Abstract

Communicating climate risks to vulnerable groups motivating them to take adaptive actions remains a significant challenge in many populations, especially to children. The theory of reasoned action (TRA) suggests that attitude and subjective norms are important for persuasive communication. This study assesses how to apply TRA, its constructs and other relevant factors to predict behavior intention and beliefs and to change behavior tendency. The randomized field experiment method was applied to explore the differences between pre- and post-communication treatments (2 × 2 design). Can Tho city, located in the Mekong Delta of Vietnam, was selected as the research context because of its vulnerability to climate change. The results show that, first, TRA was found to be a significant predictor model of children’s climate change behavior intentions. Second, attitude has a significant effect on the children’s intention to act while videos with subjective norm treatment had not. The treatment interaction of both constructs also had a significant effect. Third, TRA theory-based treatments are positively associated with changes in children’ salient beliefs on attitude and normative belief on social norm toward climate change. In addition, past practices, knowledge and gender are further factors that influence children’s behavior intentions. A theory-inspired design of communication strategy allows the prediction and influencing of intentions. This finding has strong implications for both research and development in Vietnam.

Details

Title
Theory of Reasoned Action as a Framework for Communicating Climate Risk: A Case Study of Schoolchildren in the Mekong Delta in Vietnam
Author
Nguyen, Quynh Anh; Hens, Luc; MacAlister, Charlotte; Johnson, Lester; Lebel, Boripat; Sinh Bach Tan; Nguyen, Hung Manh; The Ninh Nguyen; Lebel, Louis
First page
2019
Publication year
2018
Publication date
2018
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2108752008
Copyright
© 2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.