Abstract
Health communication campaigns have been used to address many of the most prevalent non-communicable disease risk factors, such as physical inactivity. Typically, campaigns are shared via mass media to reach a high proportion of the population and at a low cost per head. However, the mes-sages shared are in direct competition with other campaigns, such as prod-uct marketing, which can result in the campaign not being seen adequately to lead to behaviour change. Moreover, as health campaigns are shared widely, the messages may not be understood or considered appropriate by certain audiences due to their broad nature. This can lead to unintended consequences, such as inadvertent social norming of the risk behaviour. To improve the success of health communication campaigns, they should be based on theory, with the theory of planned behaviour, the elaboration like-lihood model, and the extended parallel process model, three of the most widely used. Such theories highlight the importance of targetting a cam-paign to the audience. Targetting a health communication campaign in-volves considering the audience in the development and dissemination of the message. Campaigns could also be co-developed with the audience in question to ensure relevance. Digital technologies such as machine learn-ing and artificial intelligence can be used to tailor messages to the target audience effectively. Examples of targetted and broad health communica-tion campaigns are presented.
More Information
Identification Number: | https://doi.org/10.21814/uminho.ed.46 |
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Status: | Published |
Refereed: | Yes |
Publisher: | UMinho Editora/CECS |
Depositing User (symplectic) | Deposited by Blomfield, Helen on behalf of Tench, Ralph |
Date Deposited: | 01 Dec 2021 17:04 |
Last Modified: | 11 Jul 2024 21:04 |
Item Type: | Book Section |