Abstract
Affects in warning pictorials are essential in the warning effectiveness such as comprehension and hazard perception. The purpose of this research were to design and validate emotional warning pictorials for alcohol container labels in order to increase awareness of risks from alcohol consumptions. Survey and brainstorming techniques were used to collect the idea of possible affective warning pictorials. All ideas generated through those techniques were grouped for finding candidate pictorials. Sixty affective warning pictorials were designed and categorized into three affective state groups equally as positive, neutral, and negative. Forty Thai male participants participated in this study for affective warning pictorials’ validation. Participants were asked with agreement to attend the affective manipulation by watching pictures from the International Affective Picture System (IAPS) to adjust participants’ affective state as neutral state before starting the experiment. The Self-Assessment Manikin was used to assess valence and arousal of participants after seeing each of sixty affective warning pictorials. The result showed that affective warning pictorials were able to evoke specific affective state of warning pictorials to participants such as positive, neutral, and negative state. Affective warning pictorials from this research can be implemented as the alcohol container labels. The direction of future research will be focused on the study of comprehension, risk perception, and motivation to stop drinking alcohol after participants perceive affective warning pictorials.
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Acknowledgments
Authors gratefully acknowledge to the supporter, Pat-Arin Chanduen, for her invaluable inputs, suggestions, and supports based on her experiences in design affective warning pictorials in tobacco label throughout this research.
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Authayarat, W., Kasornsuwan, P., Jiamsanguanwong, A. (2018). Design and Validation of Affective Warning Pictorials on Alcohol Container Labels. In: Chung, W., Shin, C. (eds) Advances in Affective and Pleasurable Design. AHFE 2017. Advances in Intelligent Systems and Computing, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-60495-4_4
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DOI: https://doi.org/10.1007/978-3-319-60495-4_4
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