Behaviour Change Support Systems (BCSS), already running for the 10th time at Persuasive Technology, is a workshop that builds around the concept of systems that are specifically designed to help and support behaviour change in individuals or groups. The highly multi-disciplinary nature of designing and implementing behaviour change strategies and systems for the strategies has been in the forefront of this workshop from the very beginning. The persuasive technology field is becoming a linking pin connecting natural and social sciences, requiring a holistic view on persuasive technologies, as well as multi-disciplinary approach for design, implementation, and evaluation. So far, the capacities of technologies to change behaviours and to continuously monitor the progress and effects of interventions are not being used to its full potential. The use of technologies as persuaders may shed a new light on the interaction process of persuasion, influencing attitudes and behaviours. Yet, although human- computer interaction is social in nature and people often do see computers as social actors, it is still unknown how these interactions re-shape attitude, beliefs, and emotions, or how they change behaviour, and what the drawbacks are for persuasion via technologies. Humans re-shape technology, changing their goals during usage. This means that persuasion is not a static ad hoc event but an ongoing process. Technology has the capacity to create smart (virtual) persuasive environments that provide simultaneously multimodal cues and psycho-physiological feedback for personal change by strengthening emotional, social, and physical presence. An array of persuasive applications has been developed over the past decade with an aim to induce desirable behaviour change. Persuasive applications have shown promising results in motivating and supporting people to change or adopt new behaviours and attitudes in various domains such as health and wellbeing, sustainable energy, education, and marketing. This workshop aims at connecting multidisciplinary researchers, practitioners and experts from a variety of scientific domains, such as information sciences, human-computer interaction, industrial design, psychology and medicine. This interactive workshop will act as a forum where experts from multiple disciplines can present their work, and can discuss and debate the pillars for persuasive technology.
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Despite increased interest in applying psychological theory to the practice of designing behavioral change interventions, design professionals often lack adequate knowledge and resources to do so. In this paper, we present a tool to help professionals in the creative industries design evidence-based health interventions, the Persuasive by Design model. This paper describes the contents and application of the model as well as plans for further development and testing.
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The development of eHealth applications requires a new methodological approach, departing from the more conventional methods dedicated to designing health information systems. There is a gap between theories to design persuasive eHealth applications and practices. We consequently advocate an integrated, systematic and practical but scientifically based methodology to design effective persuasive eHealth applications. This approach is being successfully embedded in our educational health informatics program.
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Recently, there has been an increase in interest for the integration of insights from the behavioural sciences into the design process. The Persuasive by Design model aims to provide an evidence-based framework by which designers gain access to relevant theoretical insights from the behavioural sciences. This paper examines the use of the model in two case studies that dealt with complex behavioural change situations. In both studies, the model proved to be a valuable aid in determining target behaviours and operationalizing intervention concepts, especially in the early stages of the design process. Some shortcomings of the model also transpired. The model was seen as too complex, and its psychological frame does not prevent designers to overlook possible systemic moderators of behaviour. Implications for further development of tools that give access to model insights are discussed.
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Games are designed with different objectives in mind. Some primarily for entertainment, others also to educate, motivate or persuade its players. Games with the latter objective, that of persuasion, are designed not only to be entertaining, but also with the intent to shape how players think and feel about issues in reality. However, despite the growing interest in persuasive games, we still lack the design insights and strategies that support their production, particularly for those using immersive technologies. To address this gap, we organize a hands-on workshop and bring together academic and industry experts to explore persuasive game design. Through making we generate knowledge in the form of insights and examplar work, and subsequently formulate best-practises and design strategies for future design and research.
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Background:It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions—not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention.Objective:This scoping review sets out to explore the different technical implementations and design characteristics of common and likely most effective persuasive strategies, namely, goal setting, monitoring, reminders, rewards, sharing, and social comparison. Furthermore, this review aims to explore whether previous mHealth studies examined the influence of the different design characteristics and technical operationalizations of common persuasive strategies on the effectiveness of the intervention to persuade the user to engage in PA.Methods:An unsystematic snowball and gray literature search was performed to identify the literature that evaluated the persuasive strategies in experimental trials (eg, randomized controlled trial, pre-post test). Studies were included if they targeted adults, if they were (partly) delivered by a mobile system, if they reported PA outcomes, if they used an experimental trial, and when they specifically compared the effect of different designs or implementations of persuasive strategies. The study methods, implementations, and designs of persuasive strategies, and the study results were systematically extracted from the literature by the reviewers.Results:A total of 29 experimental trials were identified. We found a heterogeneity in how the strategies are being implemented and designed. Moreover, the findings indicated that the implementation and design of the strategy has an influence on the effectiveness of the PA intervention. For instance, the effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken. Furthermore, studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals. This study further demonstrates that only a few studies have examined the influence of different technical implementations on PA behavior.Conclusions:The different implementations and designs of persuasive strategies in mHealth interventions should be critically considered when developing such interventions and before drawing conclusions on the effectiveness of the strategy as a whole. Future efforts are needed to examine which implementations and designs are most effective to improve the translation of theory-based persuasive strategies into practical delivery forms.
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Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing. Objective: First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field. Methods: A scoping review was conducted based on the framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given. Results: In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages. Conclusions: The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.
