Self-management of COPD supported by eHealth: Patients’ attitudes towards monitoring, risk prediction and virtual coaching

Marian Z.M. Hurmuz*, Eline te Braake, Stephanie M. Jansen-Kosterink, Christiane Grünloh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Purpose: Chronic obstructive pulmonary disease (COPD) has a high burden on patients, tremendously affecting their quality of life. For patients to be more pro-active, self-management is important. To support patients in their self-management, health data collection is needed for monitoring, which can be used for risk predictions and personalised coaching. Within the RE-SAMPLE project, we want to include these features in an eHealth technology. This study aims to investigate the attitudes of people with COPD towards health monitoring, risk predictions and virtual coaching.

Methods: We conducted workshops and interviews with persons diagnosed with COPD. Six persons participated in the workshops which focused on topics for virtual coaching. Ten persons participated in the interviews focusing on monitoring, risk prediction and virtual coaching. Results: In general, participants were positive towards the concepts health monitoring, risk predictions and virtual coaching within a self-management eHealth technology. However, most participants felt that persons who are more recently diagnosed with COPD would benefit more from using such a technology. People who are dealing with COPD for several years already know or think they know how to self-manage their disease and what helps them and what not. Conclusion: Based on our findings, we discuss several implications for design of self-management eHealth technologies for COPD: personalization in context and level of details, supporting people to reflect on their behaviour and patterns detected in the monitoring, balance accountability and paternalism when it comes to coaching, and finally explainable AI concerning risk predictions. Furthermore, we want to argue that in these types of studies, it is also important to include people newly diagnosed with COPD to have more inclusive results.

Original languageEnglish
Title of host publicationNordiCHI '24
Subtitle of host publicationProceedings of the 13th Nordic Conference on Human-Computer Interaction
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
ISBN (Electronic)979-8-4007-0966-1
DOIs
Publication statusPublished - 13 Oct 2024
Event13th Nordic Conference on Human-Computer Interaction, NordiCHI 2024: Live – Uniting HCI for a Hyperlocal and Global Experience - Uppsala, Sweden
Duration: 13 Oct 202416 Oct 2024
Conference number: 13
https://www.nordichi2024.se

Conference

Conference13th Nordic Conference on Human-Computer Interaction, NordiCHI 2024
Abbreviated titleNordiCHI 2024
Country/TerritorySweden
CityUppsala
Period13/10/2416/10/24
Internet address

Keywords

  • Chronic obstructive pulmonary disease
  • Data collection
  • Monitoring
  • Risk prediction
  • Self-management
  • Virtual coaching

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