Nudging behavior change: using in-group and out-group social comparisons to encourage healthier choices

This paper revisits concepts of nudge in the context of helping consumers to make healthier food choices. We introduce a novel form of social influence nudge not yet investigated by HCI scholars, the out-group social comparison, and test whether this form of nudging works at the point of checkout rather than the more conventional point of product consideration. Across two online experiments, we measure the effectiveness of using nutritional information nudges with added in-group (people like you) and out-group (people not like you) social comparisons. Our preliminary findings suggest that out-group social comparison nudges can be effective in encouraging both normal weight and overweight adults to reduce calories, even when these adults indicate that they do not typically change their diet behaviors. This research has implications for digital information design, interactive marketing, and public health

Blueprints:Systematizing Behavior Change Designs-The Case of Social Comparison Theory

To improve people's lives, human-computer interaction researchers are increasingly designing technological solutions based on behavior change theory, such as social comparison theory (SCT). However, how researchers operationalize such a theory as a design remains largely unclear. One way to clarify this methodological step is to clearly state which functional elements of a design are aimed at operationalizing a specific behavior change theory construct to evaluate if such aims were successful. In this article, we investigate how the operationalization of functional elements of theories and designs can be more easily conveyed. First, we present a scoping review of the literature to determine the state of operationalizations of SCT as behavior change designs. Second, we introduce a new tool to facilitate the operationalization process. We term the tool blueprints. A blueprint explicates essential functional elements of a behavior change theory by describing it in relation to necessary and sufficient building blocks incorporated in a design. We describe the process of developing a blueprint for SCT. Last, we illustrate how the blueprint can be used during the design refinement and reflection process.</p

The Influence Of Attachment Security Priming On Relationship Social Comparison Interpretations

Relationship social comparisons occur when an individual compares their relationship to another. These comparisons are unavoidable and the interpretation of them can influence how an individual feels about their relationship. Dispositional attachment style may influence how these comparisons are interpreted. Furthermore, research has shown individuals can be temporarily primed for specific attachment styles which results in cognitions and behaviors consistent with that attachment style. The current study examined the efficacy of priming attachment security on how an individual interprets relationship social comparison interpretations (RSCIs) and relationship satisfaction. A final sample of 505 individuals in a dating relationship were recruited from the United States. Though attachment priming had no effect on positive upward RSCIs, participants primed with secure attachment made RSCIs that were less negative and had more relationship satisfaction. In addition, participants with fearful-avoidant and preoccupied attachment who were primed for secure attachment had less negative RSCI compared to participants with the same attachment style who did not receive the secure prime. Collectively, these results may be important first steps that attachment priming may be effective at promoting relationship interpretations that are less negative and relationships that are more satisfying