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Obesity has become a major societal problem worldwide [1][2]. The main reason for severe overweight is excessive intake of energy, in relation to the individual needs of a human body. Obesity is associated with poor eating habits and/or a sedentary lifestyle. A significant part of the obese population (40%) belongs to a vulnerable target group of emotional eaters, who overeat due to negative emotions [3]. There is a need for self-management support and personalized coaching to enhance emotional eaters in recognising and self-regulating their emotions.Over the last years, coaching systems have been developed for behavior change support, healthy lifestyle, and physical activity support [4]-[9]. Existing virtual coach applications lack systematic evaluation of coaching strategies and usually function as (tele-)monitoring systems. They are limited to giving general feedback to the user on achieved goals and/or accomplished (online) assignments.Dialectical Behavior Therapy (DBT) focuses on getting more control over one’s ownemotions by reinforcing skills in mindfulness, emotion regulation, and stress tolerance [10]. Emotion regulation is about recognizing and acknowledging emotions and accepting the fact that they come and go. The behavior change strategies within DBT are based on validation and dialectics [11]. Dialectics changes the users’ attitude and behavior by creating incongruence between an attitude and behavior since stimuli or the given information contradict with each other.The ultimate goal of the virtual coach is to raise awareness of emotional eaters on their own emotions, and to enhance a positive change of attitude towards accepting the negative emotions they experience. This should result in a decrease of overeating and giving in to binges. We believe that the integration of the dialectical behavior change strategies and persuasive features from the Persuasive System Design Model by Kukkonen and Harjumaa [12] will enhance the personalization of the virtual coach for this vulnerable group. We aim at developing a personalized virtual coach ‘Denk je zèlf!’ (Dutch for ‘Develop a wise mind and counsel yourself’) providing support for self-regulation of emotions for young obese emotional eaters. This poster presents an eCoaching model and a research study protocol aiming at the validation of persuasive coaching strategies based on behavior change techniques using dialectical strategies. Based on the context (e.g., location), emotional state of the user, and natural language processing, the virtual coach application enables tailoring of the real-time feedback to the individual user. Virtual coach application communicates with the user over a chat timeline and provides personal feedback.The research protocol decribes the two weeks field study on validating persuasive coaching strategies for emotional eaters. Participants (N=30), recruited via a Dutch franchise organization of dietitian nutritionists, specialized in treating emotional eating behaviors, will voluntarily participate in this research study. Participants will be presented with short dialogues (existing questions and answers) and will be asked to select the preferred coaching strategy (validating or a dialectical), according to their (current) emotions. To trigger a certain emotion (e.g., the affect that fits best with the chosen coaching strategy), a set of pictures will be shown to the user that evoke respectively sadness, anger, fear, and disgust [13].Participants will be asked to fill out the demographics data ((nick) name, age, gender, weight, length, place of residence) and three questionnaires: • Dutch Eating Behavior Questionnaire (DEBQ) [14],• Five Factor Personality Inventory (FFPI) [15], • Quality of Life Index Questionnaire [16].This research study aims at answering the following research questions: “Which coaching strategies do users with a specific type of emotional eating behavior benefit most from while consulting their personalized virtual coach?; “Which coaching strategies are optimal for which emotions?” and “Which coaching approach do users prefer in which context, e.g. time of the day, before/after a craving?”
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Virtual, Augmented and Mixed Reality technologies are embraced by designers, scholars and charities alike, some primarily for their entertaining properties, others also for the opportunities in education, motivation or persuasion. Applications with the latter objective, that of persuasion, are designed not only to be entertaining, but are also designed (or framed) to shape how players think and feel about issues in reality. However, despite the growing interest in the persuasive opportunities of these immersive technologies, we still lack the design strategies and best-practices that could support in the design of these ‘immersive persuasive games’. To address this still-unexplored and fragmented design space, we organize a design-oriented workshop that brings together academia and industry. The workshop is informed by a Research through Design approach in which the primary focus is to generate knowledge through designing. Participants design and evaluate ideas on-the-spot in an iterative manner using low-fidelity, life-size, prototyping and role-playing techniques, thereby mimicking an embodied interactive immersive environment. By reflecting on design practices and player experiences, we construct a body of knowledge, built exemplar work and distil best-practices to formulate design strategies for the design of immersive persuasive games.
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Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the operationalization of the persuasive strategies could increase the effectiveness of the app, such as the actual content or visualization of feedback. Although much research has been done to examine the preferences for persuasive strategies, little is known about the needs, wishes, and preferences for the design and operationalization of persuasive strategies.Objective: The purpose of this study was to get insight in the needs, wishes, and preferences regarding the practical operationalization of persuasive strategies in a mobile application aimed at promoting PA in healthy inactive adults.Methods: Five semistructured focus groups were performed. During the focus groups, the participants were led into a discussion about the design and operationalization of six predefined theory-based persuasive strategies (e.g., self-monitoring, feedback, goal setting, reminders, rewards, and social support) directed by two moderators. The audio-recorded focus groups were transcribed verbatim and analyzed following the framework approach.Results: Eight men and 17 women between 35 and 55 years (mean age, 49.2) participated in the study. Outcomes demonstrated diverse preferences for implementation types and design characteristics of persuasive strategies in mobile applications. Basic statistics (such as distance, time and calories), positive feedback based on easy-to-achieve goals that relate to health guidelines, and motivating reminders on a relevant moment were preferred. Participants had mixed preferences regarding rewards and a social platform to invite other users to join PA.Conclusions: Findings indicated that in mHealth applications for healthy but inactive adults, persuasive strategies should be designed and implemented in a way that they relate to health guidelines. Moreover, there is a need for an app that can be adapted or can learn based on personal preferences as, for example, preferences with regard to timing of feedback and reminders differed between people.
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