Skip to main content

Perception Versus Reality: How User Self-reflections Compare to Actual Data

  • Conference paper
  • First Online:
Human-Computer Interaction – INTERACT 2023 (INTERACT 2023)

Abstract

One of the main promises of wearable sensing devices capable of physiological tracking is the potential that users can leverage the technology to make positive life changes. Now that these devices have sufficient accuracy, it is feasible that users could make decisions based on feedback from the device to change their habits and improve their well-being. A potential challenge to this, however, is whether users are able to recognize actual changes in their behavior compared to perceived changes. In this work, we look at participants who used the Oura ring as part of an in-the-wild study. Based on data analysis following 10–12 months of usage, we find that users who had positive perceptions of habit change towards sleep failed to show long-term improvement in their sleep quality, indicating a gap between perceived success and real-world impact. This work is important to informing the future design and implementation of health-tracking wearables.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Altini, M., Kinnunen, H.: The Promise of sleep: a multi-sensor approach for accurate sleep stage detection using the OURA ring. Sensors 21(13), 4302 (2021). https://doi.org/10.3390/s21134302. number: 13 Publisher: Multidisciplinary Digital Publishing Institute

  2. Attig, C., Franke, T.: Abandonment of personal quantification: a review and empirical study investigating reasons for wearable activity tracking attrition. Comput. Hum. Beh. 102, 223–237 (2020). https://doi.org/10.1016/j.chb.2019.08.025

    Article  Google Scholar 

  3. Choe, E.K., Lee, B., Zhu, H., Riche, N.H., Baur, D.: Understanding self-reflection: how people reflect on personal data through visual data exploration. In: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, Barcelona Spain, May, pp. 173–182. ACM (2017). https://doi.org/10.1145/3154862.3154881

  4. Choe, E.K., Lee, N.B., Lee, B., Pratt, W., Kientz, J.A.: Understanding quantified-selfers’ practices in collecting and exploring personal data. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto Ontario Canada, April, pp. 1143–1152. ACM (2014). https://doi.org/10.1145/2556288.2557372

  5. Epstein, D.A., Ping, A., Fogarty, J., Munson, S.A.: A lived informatics model of personal informatics. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp 2015, Osaka, Japan, pp. 731–742. ACM Press (2015). https://doi.org/10.1145/2750858.2804250

  6. Garcia, J.J., de Bruyckere, H., Keyson, D.V., Romero, N.: Designing personal informatics for self-reflection and self-awareness: the case of children with attention deficit hyperactivity disorder. In: Augusto, J.C., Wichert, R., Collier, R., Keyson, D., Salah, A.A., Tan, A.-H. (eds.) Am I 2013. LNCS, vol. 8309, pp. 109–123. Springer, Cham (2013). https://doi.org/10.1007/978-3-319-03647-2_8

  7. Gilmore, J.N.: Predicting Covid-19: wearable technology and the politics of solutionism. Cult. Stud. 35(2–3), 382–391 (2021). https://doi.org/10.1080/09502386.2021.1898021

    Article  Google Scholar 

  8. Grammel, L., Tory, M., Storey, M.: How information visualization novices construct visualizations. IEEE Trans. Visual Comput. Graphics 16(6), 943–952 (2010). https://doi.org/10.1109/TVCG.2010.164

    Article  Google Scholar 

  9. Huang, D., et al.: Personal visualization and personal visual analytics. IEEE Trans. Visual Comput. Graphics 21(3), 420–433 (2015). https://doi.org/10.1109/TVCG.2014.2359887

    Article  Google Scholar 

  10. Kefalidou, G., et al.: Enhancing self-reflection with wearable sensors. In: Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services, Toronto ON Canada, September 2014, pp. 577–580. ACM (2014). https://doi.org/10.1145/2628363.2634257

  11. Lazar, A., Koehler, C., Tanenbaum, J., Nguyen, D.H.: Why we use and abandon smart devices. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp 2015, Osaka, Japan, pp. 635–646. ACM Press (2015). https://doi.org/10.1145/2750858.2804288

  12. Li, I., Dey, A., Forlizzi, J.: A stage-based model of personal informatics systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Atlanta Georgia USA, April, pp. 557–566. ACM (2010). https://doi.org/10.1145/1753326.1753409

  13. Malakhatka, E., Al Rahis, A., Osman, O., Lundqvist, P.: Monitoring and predicting occupant’s sleep quality by using wearable device OURA Ring and smart building sensors data (living laboratory case study). Buildings 11(10), 459 (2021). https://doi.org/10.3390/buildings11100459. number: 10 Publisher: Multidisciplinary Digital Publishing Institute

  14. Marcengo, A., Rapp, A., Cena, F., Geymonat, M.: The falsified self: complexities in personal data collection. In: Antona, M., Stephanidis, C. (eds.) UAHCI 2016. LNCS, vol. 9737, pp. 351–358. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40250-5_34

  15. Rooksby, J., Rost, M., Morrison, A., Chalmers, M.: Personal tracking as lived informatics. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto Ontario Canada, April 2014, pp. 1163–1172. ACM (2014). https://doi.org/10.1145/2556288.2557039

  16. Sas, C., Dix, A.: Designing for reflection on experience. In: CHI 2009 Extended Abstracts on Human Factors in Computing Systems, Boston MA USA, April 2009, pp. 4741–4744. ACM (2009). https://doi.org/10.1145/1520340.1520730

Download references

Acknowledgements

This work was supported in part by grants from JST Trilateral AI project, Learning Cyclotron (JPMJCR20G3), JSPS Kakenhi (20KK0235), and the Grand challenge of the Initiative for Life Design Innovation (iLDi).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hannah R. Nolasco .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

R. Nolasco, H., Vargo, A., Komatsu, Y., Iwata, M., Kise, K. (2023). Perception Versus Reality: How User Self-reflections Compare to Actual Data. In: Abdelnour Nocera, J., Kristín Lárusdóttir, M., Petrie, H., Piccinno, A., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol 14144. Springer, Cham. https://doi.org/10.1007/978-3-031-42286-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-42286-7_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42285-0

  • Online ISBN: 978-3-031-42286-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics