Behavior Change Support Systems Research Articles

Persuasive Systems Design Trends in Coronary Heart Disease Management: Scoping Review of Randomized Controlled Trials.

Behavior change support systems (BCSSs) have the potential to help people maintain healthy lifestyles and aid in the self-management of coronary heart disease (CHD). The Persuasive Systems Design (PSD) model is a framework for designing and evaluating systems designed to support lifestyle modifications and health behavior change using information and communication technology. However, evidence for the underlying design principles behind BCSSs for CHD has not been extensively reported in the literature. This scoping review aims to identify existing health BCSSs for CHD, report the characteristics of these systems, and describe the persuasion context and persuasive design principles of these systems based on the PSD framework. Using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, 3 digital databases (Scopus, Web of Science, and MEDLINE) were searched between 2010 to 2022. The major inclusion criteria for studies were in accordance with the PICO (Population, Intervention, Comparison, and Outcome) approach. Searches conducted in the databases identified 1195 papers, among which 30 were identified as eligible for the review. The most interesting characteristics of the BCSSs were the predominant use of primary task support principles, followed by dialogue support and credibility support and the sparing use of social support principles. Theories of behavior change such as the Social Cognitive Theory and Self-Efficacy Theory were used often to underpin these systems. However, significant trends in the use of persuasive system features on par with behavior change theories could not be established from the reviewed studies. This points to the fact that there is still no theoretical consensus on how best to design interventions to promote behavior change in patients with CHD. Our results highlight key software features for designing BCSSs for the prevention and management of CHD. We encourage designers of behavior change interventions to evaluate the techniques that contributed to the success of the intervention. Future research should focus on evaluating the effectiveness of the interventions, persuasive design principles, and behavior change theories using research methodologies such as meta-analysis.

Designing Behavior Change Support Systems Targeting Blood Donation Behavior

While blood is crucial for many surgeries and patient treatments worldwide, it cannot be produced artificially. Fulfilling the demand for blood products on average days is already a major challenge in countries like South Africa and Ghana. In these countries, less than 1 % of the population donates blood and most of the donations come from first-time donors who do not return. Sufficient new, first-time and even lapsed donors must be motivated to donate regularly. This study argues that blood donation behavior change support systems (BDBCSS) can be beneficially applied to support blood donor management in African countries. In this study, the design science research (DSR) approach is applied in order to derive generic design principles for BDBCSS and instantiate the design knowledge in prototypes for a blood donation app and a chatbot. The design principles were evaluated in a field study in South Africa. The results demonstrate the positive effects of BDBCSS on users’ intentional and developmental blood donation behavior. This study contributes to research and practice by proposing a new conceptualization of blood donation information systems support and a nascent design theory for BDBCSS that builds on behavioral theories as well as related work on blood donation information systems. Thus, the study provides valuable implications for designing preventive health BCSS by stating three design principles for a concrete application context in healthcare.

Mobile health behaviour change support system as independent treatment tool for obesity: a randomized controlled trial

Background/ObjectivesDigital health interventions are increasingly utilized as an adjunct to face-to-face counselling in the treatment of obesity. However, previous studies have shown inconsistent efficacy when digital interventions are used as stand-alone treatment. The purpose of this study was to investigate whether a mobile health behaviour change support system (mHBCSS) is effective in weight reduction and weight loss maintenance without additional counselling. Furthermore, changes in cardiometabolic risk factors were investigated.MethodsIn this randomized controlled trial, a mHBCSS intervention was conducted for 200 volunteers with obesity (BMI 30–40 kg/m² and age 18–65 years). The study participants were randomly assigned into two groups: immediate access to mHBCSS intervention or wait-list control with access to mHBCSS after 6 months. Anthropometric and metabolic traits were also measured. The primary outcome was weight loss from the baseline to the 6-month visit.ResultsAmong 200 participants (88.5% women), mean BMI (SD) was 34.3 kg/m² (2.8) and age 46.5 years (9.5). The retention rate was 98.5% and 89.0% at the 6- and 12-month visits, respectively. At the 6-month visit, those with immediate access to mHBCSS had significantly greater weight loss (−2.5%, 95% CI −3.4 to −1.6, p < 0.001) compared with the wait-list control group (0.2%, 95% CI –0.4 to 0.9, p = 0.466; between groups p < 0.001). Weight loss was maintained until the 12-month time point in the mHBCSS group (−2.1%, 95% CI −3.3 to −0.9, p = 0.001). The usage of mHBCSS had no significant effect on metabolic traits.ConclusionThe mHBCSS as a stand-alone treatment of obesity results in weight reduction and weight loss maintenance with remarkable adherence rate. Further studies are needed to establish how to best implement the scalable and resource-efficient mHBCSS into the standard care of obesity to achieve optimal weight loss results.

