The evolving field of persuasive and behavior change technology is increasingly targeted at influencing behavior in the area of health and wellness. This paper provides an empirical review of 16 years (85 papers) of literature on persuasive technology for health and wellness to: (1.) answer important questions regarding the effectiveness of persuasive technology for health and wellness, (2.) summarize and highlight trends in the technology design, research methods, motivational strategies, theories, and health behaviors targeted by research to date, (3.) uncover pitfalls of existing persuasive technological interventions for health and wellness, and (4.) suggest directions for future research.

https://journals.sagepub.com/doi/pdf/10.1177/1460458216650979

Persuasive technology for health and wellness: State-of-the-art and emerging trends.

This paper reviews the current body of empirical research on persuasive technologies 95 studies. In recent years, technology has been increasingly harnessed to persuade and motivate people to engage in various behaviors. This phenomenon has also attracted substantial scholarly interest over the last decade. This review examines the results, methods, measured behavioral and psychological outcomes, affordances in implemented persuasive systems, and domains of the studies in the current body of research on persuasive technologies. The reviewed studies have investigated diverse persuasive systems/designs, psychological factors, and behavioral outcomes. The results of the reviewed studies were categorized into fully positive, partially positive, and negative and/or no effects. This review provides an overview of the state of empirical research regarding persuasive technologies. The paper functions as a reference in positioning future research within the research stream of persuasive technologies in terms of the domain, the persuasive stimuli and the psychological and behavioral outcomes.

Do Persuasive Technologies Persuade? - A Review of Empirical Studies

This paper discusses how persuasive technologies can be made adaptive to users. We present persuasion profiling as a method to personalize the persuasive messages used by a system to influence its users. This type of personalization can be based on explicit measures of users? tendencies to comply to distinct persuasive strategies: measures based on standardized questionnaire scores of users. However, persuasion profiling can also be implemented using implicit, behavioral measures of user traits. We present three case studies involving the design, implementation, and field deployment of personalized persuasive technologies, and we detail four design requirements. In each case study we show how these design requirements are implemented. In the discussion we highlight avenues for future research in the field of adaptive persuasive technologies. Author-HighlightsPersuasive technologies can be more effective if they are personalized.We introduce persuasion profiles to personalize persuasive messages.Persuasion profiles can be effective using implicit or explicit measures.In three case studies we show the effects of personalized persuasion.

https://pure.tue.nl/ws/files/3994499/888440058546432.pdf

Personalizing persuasive technologies

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.

/pdf/artificial-intelligence-chatbot-behavior-change-model-for-3zdot98r6t.pdf

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

Persuasive technology (PT) is increasingly being used in the health and wellness domain to motivate and assist users with different lifestyles and behavioral health issues to change their attitudes and/or behaviors. There is growing evidence that PT can be effective at promoting behaviors in many health and wellness domains, including promoting physical activity (PA), healthy eating, and reducing sedentary behavior (SB). SB has been shown to pose a risk to overall health. Thus, reducing SB and increasing PA have been the focus of much PT work. This paper aims to provide a systematic review of PTs for promoting PA and reducing SB. Specifically, we answer some fundamental questions regarding its design and effectiveness based on an empirical review of the literature on PTs for promoting PA and discouraging SB, from 2003 to 2019 (170 papers). There are three main objectives: (1) to evaluate the effectiveness of PT in promoting PA and reducing SB; (2) to summarize and highlight trends in the outcomes such as system design, research methods, persuasive strategies employed and their implementaions, behavioral theories, and employed technological platforms; (3) to reveal the pitfalls and gaps in the present literature that can be leveraged and used to inform future research on designing PT for PA and SB.

/pdf/trends-in-persuasive-technologies-for-physical-activity-and-4irbvx5eq7.pdf

Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review.

Can ubiquitous technologies intended to change people's behavior benefit from personalization? This paper addresses the development of an adaptive persuasive system intended to increase stair climbing at work: APStairs Based on their persuasion profile, individuals are distinguished by their susceptibility to different social influence strategies This paper contributes a first application of persuasion profiling in the domain of ambient intelligence; it reports the deployment of the APStairs system in a real life setting for a period of five weeks involving 34 participants Although a longer deployment period is needed to statistically validate the system, this first deployment of the system has shown the feasibility of adaptive persuasion

Personalized persuasion in ambient intelligence: the APStairs system

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Personalized persuasion in ambient intelligence: the APStairs system