Developing and validating the user burden scale

A tool for assessing user burden in computing systems

Hyewon Suh, Nina Shahriaree, Eric B. Hekler, Julie A. Kientz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

Computing systems that place a high level of burden on their users can have a negative affect on initial adoption, retention, and overall user experience. Through an iterative process, we have developed a model for user burden that consists of six constructs: 1) difficulty of use, 2) physical, 3) time and social, 4) mental and emotional, 5) privacy, and 6) financial. If researchers and practitioners can have an understanding of the overall level of burden systems may be having on the user, they can have a better sense of whether and where to target future design efforts that can reduce those burdens. To help assist with understanding and measuring user burden, we have also developed and validated a measure of user burden in computing systems called the User Burden Scale (UBS), which is a 20-item scale with 6 individual sub-scales representing each construct. This paper presents the process we followed to develop and validate this scale for use in evaluating user burden in computing systems. Results indicate that the User Burden Scale has good overall inter-item reliability, convergent validity with similar scales, and concurrent validity when compared to systems abandoned vs. those still in use.

Original languageEnglish (US)
Title of host publicationCHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages3988-3999
Number of pages12
ISBN (Electronic)9781450333627
DOIs
StatePublished - May 7 2016
Event34th Annual Conference on Human Factors in Computing Systems, CHI 2016 - San Jose, United States
Duration: May 7 2016May 12 2016

Other

Other34th Annual Conference on Human Factors in Computing Systems, CHI 2016
CountryUnited States
CitySan Jose
Period5/7/165/12/16

Keywords

  • Evaluation
  • Measuring usability
  • Technology abandonment
  • Usability
  • User burden
  • User experience
  • Validated measures

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Suh, H., Shahriaree, N., Hekler, E. B., & Kientz, J. A. (2016). Developing and validating the user burden scale: A tool for assessing user burden in computing systems. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems (pp. 3988-3999). Association for Computing Machinery. https://doi.org/10.1145/2858036.2858448

Developing and validating the user burden scale : A tool for assessing user burden in computing systems. / Suh, Hyewon; Shahriaree, Nina; Hekler, Eric B.; Kientz, Julie A.

CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2016. p. 3988-3999.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suh, H, Shahriaree, N, Hekler, EB & Kientz, JA 2016, Developing and validating the user burden scale: A tool for assessing user burden in computing systems. in CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, pp. 3988-3999, 34th Annual Conference on Human Factors in Computing Systems, CHI 2016, San Jose, United States, 5/7/16. https://doi.org/10.1145/2858036.2858448
Suh H, Shahriaree N, Hekler EB, Kientz JA. Developing and validating the user burden scale: A tool for assessing user burden in computing systems. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2016. p. 3988-3999 https://doi.org/10.1145/2858036.2858448
Suh, Hyewon ; Shahriaree, Nina ; Hekler, Eric B. ; Kientz, Julie A. / Developing and validating the user burden scale : A tool for assessing user burden in computing systems. CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2016. pp. 3988-3999
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