Persuasive Technology to Support Chronic Health Conditions: Investigating the Optimal Persuasive Strategies for Persons with COPD

  • Beatrix Wais-Zechmann
  • Valentin Gattol
  • Katja Neureiter
  • Rita Orji
  • Manfred Tscheligi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10809)

Abstract

Persuasive technology can support persons with chronic conditions to comply with their treatment plan. For persons with chronic obstructive pulmonary disease (COPD), staying physically active is crucial to prevent deteriorations of their health status. However, most persons with COPD do not reach and maintain recommended levels of physical activity goals. Although COPD is expected to become the third most common cause of death worldwide, research on how to design persuasive systems for motivating specifically persons with COPD to engage in regular physical activity is still scarce. To bridge this gap, we conducted a study involving persons with COPD (n = 115) to investigate the perceived persuasiveness of 17 strategies (i.e., ratings of their concrete implementation) and individual susceptibility to persuasion (i.e., an underlying disposition to be more receptive to certain persuasive strategies). Based on our analysis, the following strategies were perceived as most persuasive: personalization, reminder, commitment, self-monitoring, rewards, customization, authority, and scarcity. Interestingly, the data revealed differences between perceived persuasiveness and individual susceptibility to persuasion, indicating that both constructs measure distinct aspects of persuasiveness. Our results are relevant to designers and developers of persuasive systems by providing valuable insights about the most promising persuasive strategies and their practical implementation when designing for persons with COPD.

Keywords

Chronic obstructive pulmonary disease (COPD) Persuasive strategies Perceived persuasiveness Individual susceptibility to persuasion 

Notes

Acknowledgements

This research has partly been funded by the Vienna Business Agency under contract no. ID 1605387 (SmartCOPDTrainer).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Beatrix Wais-Zechmann
    • 1
  • Valentin Gattol
    • 1
  • Katja Neureiter
    • 1
  • Rita Orji
    • 2
  • Manfred Tscheligi
    • 1
    • 3
  1. 1.AIT Austrian Institute of TechnologyViennaAustria
  2. 2.Faculty of Computer ScienceDalhousie UniversityHalifaxCanada
  3. 3.University of SalzburgSalzburgAustria

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