Persuasive software design patterns for social influence

Oduor, Michael; Alahäivälä, Tuomas; Oinas-Kukkonen, Harri

doi:10.1007/s00779-014-0778-z

Cited by 43 publications

(23 citation statements)

References 52 publications

(95 reference statements)

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“…The COM-B model is compatible with recent software design models that emphasize social influence processes (Fogg 2009), and behavior change support systems (BCSS) (Oinas-Kukkonen and Harjumaa 2009). A prevescalation intervention that acknowledges strong social influences on tobacco use, therefore, may be delivered via social media and incorporate the following design principles: (1) social learning and facilitation, (2) competition (self-regulation via comparison of their performance with peers and behavioral adjustment), (3) cooperation (motivation to adopt a target behavior by leveraging the desire to be like their peers), and (4) recognition (motivation to change behavior in order to receive personal and public recognition for their efforts and accomplishments) (Oduor et al 2014).…”

Section: Strategies For Delivering and Scaling An Interventionmentioning

confidence: 99%

Preventing Smoking Progression in Young Adults: the Concept of Prevescalation

et al. 2018

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As adolescents cross the threshold to young adulthood, they encounter more opportunities to engage in or accelerate previously discouraged or prohibited behaviors. Young adults, therefore, are more apt to initiate cigarette smoking and, more importantly, to accelerate their use if they tried and experimented as an adolescent. Preventing the escalation and entrenchment of smoking in the young adult years is critically important to reducing tobacco's long-term health toll. However, traditional interventions for youth have focused on preventing smoking initiation, and interventions for adults have focused on smoking cessation; both have failed to address the needs of young adults. We introduce the concept of Bprevescalation^to capture the need and opportunity to prevent the escalation of risk behaviors that typically occur during young adulthood, with a focus on the example of cigarette smoking. Prevescalation negates the notion that prevention has failed if tobacco experimentation occurs during adolescence and focuses on understanding and interrupting transitions between experimentation with tobacco products and established tobacco use that largely occur during young adulthood. However, since risk behaviors often co-occur in young people, the core concept of prevescalation may apply to other behaviors that co-occur and become harder to change in later adulthood. We present a new framework for conceptualizing, developing, and evaluating interventions that better fit the unique behavioral, psychosocial, and socio-environmental characteristics of the young adult years. We discuss the need to target this transitional phase, what we know about behavioral pathways and predictors of cigarette smoking, potential intervention considerations, and research challenges.

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Section: Strategies For Delivering and Scaling An Interventionmentioning

confidence: 99%

Preventing Smoking Progression in Young Adults: the Concept of Prevescalation

et al. 2018

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“…Second, we contribute to research by showing that the medical condition plays a significant role on the design of social features together with the scientific theories, designer's interpretation, and external factors [13]. Our results can be used to underline the importance of medical condition and its sub factors in the design practice in the field of health behavior change, and give a better understanding of the current practice for creating relevant frameworks and guidelines for better supporting the practitioners in the design of the social features [3,4,5,10].…”

Section: Resultsmentioning

confidence: 78%

“…Theory [3,4], but also practice, show that social influence features are oftentimes treated as a black box. In the previous section, we shed light on this black box by presenting our results regarding the designers' rationales for the inclusion and design of social influence features in health behavior change applications .…”

Section: Discussionmentioning

confidence: 99%

“…Fogg [23] describes this technology as persuasive, because through means of persuasion and social influence the behavior change is supported. However, social influence in the design of persuasive technology oftentimes is described as a black box that needs to be opened [3][4][5]. Designers understand the importance to implement social influence features in behavior change technologies , but they often do not discriminate between the different social influence aspects.…”

Section: Social Influence As a Black Boxmentioning

confidence: 99%

“…However, it is unclear how designers take these theories into account and how they actually decide about the inclusion and design of social influence features. In previous research, social influence features have often been viewed as a black box [3][4][5], and their designs seem to be popped out without any particular explanation of why this particular feature was chosen and why it was designed in a specific way. In this paper, we address this gap through the research question: "What are the designers' rationales for the inclusion and design of social influence features in health behavior change applications?"…”

Section: Introductionmentioning

confidence: 99%

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Rationale Behind Socially Influencing Design Choices for Health Behavior Change

Mylonopoulou

Väyrynen

Stibe

et al. 2018

Persuasive Technology

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Abstract. Persuasive technologies for health behavior change often include social influence features. Social influence in the design of persuasive technology has been described as a black box. This case study sheds light on design practices by identifying factors that affect the design of social influence features in health behavior change applications and the designers' understanding of the social influence aspects. Our findings are twofold: First, the two most positively inclined social influence features, namely cooperation and normative influence, were missing from the reviewed applications. Second, the medical condition -the persuasive technology targets -has a major influence on consideration and integration of social influence features in health behavior change applications. Our findings should be taken into account when frameworks and guidelines are created for the design of social influence features in health behavior change applications.

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