Predicting Adherence to Behavior Change Support Systems Using Machine Learning: Systematic Review.

There is a dearth of knowledge on reliable adherence prediction measures in behavior change support systems (BCSSs). Existing reviews have predominately focused on self-reporting measures of adherence. These measures are susceptible to overestimation or underestimation of adherence behavior. This systematic review seeks to identify and summarize trends in the use of machine learning approaches to predict adherence to BCSSs. Systematic literature searches were conducted in the Scopus and PubMed electronic databases between January 2011 and August 2022. The initial search retrieved 2182 journal papers, but only 11 of these papers were eligible for this review. A total of 4 categories of adherence problems in BCSSs were identified: adherence to digital cognitive and behavioral interventions, medication adherence, physical activity adherence, and diet adherence. The use of machine learning techniques for real-time adherence prediction in BCSSs is gaining research attention. A total of 13 unique supervised learning techniques were identified and the majority of them were traditional machine learning techniques (eg, support vector machine). Long short-term memory, multilayer perception, and ensemble learning are currently the only advanced learning techniques. Despite the heterogeneity in the feature selection approaches, most prediction models achieved good classification accuracies. This indicates that the features or predictors used were a good representation of the adherence problem. Using machine learning algorithms to predict the adherence behavior of a BCSS user can facilitate the reinforcement of adherence behavior. This can be achieved by developing intelligent BCSSs that can provide users with more personalized, tailored, and timely suggestions.

The Role UX Design Attributes Play in the Perceived Persuasiveness of Contact Tracing Apps

Contact tracing apps (CTAs) were deployed worldwide in 2020 to combat COVID-19. Due to their low uptake, a growing amount of empirical research is being conducted to understand the factors that drive their adoption. For CTAs to be adopted, users must, first and foremost, find them persuasive. However, there is little research to understand the role user experience (UX) plays in their perceived persuasiveness. Consequently, we conducted an online study on Amazon Mechanical Turk among Canadian and American residents (n = 446) to investigate the most important UX design attributes associated with the perceived persuasiveness of CTAs. The study was based on two app designs (control and persuasive), each of which comprises three use cases: no exposure, exposure, and diagnosis report interfaces. One interface (screenshot) was randomly presented to a participant to view and provide their responses on the perceived UX design attributes and perceived persuasiveness of the interface. In the overall model, we found that perceived usefulness is the most important and consistent UX design attribute that influences perceived persuasiveness (β = 0.29, p &lt; 0.001), followed by perceived trustworthiness (β = 0.24, p &lt; 0.001) and perceived privacy protection (β = 0.16, p &lt; 0.05). Respectively, the three predictors were consistently significant in two-thirds, half, and one-third of the 12 submodels based on app design, adoption status, and country of residence. The relationships regarding the persuasive designs are more likely to be significant, with the variance of the target construct explained by the predictors ranging from 71% to 89% compared with 54% to 69% for the control designs. The three significant attributes will help designers know which UX design attributes to focus on when designing CTAs for future epidemics. More importantly, in predictive modeling, if their ratings are known, they hold potential in predicting new users’ responsiveness to multiple persuasive strategies/messages featured in behavior-change support systems.

Theory-based habit modeling for enhancing behavior prediction in behavior change support systems

Psychological theories of habit posit that when a strong habit is formed through behavioral repetition, it can trigger behavior automatically in the same environment. Given the reciprocal relationship between habit and behavior, changing lifestyle behaviors is largely a task of breaking old habits and creating new and healthy ones. Thus, representing users’ habit strengths can be very useful for behavior change support systems, for example, to predict behavior or to decide when an intervention reaches its intended effect. However, habit strength is not directly observable and existing self-report measures are taxing for users. In this paper, building on recent computational models of habit formation, we propose a method to enable intelligent systems to compute habit strength based on observable behavior. The hypothesized advantage of using computed habit strength for behavior prediction was tested using data from two intervention studies on dental behavior change (N = 36 and N = 75), where we instructed participants to brush their teeth twice a day for three weeks and monitored their behaviors using accelerometers. The results showed that for the task of predicting future brushing behavior, the theory-based model that computed habit strength achieved an accuracy of 68.6% (Study 1) and 76.1% (Study 2), which outperformed the model that relied on self-reported behavioral determinants but showed no advantage over models that relied on past behavior. We discuss the implications of our results for research on behavior change support systems and habit formation.

