Categorizing users in behavior change support systems based on cognitive dissonance

Isaac Wiafe, Keiichi Nakata, Stephen Gulliver

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

Most developers of behavior change support systems (BCSS) employ ad hoc procedures in their designs. This paper presents a novel discussion concerning how analyzing the relationship between attitude toward target behavior, current behavior, and attitude toward change or maintaining behavior can facilitate the design of BCSS. We describe the three-dimensional relationships between attitude and behavior (3D-RAB) model and demonstrate how it can be used to categorize users, based on variations in levels of cognitive dissonance. The proposed model seeks to provide a method for analyzing the user context on the persuasive systems design model, and it is evaluated using existing BCSS. We identified that although designers seem to address the various cognitive states, this is not done purposefully, or in a methodical fashion, which implies that many existing applications are targeting users not considered at the design phase. As a result of this work, it is suggested that designers apply the 3D-RAB model in order to design solutions for targeted users.

Original languageEnglish
Pages (from-to)1677-1687
Number of pages11
JournalPersonal and Ubiquitous Computing
Volume18
Issue number7
DOIs
Publication statusPublished - 25 Sep 2014
Externally publishedYes

Keywords

  • Behavior change
  • Behavior change support systems
  • Cognitive dissonance
  • Persuasive systems design
  • Persuasive technology

Fingerprint

Dive into the research topics of 'Categorizing users in behavior change support systems based on cognitive dissonance'. Together they form a unique fingerprint.

Cite this