Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos

Eun Kyoung Choe (1) , Yumiko Sakamoto (1) , Yanis Fatmi (2) , Bongshin Lee (3) , Christophe Hurter (2) , Ashkan Haghshenas (4) , Pourang Irani (4)

1 University of Maryland [College Park]
2 ENAC - Ecole Nationale de l'Aviation Civile
3 Microsoft Research [Redmond]
4 University of Manitoba [Winnipeg]

Self-tracking feedback with engaging and persuasive visualizations not only helps convey data but can also affect people's attitudes and behaviors. We investigate persuasive self-tracking feedback by augmenting data videos (DVs)-novel, engaging storytelling media. We introduce a new class of DVs, called Persuasive Data Videos (PDVs), by incorporating four persuasive elements-primary task, dialogue, system credibility, and social supports-drawn from the Persuasive System Design Model. We describe the iterative design of PDVs and a within-subjects preliminary validation to check their persuasive potential. We then assess PDVs' feasibility using the Persuasive Potential Questionnaire in a between-subjects study comparing a PDV against a conventional DV on Amazon Mechanical Turk (N = 252). Our results indicate the feasibility of using PDVs in providing individuals' self-tracking feedback to convey persuasive health messages, based on which we discuss opportunities for designing persuasive behavioral feedback in an engaging way.

Domaines: Informatique [cs]

Eun Kyoung Choe, Yumiko Sakamoto, Yanis Fatmi, Bongshin Lee, Christophe Hurter, et al.. Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos. AMIA 2019, Annual Symposium Informatics: From Data to Knowledge to Action, Nov 2019, Washington, United States. ⟨hal-02561809⟩