sensing. SNPBE, pp. 261–276. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-31620-4_17
Abd-Alrazaq, A., Safi, Z., Alajlani, M., Warren, J., Househ, M., Denecke, K.: Technical metrics used to evaluate health care chatbots: scoping review. J. Med. Internet Res. 22(6), e18301 (2020)
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Gamberini, L. et al. (2021). PatchAi: An e-Health Application Powered by an AI Virtual Assistant to Support Patients in Their Clinical Trials. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1421. Springer, Cham. https://doi.org/10.1007/978-3-030-78645-8_39
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