Hostname: page-component-54dcc4c588-9xpg2 Total loading time: 0 Render date: 2025-10-03T07:25:08.083Z Has data issue: false hasContentIssue false
Accepted manuscript

Examination of social media nutrition information related to multiple sclerosis: A cross-sectional social network analysis

Published online by Cambridge University Press:  18 September 2025

Yasmine Probst*
Affiliation:
School of Medical, Indigenous and Health Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia Illawarra Health and Medical Research Institute, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia
Emiliana Saffioti
Affiliation:
School of Medical, Indigenous and Health Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia
Sarah Manche
Affiliation:
School of Medical, Indigenous and Health Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia
Melissa Eaton
Affiliation:
School of Medical, Indigenous and Health Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia Illawarra Health and Medical Research Institute, University of Wollongong, Northfields Avenue, Wollongong, NSW, 2522, Australia
*
*Corresponding author: University of Wollongong, Northfields Avenue, Wollongong NSW 2522. yasmine@uow.edu.au.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective:

Multiple sclerosis (MS) is a chronic neurodegenerative condition with increasing global prevalence. People living with multiple sclerosis (plwMS) have reported limited guidance relating to nutrition information. Paired with varied health literacy levels, this makes plwMS susceptible to nutrition misinformation.

Design:

A cross-sectional online social network analysis (SNA) examining nutrition information for MS.

Setting:

A systematic SNA using Twitter/X and YouTube platforms using NodeXL to summarise metrics. Quality was assessed using the QUEST tool. Content analysis of YouTube videos was synthesised into themes for misinformation.

Participants:

Online publicly available social media user posts and video content.

Results:

Twitter/X SNA revealed keywords were used most by an account representing 72.8% of the user network with common diet mentions including Wahls (57 times), paleo (15 times) and ketogenic (11 times). ‘Favourite count’ metrics were strongly correlated with ‘repost count’ (r=0.83, p=0.000). Videos which endorsed a diet were more likely to have a lower QUEST score. User engagement metrics were higher for lower quality videos. The quality of online nutrition information relating to MS was moderate (61%). Physicians were the most likely source of nutrition information endorsing a diet for MS. The content analysis identified a knowledge gap for both medical professionals and plwMS.

Conclusions:

Nutrition misinformation for MS occurs on social media and information quality is variable. Audiences need to be cautioned about users with large followings and evaluate the credibility of all information. This study reiterates the importance of evidence-based information for the MS community.

Information

Type
Research Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Nutrition Society