A web-based cross-sectional observational study on the analysis of information on diabetes on a social media platform (Instagram)

Abstract

Information related to health and chronic diseases is freely accessible to the public via social media platforms, such as Instagram. Proper knowledge and interventions can result in the management of diseases and improve patient behaviour while misinformation leads to poor patient outcomes. To analyse the relevance and authenticity of information about diabetes available on the social media platform (Instagram). The study was a web-based cross-sectional observational study without direct human participation. Data was collected from the top-performing 600 posts on Instagram, under the top six key search words related to diabetes and its management. The collected data was further analysed in Microsoft Excel and reviewed according to the latest WHO guidelines on diabetes. Only 448 out of 600 posts were found to be relevant to the study. While only 142 posts (31.70%) had amassed more than 500 likes, none of the posts had more than 500 comments each. 176 posts (39.26%) originated from unverified sources whereas 46 posts (10.27%) were contributed by doctors. Only 79 posts (17.63%) had any description of diabetes as a disease. Information on prevalence, aetiology, prevention, treatment or mortality was unavailable in 413 (92.19%), 381 (85.04%), 309 (68.97%), 338 (75.45%) and 427 (95.31%) posts respectively. The authenticity of the information was not determined in 221 posts (49.33%) whereas misinformation was seen in 19 posts (4.24%). Social media platforms are beneficial to public health, provided verified information and guidelines issued by organisations such as the World Health Organisation are implemented and promoted.