1. Model Tarikan Metafora Visual Ketakutan bagi Meningkatkan Perhatian kepada Pesanan Khidmat Awam.
- Author
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Ahmad, Zul Imran, Salleh, Mohd Azul Mohamad, and Mustaffa, Normah
- Abstract
The role of Public Service Announcements (PSAs) in capturing the public's attention to awareness messages is increasingly challenging due to the advancements in visual technology that have elevated audience preferences. In order to maximize attention and induce behavioral changes, the common use of fear as a visual rhetoric (RV) threat in various local campaigns, especially those involving health, has been employed. However, implementations of fear appeals lacking empirical foundations often fail to engage attention and instead motivate defensive audience responses. Fear-based RV failures are attributed to the lack of a persuasive fear model specifically tailored to negotiate with the audience's knowledge and experiences. These weaknesses are more noticeable among target audiences exhibiting specific tendencies, such as video game addiction in cases of Problematic Gaming (PG) in Malaysia. This raises questions about the suitability of fear-based RV approaches for attention-grabbing and their risk of rejection. Consequently, existing PSAs attraction strategies necessitate a more cognitively and affectively sensitive concept for the audience. Therefore, the objective of this paper is to discuss and propose the concept of Fear-Induced Visual Metaphors (FVM) as a new form of PSA RV. Choosing the best stimulus construct of MV from the typologies of Pictorial Metaphor Theory (TMB), Visual Rhetoric Theory (TRV), or Visual Structure Concept (KSV) proven effective in commercial advertising, combined with threat components from the Extended Parallel Process Model (EPPM) fear appeal model, aims to enhance the potential for attention-grabbing. Theoretically, FVM attract the audience's attention through significantly superior cognitive and affective allure compared to standard visual or rhetoric. Conclusions from this study are expected to contribute a testable and empirically validated conceptual framework. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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