The content of Instagram posts featuring ultra-processed products through the lens of the heuristic-systematic model

REDES SOCIALES

POLITICA ALIMENTARIA

NUTRICIÓN

ALIMENTOS ULTRAPROCESADOS

MARKETING

BIBLIOGRAFIA NACIONAL QUIMICA

2023

Digital marketing has seen a rapid rise in the last decade as a consequence of the increased popularity of social media. However, few studies so far have analyzed the prevalence and persuasive power of digital marketing of ultra-processed products. The present study aimed at: (i) analyzing the content of Instagram posts of ultra processed products through the lens of the heuristic-systematic model, and (ii) evaluating the influence of the content of the posts on user interactions. A search for Instagram accounts of ultra-processed products was per formed using a master list of products commercialized in the two most popular online supermarkets in Uruguay. For each of the identified Instagram accounts, all the content posted in a 6-month period was recorded (August 15th, 2020 to February 15th, 2021). The posts were analyzed using content analysis based on inductive coding, and gradient boosting models (GBMs) were used to address the second study objective. A total of 2178 Instagram posts promoting specific ultra-processed products or brands were identified. The posts included a diverse set of cues to trigger both systematic and heuristic processing. References to the pleasure derived from product con sumption as well as health-related cues were most prevalent. The GBM showed that references to contests and raffles and invitations to interact encouraged users to engage with the posts through posting comments. Taken together, results stress the need to implement comprehensive regulatory approaches to reduce exposure to and the power of digital marketing of ultra-processed products given the harmful health-related consequences associated with excessive consumption of such products

Appetite Volumev.181, 2023. -- e106393

Elsevier

2023

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13 p.

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Artículo

10.1016/j.appet.2022.106393

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