Can Personalization Persuade? Study of Notification Adaptation in Mobile Behavior Change Intervention Application.

The growing ubiquity of smartphones and the ease of creating and distributing applications render the mobile platform an attractive means for facilitating positive behavior change at scale. Within the smartphone as a behavior change support system, mobile notifications play a critical role as they enable timely and relevant information distribution. In this paper we describe our preliminary investigation of the persuasiveness of mobile notifications delivered within a real-world behavior change intervention mobile app, which enabled users to set goals and define tasks related to those goals. The application aimed to motivate the users with notifications belonging to one of two groups—tailored and non-tailored, seeing them as sparks in the Fogg Behavior Model and personalizing them according to the users’ Big Five personality traits. Results indicate that customized messages may work for some individuals while working poorly for others. When analyzing users as a single group, no significant differences were observed, but when proceeding with the analysis on the individual level we found seven users whose personality traits notifications interact with in interesting ways. Our results offer two general insights: (1) Using personality-tailored messaging in a dynamic mobile domain as opposed to a static domain leads to different outcomes, and it seems that there is no one-to-one mapping between domains; (2) A major reason for most of our hypotheses being false may be that messages that are deemed as persuasive on their own are not what persuades people to perform an action. Unlike the clear-cut findings observed in other domains, we discover a rather nuanced relationship between the personalization and persuasiveness that calls for further exploration at the individual participant level.

Process-based Guidance for Designing Behavior Change Support Systems: Marrying the Persuasive Systems Design Model to the Transtheoretical Model of Behavior Change

Process-based Guidance for Designing Behavior Change Support Systems: Marrying the Persuasive Systems Design Model to the Transtheoretical Model of Behavior Change

The role of informational feedback as a game mechanic on user perceptions, attitudes and the intention to continue using a gamified Health Behaviour Change Support System

Gamification's widespread application across industries has demonstrated its usefulness as a user engagement strategy. In the healthcare sector, the impact of lifestyle diseases has seen the need for modifying health-related behaviours. Health Behaviour Change Support Systems (HBCSS) enhanced with gamification features seek to help users achieve their health related goals. Adapting the Technology Acceptance Model, the role of informational feedback as a game mechanic in influencing perceptions, attitudes and continued usage intentions towards the gamified HBCSS is assessed. The results show a strong influence of attitude towards informational feedback afforded on the continued use intentions of the user.

Intelligent Cognitive Assistants for Attitude and Behavior Change Support in Mental Health: State-of-the-Art Technical Review

Intelligent cognitive assistant (ICA) technology is used in various domains to emulate human behavior expressed through synchronous communication, especially written conversation. Due to their ability to use individually tailored natural language, they present a powerful vessel to support attitude and behavior change. Behavior change support systems are emerging as a crucial tool in digital mental health services, and ICAs exceed in effective support, especially for stress, anxiety and depression (SAD), where ICAs guide people’s thought processes and actions by analyzing their affective and cognitive phenomena. Currently, there is no comprehensive review of such ICAs from a technical standpoint, and existing work is conducted exclusively from a psychological or medical perspective. This technical state-of-the-art review tried to discern and systematize current technological approaches and trends as well as detail the highly interdisciplinary landscape of intersections between ICAs, attitude and behavior change, and mental health, focusing on text-based ICAs for SAD. Ten papers with systems, fitting our criteria, were selected. The systems varied significantly in their approaches, with the most successful opting for comprehensive user models, classification-based assessment, personalized intervention, and dialogue tree conversational models.

Exploring the Impacts of Elaborateness and Indirectness in a Behavior Change Support System

Numerous technologies exist for promoting a healthier lifestyle. These technologies collectively referred to as “Behavior Change Support Systems”. However, the majority of existing apps use quantitative data representation. Since it is difficult to understand the meaning behind quantitative data, this approach has been suggested to lower users' motivation and fail to promote behavior change. Therefore, an interpretation of quantitative data needs to be provided as a supplement. However, different descriptions of the same data may lead to different outcomes. In this paper, we explore the impact of different communication styles for interpretations of quantitative data on behavior change by developing and evaluating Walkeeper - a web-based app that provides interpretations of the users' daily step counts using different levels of elaborateness and indirectness with the aim of promoting walking. Through the quantitative analysis and results of a user study, we contribute new knowledge on designing such interpretations for quantitative data.

