Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter

Responses to (Un)healthy advice: Processing and acceptance of health content creators' nutrition misinformation by youth

Health information, particularly about nutrition, has flourished on social media in recent years. However, these claims often lack proper scrutiny enhancing the risk of misinformation. Nutrition misinformation on social media can originate from various sources including influencers, celebrities, and (freelance) journalists, who often have substantial reach. We conducted a between-subjects experiment, manipulating presence of misinformation and source type (influencer/celebrity/journalist), among N = 480 youth aged 16-22 years. We investigated how nutrition misinformation affects their nutrition (mis)beliefs and dieting. We also tested the moderating role of participants' issue involvement and the mediating role of the sources' perceived expertise. We found that youth remained largely unaffected by nutrition misinformation. However, perceived source expertise acted as a heuristic cue to determine trust in an unknown health content creator. This perceived expertise, in turn, increased perceived healthiness of food products mentioned by the 'expert' content creator regardless of misinformation exposure.

Hidden hunger: from a plant biologist's perspective

In recent years, changes in dietary patterns from an omnivore diet to a moderate-to-restrictive diet that includes more plant food are becoming popular for various reasons and the associated health benefits. Despite the increased consumption of plant food as recommended by these seemingly healthy diets, micronutrient deficiency is still prevalent particularly among the health-conscious populations. The aim of this review is to help guide interventions by understanding micronutrient deficiency trends from a dietary habit and plant physiology context. In this review, the author discusses how modern agricultural practices coupled with climate change, and with particular emphasis on the extreme dietary habits that lack variation and excessive consumption, may contribute to an increased ingestion of antinutrients which in turn potentially exacerbate vitamin and mineral deficiencies. While plants possess a wide range of secondary metabolites that exert beneficial health effects, some of these compounds are also antinutrients that interfere with the digestion and absorption of nutrients and micronutrients. Furthermore, the article also raises questions concerning the fate of antinutrient traits in future crops that were to be redesigned with improved stress tolerance, and the impacts it may have on human nutrition and the environment. © 2025 Society of Chemical Industry.

Diet culture on TikTok: a descriptive content analysis

OBJECTIVE

To investigate how dieting is portrayed on TikTok and the potential implications for public health considering the effect of diet culture on eating disorders amongst young people.

DESIGN

A cross-sectional descriptive content analysis of 250 videos from the five most popular diet-related hashtags. A codebook was developed to analyse the content of the videos and collect the engagement for each video (likes, comments and shares).

SETTING

TikTok website.

PARTICIPANTS

There were no participants in this study.

RESULTS

More than half of the videos portrayed 'body checking', a potentially harmful practice for body image. Of the videos that represented body image, almost half represented body image negatively. However, most videos promoted the idea of 'healthy eating', and only 6·4 % displayed disordered eating behaviours. Over half of the videos provided dietary advice, and of those videos, most content creators claimed to be experts (64 %). Claiming expertise was not significantly associated with engagement; however, the use of humour was significantly associated with engagement. Additionally, males were more likely than females to disclose their goals of the diet.

CONCLUSIONS

Overall, it appears that TikTok is commonly used to share nutrition tips and personal experiences around dieting and eating in general, often employing humour as an effective technique. The popularity of the platform and rapid dissemination of information would be a useful tool for health professionals, especially those working with eating disorders, to utilise.

Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis

BACKGROUND

Data from the social media platform X (formerly Twitter) can provide insights into the types of language that are used when discussing drug use. In past research using latent Dirichlet allocation (LDA), we found that tweets containing "street names" of prescription drugs were difficult to classify due to the similarity to other colloquialisms and lack of clarity over how the terms were used. Conversely, "brand name" references were more amenable to machine-driven categorization.

OBJECTIVE

This study sought to use next-generation techniques (beyond LDA) from natural language processing to reprocess X data and automatically cluster groups of tweets into topics to differentiate between street- and brand-name data sets. We also aimed to analyze the differences in emotional valence between the 2 data sets to study the relationship between engagement on social media and sentiment.

METHODS

We used the Twitter application programming interface to collect tweets that contained the street and brand name of a prescription drug within the tweet. Using BERTopic in combination with Uniform Manifold Approximation and Projection and k-means, we generated topics for the street-name corpus (n=170,618) and brand-name corpus (n=245,145). Valence Aware Dictionary and Sentiment Reasoner (VADER) scores were used to classify whether tweets within the topics had positive, negative, or neutral sentiments. Two different logistic regression classifiers were used to predict the sentiment label within each corpus. The first model used a tweet's engagement metrics and topic ID to predict the label, while the second model used those features in addition to the top 5000 tweets with the largest term-frequency-inverse document frequency score.

