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Modeling Gender Differences in Healthy Eating Determinants for Persuasive Intervention Design

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Persuasive Technology (PERSUASIVE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7822))

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Abstract

The onset of many health conditions, such as obesity and type 2 diabetes, can be prevented or at least delayed by adequate changes in diet. Various determinants of healthy eating – such as Weight Concern, Nutrition Knowledge, Concern for Disease, Social Influence, and Food Choice Motive – have been manipulated by persuasive technologies to motivate healthy eating behavior. However, the relative importance and the dynamic of interaction between the determinants of healthy behavior for males and females are still unknown. Understanding how the determinants vary across user groups is important, as it will help persuasive technology designers personalize their interventions to the target demographics, thereby increasing the effectiveness of the intervention. To investigate for possible variations in healthy eating determinants, we developed separate models of healthy eating determinants for males and females. The models, which are based on a quantitative study of 228 (124 males and 104 females) participants, reveal some similarities and differences in the interactions between the determinants of healthy eating behavior. Based on the result from our models, we highlight some gender-inclusive and gender-specific approaches to persuasive intervention design.

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Orji, R.O., Vassileva, J., Mandryk, R.L. (2013). Modeling Gender Differences in Healthy Eating Determinants for Persuasive Intervention Design. In: Berkovsky, S., Freyne, J. (eds) Persuasive Technology. PERSUASIVE 2013. Lecture Notes in Computer Science, vol 7822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37157-8_20

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  • DOI: https://doi.org/10.1007/978-3-642-37157-8_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37156-1

  • Online ISBN: 978-3-642-37157-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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