Learning to Stop Smoking: Understanding Persuasive Applications’ Long-Term Behavior Change Effectiveness Through User Achievement Motivation | SpringerLink
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Learning to Stop Smoking: Understanding Persuasive Applications’ Long-Term Behavior Change Effectiveness Through User Achievement Motivation

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Persuasive Technology. Designing for Future Change (PERSUASIVE 2020)

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Abstract

Compromising smoking cessation applications’ effectiveness, many users relapse. We propose that long-term adoption of persuasive technology is (partly) dependent on users’ motivational orientation. Therefore, we studied the potential relationship between user’s achievement motivation and the long-term behavior change effectiveness of persuasive technology. One-hundred users of a smoking cessation app filled out a questionnaire assessing their motivational orientation and (long-term) behavior change rates. Based on research findings, we expected that participants with stronger learning goal orientation (who are focused on self-improvement and persistent when facing failure) would report a higher long-term behavior change success rate. In contrast, we expected that participants with a stronger performance goal orientation (focused on winning, for whom solitary failures can undermine intrinsic motivation) would report lower long-term success. Results confirmed our hypotheses. This research broadens our understanding of how persuasive applications’ effectiveness relates to user achievement motivation.

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Acknowledgements

We would like to thank Ahmet Aman (Eindhoven University of Technology) for important contributions and for running the study, and Mila Davids (Eindhoven University of Technology) for her valuable comments.

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Correspondence to Jaap Ham .

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Ham, J., Langrial, S.U. (2020). Learning to Stop Smoking: Understanding Persuasive Applications’ Long-Term Behavior Change Effectiveness Through User Achievement Motivation. In: Gram-Hansen, S., Jonasen, T., Midden, C. (eds) Persuasive Technology. Designing for Future Change. PERSUASIVE 2020. Lecture Notes in Computer Science(), vol 12064. Springer, Cham. https://doi.org/10.1007/978-3-030-45712-9_11

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  • DOI: https://doi.org/10.1007/978-3-030-45712-9_11

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