RESULTS

Using BERTopic, we identified 40 topics for the street-name data set and 5 topics for the brand-name data set, which we generalized into 8 and 5 topics of discussion, respectively. Four of the general themes of discussion in the brand-name corpus referenced drug use, while 2 themes of discussion in the street-name corpus referenced drug use. From the VADER scores, we found that both corpora were inclined toward positive sentiment. Adding the vectorized tweet text increased the accuracy of our models by around 40% compared with the models that did not incorporate the tweet text in both corpora.

CONCLUSIONS

BERTopic was able to classify tweets well. As with LDA, the discussion using brand names was more similar between tweets than the discussion using street names. VADER scores could only be logically applied to the brand-name corpus because of the high prevalence of non-drug-related topics in the street-name data. Brand-name tweets either discussed drugs positively or negatively, with few posts having a neutral emotionality. From our machine learning models, engagement alone was not enough to predict the sentiment label; the added context from the tweets was needed to understand the emotionality of a tweet.

The Impact of Following Instagram Influencers on Women's Body Dissatisfaction and Eating Disorder Symptoms

According to the Tripartite Influence Model, social media is one of the primary sources influencing women's body dissatisfaction. However, the role of social media influencers as a potential driver for impacting users' body image evaluation when disseminating content on social networks has been little investigated. The present research aims to explore the relationship between following three Instagram influencers (i.e., nutrition, fitness, and entertainment) and eating disorder (ED) symptoms and body dissatisfaction among a group of female users. A sample of 5060 women (mean age = 35.33 ± 9.33) were recruited with the collaboration of three Italian influencers, and self-reported questionnaires were administered. Women who followed the nutritional influencer account reported significantly higher scores on ED symptoms and body dissatisfaction than women who followed the fitness and entertainment influencer accounts (η2 = 0.05 and η2 = 0.02, respectively). Overall, following nutrition and fitness accounts (compared to entertainment accounts) and spending more time daily on social networks positively predicts ED symptoms (β = 0.28, p < 0.001, β = 0.10, p < 0.001, β = 0.11, p < 0.001, respectively) and body dissatisfaction (β = 0.07, p < 0.001, β = 0.04, p < 0.001, β = 0.07, p < 0.001, respectively). Moreover, following nutritional influencers compared to fitness influencers positively predicts ED symptoms (β = 0.17, p < 0.001) but not body dissatisfaction. The current results suggest that being exposed to dieting and weight loss topics on social media might be particularly harmful for individuals with specific vulnerabilities. Practical implications will be discussed.

The use of sentiment and emotion analysis and data science to assess the language of nutrition-, food- and cooking-related content on social media: a systematic scoping review

Social media data are rapidly evolving and accessible, which presents opportunities for research. Data science techniques, such as sentiment or emotion analysis which analyse textual emotion, provide an opportunity to gather insight from social media. This paper describes a systematic scoping review of interdisciplinary evidence to explore how sentiment or emotion analysis methods alongside other data science methods have been used to examine nutrition, food and cooking social media content. A PRISMA search strategy was used to search nine electronic databases in November 2020 and January 2022. Of 7325 studies identified, thirty-six studies were selected from seventeen countries, and content was analysed thematically and summarised in an evidence table. Studies were published between 2014 and 2022 and used data from seven different social media platforms (Twitter, YouTube, Instagram, Reddit, Pinterest, Sina Weibo and mixed platforms). Five themes of research were identified: dietary patterns, cooking and recipes, diet and health, public health and nutrition and food in general. Papers developed a sentiment or emotion analysis tool or used available open-source tools. Accuracy to predict sentiment ranged from 33·33% (open-source engine) to 98·53% (engine developed for the study). The average proportion of sentiment was 38·8% positive, 46·6% neutral and 28·0% negative. Additional data science techniques used included topic modelling and network analysis. Future research requires optimising data extraction processes from social media platforms, the use of interdisciplinary teams to develop suitable and accurate methods for the subject and the use of complementary methods to gather deeper insights into these complex data.

Identifying methods used to manage weight and shape by first year university students: A qualitative analysis

OBJECTIVE

To identify current strategies used by first-year university students to lose weight, maintain weight, or change their body shape.

METHODS

First-year university students (n = 661) completed an open-ended, web-based survey. Cross-sectional data were analyzed qualitatively using a reflexive thematic approach to identify strategies used to lose weight, maintain weight, or alter body shape/composition. Thematic maps were constructed for each weight- and shape-related goal.

