Using Health Chatbots for Behavior Change: A Mapping Study

Pereira, Juanan; Díaz, Óscar

doi:10.1007/s10916-019-1237-1

Cited by 165 publications

(100 citation statements)

References 43 publications

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“…Chatbots for promoting physical activity and a healthy diet are designed to achieve behavior change goals, such as walking for certain times and/or distances and following healthy meal plans [ 25 - 29 ]. Although no systematic review of chatbots for lifestyle modification programs has been published, there are several reviews on chatbots covering health care issues ranging from mental health support and smoking cessation to disease diagnosis [ 16 , 30 ]. Owing to the different natures of targeted behaviors, some chatbots were mainly designed to provide information and knowledge [ 31 ], whereas others were developed based on established mental health intervention programs such as cognitive behavioral therapy [ 32 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

212

116

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Background Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. Objective The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdisciplinary research, and discuss ethical principles and considerations. Methods We conducted a preliminary search of studies reporting chatbots for improving physical activity and/or diet in four databases in July 2020. We summarized the characteristics of the chatbot studies and reviewed recent developments in human-AI communication research and innovations in natural language processing. Based on the identified gaps and opportunities, as well as our own clinical and research experience and findings, we propose an AI chatbot behavior change model. Results Our review found a lack of understanding around theoretical guidance and practical recommendations on designing AI chatbots for lifestyle modification programs. The proposed AI chatbot behavior change model consists of the following four components to provide such guidance: (1) designing chatbot characteristics and understanding user background; (2) building relational capacity; (3) building persuasive conversational capacity; and (4) evaluating mechanisms and outcomes. The rationale and evidence supporting the design and evaluation choices for this model are presented in this paper. Conclusions As AI chatbots become increasingly integrated into various digital communications, our proposed theoretical framework is the first step to conceptualize the scope of utilization in health behavior change domains and to synthesize all possible dimensions of chatbot features to inform intervention design and evaluation. There is a need for more interdisciplinary work to continue developing AI techniques to improve a chatbot’s relational and persuasive capacities to change physical activity and diet behaviors with strong ethical principles.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

212

116

View full text Add to dashboard Cite

show abstract

“…A "chatbot" is de ned as an "arti cial intelligence program designed to simulate human conversation via text or speech", as opposed to the current owchart model [20][21]. The use of chatbots has seen a growing development and usage within the medical literature [21][22], with successful application for recording key symptoms [23][24][25][26].…”

Section: Development Of a Chatbot As An Addition To The Copenhagen Emmentioning

confidence: 99%

Strategies to Handle Increased Demand in the COVID-19 Crisis a Corona Telephone Hotline and a Web-based Self-triage System

Jensen¹,

Holgersen

Jespersen

et al. 2020

Preprint

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BackgroundIn emergencies, such as the COVID-19 pandemic, there is an increased need for contact withemergency medical services (EMS), and call volume might surpass capacity. Thus, the Copenhagen EMS in Denmark implemented a separate coronavirus hotline followed by a web-based self-triage system to reduce nonemergency call volume. The aim of this paper is to present the two measures implemented to handle the increased call volume to the Copenhagen EMSfromthose with mild or no relevant COVID-19 symptoms.MethodsThis is a cross sectional observational study monitoring call volume in the first month of the COVID-19 pandemic in accumulated callnumbers, compared to the equivalent numbers during one month from the year before (2019). A coronavirus hotline and web-based self-triage system arepresented in absolute numbers of users.ResultsIn the first month of the COVID-19 pandemic in Copenhagen, emergency medical dispatch centers were extensively overloaded with more than 10.800 calls, resulting in significantly prolonged queue time (mean time in minutes:12:02; CI: 11:55-12:09)) compared to 2019 (mean time in minutes02:23; CI: 02:22-02:25) and thereby limiting access to emergency assistance and triage for citizens. The introduction of the coronavirus hotline showed reduced call volume and queue time to the EMS. The web-based self-triage system was used more than 107.000 times. However, no correlation between call volume and the use of a web-based self-triage systemwas observed.ConclusionsCreating a coronavirus hotlinestaffed by healthcare personnelseemed to have an impact on call volume and potentially relieved the strain in resources, while the web-based self-triage system was widely used and could be further developed to reach itsfull potential. Other EMS organizations can implement these measures to enhance capacity in a future epidemic.

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“…A chatbot could be de ned as a social AI that has been designed to carry out conversations with humans using NLP [9,56]. The exibility this creates has led to chatbots being used in various elds [2,48], for instance in customer service [6] (e.g., ChatBot, chatbot.com), libraries [32] (e.g., Pixel, pixel.unl.edu), and health care [42] (e.g., MedWhat, medwhat.com). Chatbots can be used for various purposes, such as helping users to nd information, supporting collaboration between users, and automating parts of a work ow that are repetitive [40].…”

Section: Chatbotsmentioning

confidence: 99%

Artificial Intelligence in Conversational Agents

Svenningsson

Faraon

2019

Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference

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Arti cial intelligence (AI) is gaining traction in service-oriented businesses in the form of chatbots. A chatbot is a popular type of social AI that uses natural language processing to communicate with users. Past studies have shown discrepancies in terms of whether or not a chatbot should communicate and behave like a human. This article aims to explore these discrepancies in order to provide a theoretical contribution of a list of factors related to perceived humanness in chatbots and how these may consequently lead to a positive user experience. The results suggest that a chatbot should have the following characteristics: avoiding small talk and maintaining a formal tone; identifying itself as a bot and asking how it can help; providing speci c information and articulating itself with sophisticated choices of words and well-constructed sentences; asking follow-up questions during decision-making processes and; providing an apology when the context is not comprehensible, followed by a question or a statement to dynamically move a conversation forward. These results may have implications for designers working in the eld of AI as well as for the wider debates and the broader discourse around the adoption of AI in society. CCS CONCEPTS • Human-centered computing → Interaction design → Interaction design theory, concepts and paradigms • Computing methodologies → Artificial intelligence → Intelligent agents; Discourse, dialogue and pragmatics

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Using Health Chatbots for Behavior Change: A Mapping Study

Cited by 165 publications

References 43 publications

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Strategies to Handle Increased Demand in the COVID-19 Crisis a Corona Telephone Hotline and a Web-based Self-triage System

Artificial Intelligence in Conversational Agents

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