A Tailored Motivational Messages Library for a Mobile Health Sleep Behavior Change Support System to Promote Continuous Positive Airway Pressure Use Among Patients With Obstructive Sleep Apnea: Development, Content Validation, and Testing.

BackgroundContinuous positive airway pressure (CPAP) therapy is the most effective treatment for obstructive sleep apnea (OSA). Despite the reported benefits of CPAP therapy in treating OSA, its effectiveness is reduced by less-than-optimal adherence or use. Up to 50% of patients who accept CPAP therapy fail to adhere to it. As a lack of commitment to CPAP therapy is one of the most significant factors that hinder OSA treatment effectiveness, patient motivation and education are critical to help alleviate the problem of poor CPAP adherence or use.ObjectiveThis study aims to support the development of mobile health interventions or information systems solutions to promote CPAP adherence and use among patients with OSA through development, content validation, and testing of tailored motivational messages.MethodsIn phase 1, an initial library of 60 messages was developed to promote CPAP use among patients with OSA. In phase 2, draft messages were evaluated for content validation testing for relevance and clarity by research and clinical experts. In phase 3, patients with OSA (N=24) were recruited through a Qualtrics panel to rate the perceived persuasiveness of the messages in terms of threat and efficacy perceptions, as per their computed extended parallel process model (EPPM) response states. The average score of the ratings was calculated for each message. The messages were sorted according to their average (from highest to lowest) to select the best 12 messages for each tailored set based on the potential responses from the EPPM.ResultsIn phase 1, 60 messages were developed based on the existing literature and a review of existing materials. In phase 2, the enumerated content validity of the messages was established through the use of the content validity index for items. A total of 57 messages were found to have acceptable content relevance and clarity. In phase 3, patients with OSA perceived the final library of 48 messages to be persuasive.ConclusionsAfter the process of content validation and testing, the final library of messages met the criteria for clarity, relevance, and perceived persuasiveness. This study emphasizes the importance of developing and validating the content of motivational messages, grounded in EPPM theory, across the 4 possible response states in terms of high or low efficacy and threat perceptions.

Lifestyle counselling by persuasive information and communications technology reduces prevalence of metabolic syndrome in a dose–response manner: a randomized clinical trial (PrevMetSyn)

Objectives The aim was to investigate whether lifestyle changes produced by persuasive Information and Communication Technology (ICT) counselling can lower the prevalence of metabolic syndrome (MetS). Methods A total of 532 participants (20–60 years, body mass index 27–35 kg/m2) were randomly assigned to six arms according to counselling type (no, short-term, or intensive) with or without ICT intervention. In this report the prevalence of MetS and its components were compared between no-ICT group and ICT group. Moreover, the frequency of the web information system usage was analysed for the number of logins, responses to weekly messages, and other record variables. Results The ICT group had significantly lower proportion of MetS (33.7% vs. 45.3%, p = .022) than the no-ICT group at 2-year follow-up. In mixed model, the ICT group had lower prevalence of MetS than no-ICT group (OR 0.50, 95%CI 0.27–0.90) after intervention. The tertile with the highest utilization had 71% lower prevalence of MetS compared with the lowest utilization tertile or the no-ICT group. Conclusions Web-based ICT is able to reduce the prevalence of MetS. In addition, higher utilization of the web information system is associated with a greater decrease in the prevalence of MetS. Key messages Our internet health behaviour change support system based on persuasive design and cognitive behaviour therapy markedly reduces metabolic syndrome in overweight/obese subjects. As a stand-alone tool it may save healthcare personnel resources as it is suitable at a low cost for both obese/overweight patients and the public at large.