RESULTS

Four main types of strategies were used to achieve all three weight or shape-related goals among first-year college students: changes in diet, changes in exercise, self-monitoring, and disordered eating. One behavioral strategy observed across all weight-related goals was prioritizing protein consumption, including protein gained from supplementation. However, there were also differences in strategies by weight- or shape-related goal. For example, only participants aiming to lose or maintain weight reported mindful strategies for monitoring diet. Individuals aiming to alter body composition reported heterogeneity in goal-related intentions, targeting specific body parts through exercise, and extensive supplement use.

CONCLUSIONS

First-year college students use a variety of strategies to manage their weight and shape. Some strategies were observed across goals, whereas others are specific to the weight- or shape-related goal. More research is needed to understand the impacts, both positive and negative, of using the strategies identified in the present study.

Digging into digital buffets: A systematic review of eating-related social media content and its relationship with body image and eating behaviours

Recently, researchers have started investigating the influence of eating-focused social media content on viewers' body image and eating behaviour. The current systematic review collates the evidence for the relationship between exposure to eating-related social media content and people's body image, disordered eating, food consumption, and eating-related opinions. Following PRISMA guidelines, searches were conducted on five databases (i.e., Medline, PsycINFO, Web of Science, Scopus, and ProQuest), resulting in 38 eligible studies that examined the link between eating-related content and body image, eating behaviour and/or viewers' perceptions. Evidence showed positive relationships between exposure to certain material on social media (e.g., fast-food advertisements, clean eating, eating videos) and body image concerns, disordered eating, and consumption of, or a willingness to consume the foods seen on social media; however, studies that focused on 'healthy food' content showed no such link. Viewers expressed mixed feelings towards content such as nutrition information and mukbang videos which record hosts eating a large amount of food. Future research would benefit from a consistent measure of exposure to different eating-related content. There is also a need for more experimental research to examine the impact of watching different types of eating videos on body image, disordered eating, and food consumption.

Nutrition knowledge and health vulnerability of mothers of pre-school children in north-central, Nigeria

OBJECTIVE

This study explores the contribution of nutrition knowledge to the health status of pre-school children's mothers in Niger State, North-Central, Nigeria.

DESIGN

The study is a descriptive cross-sectional design using a quantitative data collection method.

SETTING/PARTICIPANTS

A multi-stage sampling technique was used to recruit 450 mothers of pre-school children across Niger state, Nigeria. Chi-square and linear regression were used to test the level of statistical significance (at p < 0.05). Socioeconomic and demographic information, anthropometric indices and nutrition knowledge were obtained using semi-structured questionnaires. Feeding patterns were also assessed using a qualitative 7-day dietary recall.

RESULT

The results showed that the majority (63.8%) of the mothers were within 26-35 years, and more than half (51.6%) of the mothers lacked knowledge of a "balanced diet". Fruits, vegetables, and dairy products were the least consumed food group among the mothers (7.1% and 9.1%, respectively). Place of residence, occupation, and method of waste disposal were significantly associated with maternal minimum dietary diversity adequacy (p<0.05). Over half (57.6%) of the mothers were within the normal BMI range, and the mean waist/hip ratio was 0.82± 0.08. Social media/online was the most (36.4%) explored source of nutrition information among the mothers. This study shows no significant association between nutrition knowledge and adequacy of minimum dietary diversity among the mothers of preschool children (p = 0.09, χ2 = 13.682).

CONCLUSION

Dietary diversity among mothers was associated with the socioeconomic status and BMI of the mothers, which were strong determinants of meal quality and health outcomes in Nigeria and other developing countries experiencing food insecurity.

Nutrition and Food Literacy: Framing the Challenges to Health Communication

Nutrition and food literacy are two important concepts that are often used interchangeably, but they are not synonymous. Nutrition refers to the study of how food affects the body, while food literacy refers to the knowledge, skills, and attitudes necessary to make informed decisions about food and its impact on health. Despite the growing awareness of the importance of food literacy, food illiteracy remains a global issue, affecting people of all ages, backgrounds, and socioeconomic status. Food illiteracy has serious health implications as it contributes to health inequities, particularly among vulnerable populations. In addition, food literacy is a complex and multidisciplinary field, and there are numerous challenges to health communication that must be addressed to effectively promote food literacy and improve health outcomes. Addressing food illiteracy and the challenges to health communication is essential to promote health equity and improve health outcomes for all populations.

