Users’ perceptions of a personalized stress self-monitoring application; research insights to design a practical innovation
File(s)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Self-monitoring is considered a promising tool for self-management in clinical mental health, such as for coping with excessive stress. Detecting debilitating stress before the onset of a psychopathology is becoming more of interest both for practitioners and the scientific community. However, the development of mental well-being technology focusing on stress is disrupted by the complexity of accurately measuring stress, as no clear idea exists on the construct and how it should be measured. There is also limited knowledge on the perception of perceived quality of the outcomes from a stress algorithm and the variety in its behavioural consequences. Therefore, the purpose of this study is to explore the impact of such digital self-monitoring technology for stress. It applies a qualitative method, by using semi-structured interviews. The most important resulting themes to users of this application were data-interpretation and a request for transparency. Results indicated that the majority of the predictions of the stress algorithm were not in line with the expectations of the users. The implications of these findings reveal how stress algorithms can make participants doubt their own self judgment on assessing their daily stress levels.
Date Acceptance
2022-01-01
Citation
Universal Access in Human-Computer Interaction. Novel Design Approaches and Technologies. HCII 2022., 13308, pp.325-341
ISBN
978-3-031-05028-2
Publisher
Springer Cham
Start Page
325
End Page
341
Journal / Book Title
Universal Access in Human-Computer Interaction. Novel Design Approaches and Technologies. HCII 2022.
Volume
13308
Copyright Statement
Copyright © 2022 Springer-Verlag. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-05028-2_22
Identifier
https://link.springer.com/chapter/10.1007/978-3-031-05028-2_22
Source
24th HCI International Conference, HCII 2022
Publication Status
Published
Start Date
2022-06-26
Finish Date
2022-07-01
Date Publish Online
2022-06-16