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

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.

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https://knowledge.amia.org/69862-amia-1.4570936/t004-1.4574923/t004-1.4574924/3203139-1.4575141/3203139-1.4575142?qr=1

Eun Kyoung Choe, Yumiko Sakamoto, Yanis Fatmi, Bongshin Lee, Christophe Hurter, Ashkan Haghshenas, and Pourang Irani (2019) Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos, Proceedings of AMIA 2019.

Bibtext Entry

@InProceedings{choe2019persuasive,
author = {Choe, Eun Kyoung and Sakamoto, Yumiko and Fatmi, Yanis and Lee, Bongshin and Hurter, Christophe and Haghshenas, Ashkan and Irani, Pourang},
title = {Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos},
booktitle = {Proceedings of AMIA 2019},
year = {2019},
month = {November},
abstract = {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.},
url = {https://www.microsoft.com/en-us/research/publication/persuasive-data-videos-investigating-persuasive-self-tracking-feedback-with-augmented-data-videos/},
}

Authors

Dr. Yumiko Sakamoto

Dr. Yumiko Sakamoto

Research Associate
Yanis Fatmi

Yanis Fatmi

Alumni
Pourang Irani

Pourang Irani

Professor
Canada Research Chair

As well as: Eun Kyoung Choe, Bongshin Lee, Christophe Hurter