Designing an integrated socio-technical behaviour change system for energy saving

Stimulating households to save energy with behaviour change support systems is a challenge and an opportunity to support efforts towards more sustainable energy consumption. The approaches developed so far, often either; do not consider the underlying behaviour change process in a systematic way, or do not provide a systematic linking of design elements to findings from behaviour change literature and the design of persuasive systems. This paper discusses the design and evaluation of a holistic socio-technical behaviour change system for energy saving that combines insights from behavioural theories and the persuasive system design in a systematic way. The findings from these two streams of research are combined into an integrated socio-technical model for informing the design of a behaviour change system for energy saving, which is then implemented in a concrete system design. The developed system combines smart meter data with interactive visualisations of energy consumption and energy saving impact, gamified incentive mechanisms, energy saving recommendations and attention triggers. The system design distinguishes between a version with non-personalized energy saving tips and a version with personalized recommendations that are deployed and evaluated separately. In this paper, we present the design and evaluation results of the non-personalized system in a real-world pilot. Obtained results indicate reduced energy consumption compared to a control group and a positive change in energy knowledge in the treatment group using the system, as well as positive user feedback about the suitability of the designed system to encourage energy saving.

Tailoring persuasive technology: A systematic review of literature of self-schema theory and transformative learning theory in persuasive technology context

Groundwork for understanding persuasion in human behaviour change through the human-computer environment has been laid by the socio-psychological paradigm and theories, and an acknowledged key element in behaviour change is the role of attitude in the intention-behaviour gap. The said gap is explored in the present paper by means of a systematic literature review of how theories of self-schema and transformative learning have been used thus far in researching behaviour change support systems. Tailoring content and persuasive strategies to some end-user traits is an acknowledged avenue in the persuasive technology field, but what identifiable traits beyond needs, interests, personality, or context can be identified and used in the pursuit of systems that are increasingly more relevant to their users? Various databases were searched for peer-reviewed articles, and the research contributions were analysed against the Persuasive Systems Design Model and Outcome/Change Design Matrix. The results show that neither theory has been used extensively for researching behaviour change support systems; yet, a closer look at the records offers feasible approaches for addressing the intention-behaviour gap. Both SST and TLT emerge as worth investigating as regards identifying and influencing attitude and self-perception level factors in persuasion.

Committing to change: a persuasive systems design analysis of user commitments for a behaviour change support system

ABSTRACT Persuasive systems in different domains have been used to support people in changing their behaviours. These systems motivate desirable behaviour in users by providing relevant information, tracking user progress, and giving them feedback. This study investigates the persuasive features of a web-based information system that supports the enforcement of user commitments. A structural equation modelling approach and analysis of open text responses are used to identify the factors that affect the intention to continue to use the system, to gather users’ perspectives on how the system helps them to stick to their goals and the improvements that could be made. Data (N = 227) collected from the system's users is tested against the proposed research model. The results show that 30% of users’ continuance intention is explained by the implemented persuasive software feature categories (computer-human dialogue support, primary task support, perceived credibility, and social support) and perceived competence. Of these categories, primary task support has the strongest effect on perceived competence and continuance intention. The results also reveal how the system helps users to be consistent in their goals and the lack of specialised social support features. The study concludes with a discussion and recommendations for future research.

Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students

We describe how a mobility behavior change support system, called Blaze, is able to achieve a shift in changing the travel behavior of university students. We identify a causal pathway linking the effect of the technology intervention to its behavioral outcome through the mediation of a number of variables. The stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework to understand how the outcome may be influenced by determinants (conceptual theory), and how the determinants may be activated by different intervention types (action theory). Using longitudinal data from a social experiment conducted over a month at a university in the Philippines, we test three hypotheses regarding the mechanism of change induced by Blaze. Our main findings suggest, in agreement with SSBC, that travel behavior change is achieved by a transition through a temporal sequence of four stages: predecision, pre-action, action and post-action. In an extension from SSBC, we further distinguish post-action depending on whether the behavior is on initiation or under maintenance. We observe that the former (initiation) is characterized by instability (either relapse or progress), while the latter (maintenance) by stability. Moreover, we validate most of the determinants of intentions as postulated by the stage model. Finally, we find that that Blaze can significantly change only the proximate implementation intention and not the more distal ones (e.g. goal and behavioral intentions). We discuss the implications of our results on the potential role of technology interventions in mobility management.

A randomized clinical trial of the effectiveness of a Web-based health behaviour change support system and group lifestyle counselling on body weight loss in overweight and obese subjects: 2-year outcomes.