Tracking in the wild: exploring the everyday use of physical activity trackers

As the rates of chronical diseases, such as obesity, cardiovascular disease and diabetes continue to increase, the development of tools that support people in achieving healthier habits is becoming ever more important. Personal tracking systems, such as activity trackers, have emerged as a promising class of tools to support people in managing their everyday health. However, for this promise to be fulfilled, these systems need to be well designed, not only in terms of how they implement specific behavior change techniques, but also in how they integrate into people’s daily lives and address their daily needs. My dissertations provides evidence that accounting for people’s daily practices and needs can help to design activity tracking systems that help people get more value from their tracking practices. To understand how people derive value from their activity tracking practices, I have conducted two inquiries into people’s daily uses of activity tracking systems. In a fist attempt, I led a 10-month study of the adoption of Habito, our own activity tracking mobile app. Habito logged not only users’ physical activity, but also their interactions with the app. This data was used to acquire an estimate of the adoption rate of Habito, and understanding of how adoption is affected by users’ ‘readiness’, i.e., their attitude towards behavior change. In a follow-up study, I turned to the use of video methods and direct, in-situ observations of users’ interactions to understand what motivates people to engage with these tools in their everyday life, and how the surrounding environment shapes their use. These studies revealed some of the complexities of tracking, while extending some of the underlying ideas of behavior change. Among key results: (1) people’s use of activity trackers was found to be predominantly impulsive, where they simultaneously reflect, learn and change their behaviors as they collect data; (2) people’s use of trackers is deeply entangled with their daily routines and practices, and; (3) people use of trackers often is not in line with the traditional vision of these tools as mediators of change – trackers are also commonly used to simply learn about behaviors and engage in moments of self-discovery. Examining how to design activity tracking interfaces that best support people’s different needs , my dissertation further describes an inquiry into the design space of behavioral feedback interfaces. Through a iterative process of synthesis and analysis of research on activity tracking, I devise six design qualities for creating feedback that supports people in their interactions with physical activity data. Through the development and field deployment of four concepts in a field study, I show the potential of these displays for highlighting opportunities for action and learning.À medida que a prevalência de doenças crónicas como a obesidade, doenças cardiovasculares e diabetes continua a aumentar, o desenvolvimento de ferramentas que suportam pessoas a atingir mudanças de comportamento tem-se tornado essencial. Ferramentas de monitorização de comportamentos, tais como monitores de atividade física, têm surgido com a promessa de encorajar um dia a dia mais saudável. Contudo, para que essa promessa seja cumprida, torna-se essencial que estas ferramentas sejam bem concebidas, não só na forma como implementam determinadas estratégias de mudança de comportamento, mas também na forma como são integradas no dia-a-dia das pessoas. A minha dissertação demonstra a importância de considerar as necessidades e práticas diárias dos utilizadores destas ferramentas, de forma a ajudá-las a tirar melhor proveito da sua monitorização de atividade física. De modo a entender como é que os utilizadores destas ferramentas derivam valor das suas práticas de monitorização, a minha dissertação começa por explorar as práticas diárias associadas ao uso de monitores de atividade física. A minha dissertação contribui com duas investigações ao uso diário destas ferramentas. Primeiro, é apresentada uma investigação da adoção de Habito, uma aplicação para monitorização de atividade física. Habito não só registou as instâncias de atividade física dos seus utilizadores, mas também as suas interações com a própria aplicação. Estes dados foram utilizados para adquirir uma taxa de adopção de Habito e entender como é que essa adopção é afetada pela “prontidão” dos utilizadores, i.e., a sua atitude em relação à mudança de comportamento. Num segundo estudo, recorrendo a métodos de vídeo e observações diretas e in-situ da utilização de monitores de atividade física, explorei as motivações associadas ao uso diário destas ferramentas. Estes estudos expandiram algumas das ideias subjacentes ao uso das ferramentas para mudanças de comportamento. Entre resultados principais: (1) o uso de monitores de atividade física é predominantemente impulsivo, onde pessoas refletem, aprendem e alteram os seus comportamentos à medida que recolhem dados sobe estes mesmos comportamentos; (2) o uso de monitores de atividade física está profundamente interligado com as rotinas e práticas dos seus utilizadores, e; (3) o uso de monitores de atividade física nem sempre está ligado a mudanças de comportamento – estas ferramentas também são utilizadas para divertimento e aprendizagem. A minha dissertação contribui ainda com uma exploração do design de interfaces para a monitorização de atividade física. Através de um processo iterativo de síntese e análise de literatura, seis qualidades para a criação de interfaces são derivadas. Através de um estudo de campo, a minha dissertação demonstro o potencial dessas interfaces para ajudar pessoas a aprender e gerir a sua saúde diária

How does a Gamification Design Influence Students’ Interaction in an Online Course?

This study created and examined a gamification design that aimed at improving students’ interaction in a graduate level online course. By using a design-based research approach, the study investigated the application of principles from Self-Determination Theory in the gamification design and its influence on students’ interaction in discussion forums in terms of quantity, interaction dynamic, and interaction quality. The gamification design included a positive feedback system, contextualized in a narrative environment that was based on the original course project design. Participants were 49 students enrolled in the online course in three versions of the course, which were the non-gamification version of the course in the 2016 summer semester (NGC), the prototype gamification version of the course in the 2016 summer semester (PGC), and the revised gamification version of the course in the 2016 summer semester (RGC). Students’ interaction data in the academic discussion forums were compared with each other. Students’ gamification performance data were presented and compared between the PGC and the RGC. Moreover, eight students from the RGC participated in semi-structured interviews and shared their experiences and perspectives about the revised gamification design. The results showed that students in the gamified courses posted more messages per week. When students were the facilitators for the week, they were more actively involved in the online discussion. The student facilitators in the gamified courses were more active compared to the student facilitators in the non-gamified course. Second, students’ interaction was more evenly distributed among students in the gamified courses. On average, students in the gamified courses received comments from more peers than students in the non-gamified course. The class level density scores were higher with smaller centralization scores in the gamified courses. Finally, the RGC discussion transcripts presented more knowledge building features on a weekly basis in comparison with the PGC and the NGC, while overall the online discussion in the three versions of the course fell into the lower phases in the knowledge building conceptual model. Students’ gamification performance was about the same in the two gamified courses. Nonetheless, the design adjustments made between the two design cycles and during the second cycle improved students’ participation in several gamification activities. Furthermore, students’ interaction was more stable during the six weeks in the RGC due to the design adjustments. The semi-structured interviews further revealed the RGC interviewees’ experiences in the course. The positive feedback system satisfied students’ competence needs. Nonetheless, to what degree their competence needs were satisfied depended on their experiences and understanding of gamification. In pursuit of competence needs, some interviewees’ autonomy needs were undermined. The peer evaluation, dynamic academic discussion, and the authentic course project satisfied students’ relatedness needs. But additional emotional support from peers was barely sufficient. The study provided an example of gamification design in online courses to improve students’ interactions in discussion forums. The results suggested a positive feedback system could be added in the course design to improve students’ performance of the targeted learning activities. The selection of learning activities, the design and development of the gamification elements, and the gamification algorithm should take both the subject matter and students’ characteristics into consideration. A narrative environment can help align the feedback system with the course context and students’ actions should result in development of the narrative