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  • DIS 2020 Mental wellbeing workshop

    Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in DIS' 20 Companion: Companion Publication of the 2020 ACM Designing Interactive Systems Conference, (2020) https://dl.acm.org/doi/10.1145/3393914.3395920

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    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Mental Wellbeing: Future Agenda Drawing from Design, HCI and Big Data

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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  • Corina Sas
  • Kristina Hook
  • Gavin Doherty
  • Pedro Sanches
  • Tim Leufkens
  • Joyce Westerink
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Abstract

Most HCI work on the exploration and support of mental wellbeing involves mobiles, sensors, and various on-line systems which focus on tracking users. However, adoption of, and adherence to such systems is not ideal. Are there innovative ways to better design for mental wellbeing? A promising novel approach is to encourage changes to behavior through the use of tailored feedback informed by machine learning algorithms applied to large sets of use data. This one day workshop aims to explore novel ways to actively engage participants through interactive systems, with an overall aim to shape the research agenda of future HCI work on mental wellbeing. The workshop is designed in an innovative format offering a mixture of traditional presentation, hands-on design and future-thinking activities. The workshop brings together both practitioners and HCI researchers from across a range areas addressing mental wellbeing.

Bibliographic note

© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in DIS' 20 Companion: Companion Publication of the 2020 ACM Designing Interactive Systems Conference, (2020) https://dl.acm.org/doi/10.1145/3393914.3395920