Advertisement

Art-Based User Research: Combining Art-Based Research and User Research to Inform the Design of a Technology to Improve Emotional Wellbeing

  • Carla NaveEmail author
  • Teresa Romão
  • Nuno Correia
Conference paper
First Online:
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 265)

Abstract

This paper presents research output from an experiment that combines ideas from User Research and Art-based Research. Artistic processes inspired the study, in which we asked participants to assess and then “paint” their emotions over emotion-eliciting images using an array of materials, such as watercolors and colored pencils. We used a mixed methods approach that included questionnaires, psychometric data from validated scales and informal conversations. Our primary goals were to inform the design of a mobile application meant to improve emotional wellbeing and assess whether creative self-expression can help to engage users when evaluating and exploring their affective states. We conclude by summarizing the results, which we believe to be positive.

Keywords

Art-based research Design Emotions Human-Computer Interaction Technology User research Wellbeing 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

This work is funded by Fundação para a Ciência e Tecnologia - grant PD/BD/114141/2015 and FCT/MEC NOVA LINCS PEst UID/CEC/04516/2013.

References

  1. 1.
    Attfield, S., Kazai, G., Lalmas, M.: Towards a science of user engagement (position paper). In: WSDM Workshop on User Modelling for Web Applications (2011)Google Scholar
  2. 2.
    Bradley, M., Lang, P.J.: Measuring emotion the self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25(1), 49–59 (1994)CrossRefGoogle Scholar
  3. 3.
    Carroll, J.M.: Human-computer interaction: psychology as a science of design. Annu. Rev. Psychol. 48(1), 61–83 (1997)CrossRefGoogle Scholar
  4. 4.
    Csikszentmihalyi, M.: Flow: The Psychology of Optimal Experience. Harper, New York (1990)Google Scholar
  5. 5.
    Csikszentmihalyi, M.: The Evolving Self: A Psychology for the Third Millennium. Harper, New York (1993)Google Scholar
  6. 6.
    Dan-Glauser, E.S., Scherer, K.R.: The Geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance. Behav. Res. Methods 43(2), 468–477 (2011)CrossRefGoogle Scholar
  7. 7.
    Gute, D., Gute, G.: How creativity works in the brain. National Endowment for the Arts (2015)Google Scholar
  8. 8.
    De Petrillo, L., Winner, E.: Does art improve mood? A test of a key assumption underlying art therapy. Art Ther. 22(4), 205–212 (2005)CrossRefGoogle Scholar
  9. 9.
    Edwards, D.: Art therapy (2004)Google Scholar
  10. 10.
    Engeser, S., Rheinberg, F.: Flow, performance and moderators of challenge-skill balance. Motiv. Emot. 32(3), 158–172 (2008)CrossRefGoogle Scholar
  11. 11.
    Eysenbach, G.: The law of attrition. J. Med. Internet Res. 7(1) (2005)CrossRefGoogle Scholar
  12. 12.
    Geraghty, A.W.A., Torres, L.D., Leykin, Y., Pérez-Stable, E.J., Muñoz, R.F.: Understanding attrition from international Internet health interventions: a step towards global eHealth. Health Promot. Int. 28(3), 442–452 (2013)CrossRefGoogle Scholar
  13. 13.
    Gulliksen, J., Göransson, B., Boivie, I., Blomkvist, S., Persson, J., Cajander, Å.: Key principles for user-centred systems design. Behav. Inf. Technol. 22, 397–409 (2003)CrossRefGoogle Scholar
  14. 14.
    Guo, Y.M., Poole, M.S.: Antecedents of flow in online environments: the role of website complexity. In: AMCIS 2006 Proceedings, pp. 2933–2941 (2006)Google Scholar
  15. 15.
    Jackson, S.A., Marsh, H.W.: Development and validation of a scale to measure optimal experience: the flow state scale. J. Sport Exerc. Psychol. 18, 17–35 (1996)CrossRefGoogle Scholar
  16. 16.
    Knowles, J., Cole, A.: Handbook of the Arts in Qualitative Research: Perspectives. Examples, and Issues, Methodologies (2008)Google Scholar
  17. 17.
    Lang, P.J.: Behavioral treatment and bio-behavioral assessment: computer applications, in technology in mental health care delivery systems (1980)Google Scholar
  18. 18.
    Lee, E.: The relationship of motivation and flow experience to academic procrastination in university students. J. Genet. Psychol. 166(1), 5–15 (2005)MathSciNetCrossRefGoogle Scholar
  19. 19.
    McNiff, S.: Art-based research. In: Handbook of the Arts in Qualitative Research: Perspectives, Methodologies, Examples, and Issues (1998)Google Scholar
  20. 20.
    Quinn, R.W.: Flow in knowledge work: high performance experience in the design of national security technology. Adm. Sci. Q. 50, 610–641 (2005)CrossRefGoogle Scholar
  21. 21.
    Reynolds, M.W., Nabors, L., Quinlan, A.: The effectiveness of art therapy: does it work? Art Ther. 17, 207–213 (2000)CrossRefGoogle Scholar
  22. 22.
    Root-Bernstein, B., Siler, T., Brown, A., Snelson, K.: ArtScience: integrative collaboration to create a sustainable future. Leonardo 44(3), 192 (2011)CrossRefGoogle Scholar
  23. 23.
    Slayton, S., D’Archer, J., Kaplan, F.: Outcome studies on the efficacy of art therapy: a review of findings. Art Ther.: J. Am. Art Ther. Assoc. 27(3), 108–118 (2010)CrossRefGoogle Scholar
  24. 24.
    Swan, M.: Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0. J. Sens. Actuator Netw. 1(3), 217–253 (2012)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.NOVALincs, Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal

Personalised recommendations

Cite paper

Buy options