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Exploring nutrition misinformation on social media platforms

Published online by Cambridge University Press:  21 May 2025

R. Diyab
Affiliation:
Nutrition and Dietetics, Sydney Nursing School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
J. Grgurevic
Affiliation:
Nutrition and Dietetics, Sydney Nursing School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
R. Roy
Affiliation:
Nutrition and Dietetics, Sydney Nursing School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
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Abstract

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Social media platforms such as Instagram and TikTok have transformed how individuals seek and engage with dietary advice, leading to the rapid propagation of unverified nutrition information that can result in poor dietary choices, contribute to disordered eating and broader health issues(1). This study aims to measure the accuracy and frequency of nutrition misinformation, identify the types of thematic misinformation, and understand user engagement metrics on Instagram and TikTok. A mixed-methods approach was employed, analysing 500 posts (250 from each platform) collected over a six-month period from September 15, 2023, to March 15, 2024, using keywords like healthy eating, healthy food, diet, and weight loss. Posts were evaluated using a modified, previously developed, Social Media Evaluation Checklist(2) and evidence coding framework to measure accuracy. Results indicated a higher prevalence of misinformation on TikTok compared to Instagram, with a significant portion (p < 0.05) of users lacking relevant credentials. The most common characteristic was cooking/recipes and meal plans. TikTok posts with mostly accurate and completely inaccurate information had higher engagement than Instagram posts. TikTok had a larger proportion of completely inaccurate posts (10.8%), mainly related to weight loss. Descriptive statistics for engagement metrics showed TikTok posts had significantly (p < 0.05) higher likes and comments compared to Instagram posts across various accuracy levels. For Instagram, completely accurate posts had a mean of 4,318 likes and 40 comments, while mostly accurate posts had a mean of 25,153 likes and 186 comments. For TikTok, completely accurate posts had a mean of 146,327 likes and 423 comments, mostly accurate posts had a mean of 75,804 likes and 483 comments. An independent t-test revealed significant (p < 0.05) differences in likes and comments between platforms for posts with varying accuracy levels. The study highlights the need for social media platforms to verify the qualifications of individuals providing nutrition advice and implement measures to promote accurate information. Further research is necessary to develop effective strategies to mitigate the spread of misinformation via social media platforms and its impact on public health.

Type
Abstract
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Nutrition Society

References

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