Myriam Sillevis Smitt

Mehdi Montakhabi

Jessica Morton

Cora van Leeuwen

Klaas Bombeke

An Jacobs 


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.


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