Designing representations of behavioral data with blended causality: An approach to interventions for lifestyle habits

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1 Citation (Scopus)


Many personal informatics systems present users’ behavioral data in numbers or graphs for their reflection, which may not be effective on a daily basis because people do not always act like data scientists. Representation of behavioral data in virtual environments can provide information at a glance. Grounded in conceptual blending theory, insights from social psychology, and existing persuasive design principles, this article is conceptual-theoretical. It argues that representations should be designed like virtual consequences of behavior and related to users’ existing knowledge of comparable cause-effect relationships in order to prompt one’s imaginative beliefs about the behavioral-virtual causality. It proposes a framework that guides designing representations of behavioral data, including (1) identifying scenarios with comparable causality, (2) examining and grounding the mappings in embodied experiences, (3) performing blends between the behavior and the identified scenario, with different virtual consequences corresponding to different user behaviors, and (4) rendering virtual consequences as feedback that dynamically anchors the scenario for similar blends in users. Design cases are presented and analyzed to demonstrate how embodied mappings can be constructed for interventions for lifestyle habits.

Original languageEnglish
Title of host publicationProceedings of International conference on Persuasive Technology: Development of Persuasive and Behavior Change Support Systems - 14th International Conference, PERSUASIVE 2019, Proceedings
EditorsEvangelos Karapanos, Eleni Kyza, Khin Than Win, Harri Oinas-Kukkonen, Pasi Karppinen
Number of pages13
ISBN (Print)9783030172862
Publication statusPublished - Apr 2019
Event14th International Conference on Persuasive Technology, PERSUASIVE 2019 - Limassol, Cyprus
Duration: 9 Apr 201911 Apr 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Conference on Persuasive Technology, PERSUASIVE 2019


  • Behavior change
  • Blending theory
  • Personal informatics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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