Weight loss can prevent and treat obesity-related diseases. However, lost weight is usually regained, returning to the initial or even higher levels in the long term. New counselling methods for maintaining lifestyle changes are urgently needed. An information and communication technology-based health behaviour change support system (HBCSS) that utilizes persuasive design and methods of cognitive behavioural therapy (CBT) was developed with the aim of helping individuals to maintain body weight. The purpose of this study was to assess whether CBT-based group counselling combined with HBCSS or HBCSS alone helps to maintain improved lifestyle changes needed for weight loss compared to self-help guidance or usual care. A randomized lifestyle intervention for overweight or obese persons (BMI 27-35kgm-2 and age 20-60years), recruited from the population registry in the city of Oulu, Finland, was conducted. This study comprised six randomly assigned study arms: CBT-based group counselling (eight sessions led by a nutritionist), self-help guidance-based group counselling (SHG; two sessions led by a nurse) and control, each with or without HCBSS, for 52weeks. Subjects visited the study centre for anthropometric measurements, blood sample collection and to complete questionnaires at baseline, 12 and 24months. The main outcome was weight change from baseline to 12months and from baseline to 24months. Of the 1065 volunteers screened for the study, 532 subjects (51% men) met the inclusion criteria and were enrolled. The retention rate was 80% at 12months and 70% at 24months. CBT-based counselling with HBCSS produced the largest weight reduction without any significant weight gain during follow-up. The mean weight change in this arm was 4.1% [95% confidence interval (CI), -5.4 to -2.8, P<0.001) at 12months and 3.4% (95% CI, -4.8 to -2.0, P<0.001) at 24months. HBCSS even without any group counselling reduced the mean weight by 1.6% (95% CI, -2.9 to -0.3, P=0.015) at 24months. The combination of CBT-based group counselling and HBCSS-based weight management is feasible for overweight or obese individuals. Moreover, HBCSS alone could be disseminated to the population at large as an effective means of treating obesity.

Opportunities and challenges of behavior change support systems for enhancing habit formation: A qualitative study

The formation of healthy habits is considered to play a fundamental role in health behavior change. A variety of studies on Health Behavior Change Support Systems (HBCSS) have been conducted recently, in which individuals use such systems to influence their own attitudes or behaviors to achieve their personal goals. However, comparatively much less research has been devoted to studying how the users of these systems form habits with the help of HBCSS, or to understanding how to design these systems to support habit formation. ObjectiveThe objective of this article is to study HBCSS user experiences regarding habit formation through an intervention study targeted at establishing a healthier lifestyle. This study also aims to map habit formation stages, as suggested by Lally and Gardner, with the Persuasive System Design (PSD) model. The application domain is the prevention of metabolic syndrome, in which 5% weight loss can significantly reduce the prevalence of the syndrome. MethodsThis study employs a web-based HBCSS named Onnikka, a lifestyle intervention designed for the prevention of metabolic syndrome for participants who are at risk of developing a metabolic syndrome or are already suffering from it. The system under investigation was designed according to the principles of the PSD model and Behavior Change Support System framework. Lally and Gardner’s research on the stages of habit formation were used to study the extent to which the Onnikka system was able to enhance the development of new habits. A total of 43 Onnikka users were interviewed for this study during and after a 52-week intervention period. The research approach employed here was hermeneutics, which leans ontologically toward the social construction of reality, gained through language, consciousness, and shared meaning. In addition, the system’s login data and participants’ weight measurements were utilized to build an interpretation of the results. ResultsThe findings of this study suggest that IT habits appear to have a strong linkage with use adherence, whereas lifestyle habits did not seem to be directly related to the 5% weight loss among study participants. Moreover, habit formation stages provide a possible explanation for why self-monitoring, reminders, and tunneling were perceived as especially valuable features in this study. ConclusionsFor sustainable weight management, holistic e-health interventions are required, and the PSD model offers a practical approach for designing and developing them. Recognizing the stages of habit formation provides additional valuable guidance for designing systems that help shape an individual’s habits.

SaferDrive: An NLG-based behaviour change support system for drivers

AbstractDespite the long history of Natural Language Generation (NLG) research, the potential for influencing real world behaviour through automatically generated texts has not received much attention. In this paper, we presentSaferDrive, a behaviour change support system that uses NLG and telematic data in order to create weekly textual feedback for automobile drivers, which is delivered through a smartphone application. Usage-based car insurances use sensors to track driver behaviour. Although the data collected by such insurances could provide detailed feedback about the driving style, they are typically withheld from the driver and used only to calculate insurance premiums.SaferDriveinstead provides detailed textual feedback about the driving style, with the intent to help drivers improve their driving habits. We evaluate the system with real drivers and report that the textual feedback generated by our system does have a positive influence on driving habits, especially with regard to speeding.