Abstract

Mental wellbeing is a growing concern for many young adults today. The design of digital products and services that could support young adults is hampered by a lack of knowledge about what constitutes mental wellbeing, and what design requirements exist for interventions. This study applied a provotyping method to add to this knowledge. Results show that mental wellbeing is broader than hedonic and eudaimonic aspects, encompassing also social, psychosocial, health- and activity-related and relaxation-related aspects. Design requirements for interventions that automatically register and provide feedback on mental wellbeing include tailoring of defining aspects to personal situations, algorithms that learn from user input, continuous and unobtrusive measurement, and minimalisation of burden. This research shows that using sensors and algorithms for mental wellbeing support for young adults is still in its early stages, and offers insights to inform next steps in design research in this area.

Keywords

mental wellbeing; digital health; design requirements; measuring mental wellbeing

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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Research Paper

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Jun 23rd, 9:00 AM Jun 28th, 5:00 PM

Measuring Mental Wellbeing – Can We Measure It, And If So, What Should We Measure, And How? A Qualitative Provotyping Study

Mental wellbeing is a growing concern for many young adults today. The design of digital products and services that could support young adults is hampered by a lack of knowledge about what constitutes mental wellbeing, and what design requirements exist for interventions. This study applied a provotyping method to add to this knowledge. Results show that mental wellbeing is broader than hedonic and eudaimonic aspects, encompassing also social, psychosocial, health- and activity-related and relaxation-related aspects. Design requirements for interventions that automatically register and provide feedback on mental wellbeing include tailoring of defining aspects to personal situations, algorithms that learn from user input, continuous and unobtrusive measurement, and minimalisation of burden. This research shows that using sensors and algorithms for mental wellbeing support for young adults is still in its early stages, and offers insights to inform next steps in design research in this area.

 

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