A Twitter Discourse Analysis of Negative Feelings and Stigma Related to NAFLD, NASH and Obesity

Jeffrey V. Lazarus; Christine Kakalou; Adam Palayew; Christina Karamanidou; Christos Maramis; Pantelis Natsiavas; Camila A Picchio; Marcela Villota-Rivas; Shira Zelber-Sagi; Patrizia Carrieri

Disclosures

Liver International. 2021;41(10):2295-2307. 

In This Article

Discussion

This study set out to analyse the relationship between NAFLD/NASH and stigmatizing obesity-related content on Twitter utilizing an in-house platform to host and visualize the data. We found that very few tweets contained NAFLD/NASH and obesity content. We also examined tweets just containing obesity terms and found that the obesity-specific rhetoric was very negative on Twitter. For the NAFLD and NASH tweets, some of the shared content was medical misinformation, such as 'quick cures' and 'super smoothies' for NAFLD; however, the quantity of such misinformation was not evaluated in this study. Further in the NAFLD/NASH dataset, we found bot retweeting of links with misinformation claiming herbal/natural remedies for fatty liver when annotating the data.

A certain portion of the NAFLD and especially the NASH discourse was around the promotion of newly published scientific research. A portion of the NASH Twitter content screened included discussion about recent trials and stocks of various companies investing in NASH therapeutics and diagnostics. For both NAFLD and NASH, we found diet misinformation and 'get better' cures and simply classified them as 'information', making no appraisal about whether information was misinformation or not, as we wanted to be as objective as possible in the labelling process. We did, however, find that there were more untrustworthy URLs than trustworthy URLs in the NAFLD and NASH datasets. Diet-related unprofessional advice and tips using Twitter or other internet channels is also common in other diseases. For example, for bowel disease, Twitter is becoming a growing space for online conversation, namely regarding associated symptoms and alternative treatments including tweets containing mentions of foods and diets.[23] Such medical and diet-related misinformation may point to an urgent need for increased availability of reliable information tailored to the public on all aspects of NAFLD, especially treatment options.

Furthermore, positive rhetoric was often in response to negative rhetoric, whereas negative rhetoric was normally in response to an event or another tweet. The geographic location of the majority of the positive content regarding obesity was in North America and Europe with some in Australia and all mainly in metropolitan areas. These two observations could be tied to each other because of the temporality in the sampling algorithm of tweets generated around certain events, which could disproportionally affect the content. For example, in our study period, a large amount of content was generated the night that the singer Lizzo performed at the Video Music Awards, causing a spike in fatphobic content specifically around Lizzo. However, this also spurred content where people denounced fat shaming. Further research could focus on network analysis to estimate the reach of the negative vs positive tweets and consequently their influence on enhancing or shifting affective obesity discourse.

Stigma and disease on social media have been previously studied. A study looking at Alzheimer's disease stigma on Twitter found that a substantial proportion (21.1%) of Alzheimer's disease-related posts contained ridicule and perpetuated stigma.[24] Furthermore, a study exploring how seizures were being portrayed on Twitter found that 41% of seizure tweets were derogatory.[25] Another study, examining COVID-19 stigma on Twitter during the early stages of the pandemic, December 2019-March 2020, found that about 25% of the tweets studied included stigmatizing content.[26] On the other hand, a study on mental illness and bipolar disorder on Twitter looking at tweet spikes (dates with the most tweets during a 3-month period) found that, overall, most messaging was supportive but that, nonetheless, bipolar disorder tweets contained more stigma and less support compared to mental illness ones.[27] Additionally, a study looking at lung cancer talk on Twitter, Facebook and Macmillan.org.uk found that Twitter posts showed the most companionship support while emotional support was most prominent on Macmillan.org.uk, with Facebook following closely behind; Facebook also revealed spiritual support and there was little evidence of stigma on any of the platforms.[28]

In terms of obesity or weight stigma, two studies exploring social media platforms, including Twitter, found that negative weight stigmatization was the most common theme.[15,29] One of them, which performed content analysis of weight stigma on Twitter, found that most messages (57%) were stigmatizing and classified people with overweight/obesity as gluttonous, unattractive, undesirable, sedentary and incompetent.[29] Another study looking at retweets about obesity on Twitter found that most (55.8%) tweets collected for analysis were jokes about weight or obesity and that derogatory humour was retweeted more than non-derogatory humour.[30]

As for other diseases and obesity, a study examining the connections between obesity and cancer on Twitter and Facebook found that Twitter contained more negative sentiments when compared to Facebook and that posts with both negative and positive sentiments tended to frame overweight people and cancer patients distinctly; numerous posts implied that being overweight was a result of individual responsibility and that having cancer was outside personal control.[31] Given the vast volume of obesity-related discussions on Twitter, automated techniques to classify the sentiment expressed can provide a reliable and fast tool for public health and health communication experts to monitor obesity discourse and detect possible shifts in perceptions in a timely manner. Furthermore, Twitter initiatives such as @EndWeightStigma, whose aim is to end weight stigma and discrimination by asking Twitter users to send them examples of weight stigma and discrimination, can help to further shed light on and tackle this ongoing issue.[32]

Similar to obesity, NAFLD is often considered to be a self-inflicted disease because of its strong association with obesity, an unhealthy diet and low physical activity. Apart from lean NAFLD, which affects 7%-20% of individuals with NAFLD,[33] it is wrongly assumed that individuals' decisions are independent of structures in society that drive personal choice. There is a common notion that the responsibility for a healthy diet lies with the individual and that high body weight is caused by self-controlled attitudes. This perception underestimates societal and environmental factors that contribute to the development of obesity, which could lead to attitudes that facilitate weight-related stigmatization.[34] Collectively, research examining weight stigma illustrates a range of potential adverse health consequences that are physical, psychological and behavioural in nature (overeating and low motivation for physical activity), which can reduce quality of life for individuals with obesity and may ultimately interfere with efforts to improve their health and lose weight.[35]

One might assume that the lack of negative tweets on NAFLD is a positive finding, but it more probably reflects unawareness of NAFLD and its close relation with obesity and a poor lifestyle.[36,37] In addition, NAFLD is a silent and hidden disease[38,39] unlike obesity, which is more easily observed and diagnosed and, thus, an easier target for stigma. Once awareness raising leads to NAFLD becoming common knowledge in the general population, it may draw negative attention, in part because it contains the term 'non-alcoholic' in the name; therefore, reducing obesity-related stigma and raising awareness around NAFLD are both crucial for preventing NAFLD-related stigma. This can be achieved in part through regular social media presence by respected liver health organizations that include positive, evidence-based messaging and links to additional reliable information.

processing....