A Content Analysis of Persuasive Appeals Used in Media Campaigns to Encourage and Discourage Sugary Beverages and Water in the United States

The frequent consumption of sugary beverages is associated with many health risks. This study examined how persuasive appeals and graphics were used in different media campaigns to encourage and discourage sugary beverages and water in the United States (U.S.) The investigators developed a codebook, protocol and systematic process to conduct a qualitative content analysis for 280 media campaigns organized into a typology with six categories. SPSS version 28.0 was used to analyze rational and emotional appeals (i.e., positive, negative, coactive) for campaign slogans, taglines and graphic images (i.e., symbols, colors, audiences) for 60 unique campaigns across the typology. Results showed that positive emotional appeals were used more to promote sugary beverages in corporate advertising and marketing (64.7%) and social responsibility campaigns (68.8%), and less to encourage water in social marketing campaigns (30%). In contrast, public awareness campaigns used negative emotional appeals (48.1%), and advocacy campaigns combined rational (30%) and emotional positive (50%) and negative appeals (30%). Public policy campaigns used rational (82.6%) and positive emotional appeals (73.9%) to motivate support or opposition for sugary beverage tax legislation. Chi-square analyses assessed the relationships between the U.S. media campaign typology categories and graphic elements that revealed three variables with significant associations between the campaign typology and race/ethnicity (χ²(103) = 32.445, p = 0.039), content (χ²(103) = 70.760, p < 0.001) and product image (χ²(103) = 11.930, p = 0.036). Future research should examine how positive persuasive appeals in text and graphics can promote water to reduce sugary beverage health risks.

Investigating the Role of Nutrition in Enhancing Immunity During the COVID-19 Pandemic: Twitter Text-Mining Analysis

BACKGROUND

The COVID-19 pandemic has brought to the spotlight the critical role played by a balanced and healthy diet in bolstering the human immune system. There is burgeoning interest in nutrition-related information on social media platforms like Twitter. There is a critical need to assess and understand public opinion, attitudes, and sentiments toward nutrition-related information shared on Twitter.

OBJECTIVE

This study uses text mining to analyze nutrition-related messages on Twitter to identify and analyze how the general public perceives various food groups and diets for improving immunity to the SARS-CoV-2 virus.

METHODS

We gathered 71,178 nutrition-related tweets that were posted between January 01, 2020, and September 30, 2020. The Correlated Explanation text mining algorithm was used to identify frequently discussed topics that users mentioned as contributing to immunity building against SARS-CoV-2. We assessed the relative importance of these topics and performed a sentiment analysis. We also qualitatively examined the tweets to gain a closer understanding of nutrition-related topics and food groups.

RESULTS

Text-mining yielded 10 topics that users discussed frequently on Twitter, viz proteins, whole grains, fruits, vegetables, dairy-related, spices and herbs, fluids, supplements, avoidable foods, and specialty diets. Supplements were the most frequently discussed topic (23,913/71,178, 33.6%) with a higher proportion (20,935/23,913, 87.75%) exhibiting a positive sentiment with a score of 0.41. Consuming fluids (17,685/71,178, 24.85%) and fruits (14,807/71,178, 20.80%) were the second and third most frequent topics with favorable, positive sentiments. Spices and herbs (8719/71,178, 12.25%) and avoidable foods (8619/71,178, 12.11%) were also frequently discussed. Negative sentiments were observed for a higher proportion of avoidable foods (7627/8619, 84.31%) with a sentiment score of -0.39.

CONCLUSIONS

This study identified 10 important food groups and associated sentiments that users discussed as a means to improve immunity. Our findings can help dieticians and nutritionists to frame appropriate interventions and diet programs.

Misinformation and Disinformation in Food Science and Nutrition: Impact on Practice

Food and nutrition are popular topics in the media and on social media. The ubiquity of social media has created new opportunities for qualified or credentialed experts in the scientific community to connect with clients and the public. It has also created challenges. Health and wellness gurus, or self-proclaimed experts, utilize social media platforms to garner attention through compelling narratives, build audience followings, and influence public opinion by sharing (often) misleading information about food and nutrition. The consequence of this can be the perpetuation of misinformation, which not only undermines a well-functioning democracy but also diminishes support for policies that are science or evidence based. Nutrition practitioners, clinician scientists, researchers, communicators, educators, and food experts need to encourage and model critical thinking (CT) to participate in our world of mass information and mitigate misinformation. These experts can play a vital role in the evaluation of information about food and nutrition against the body of evidence. This article explores the role of CT and ethics of practice in the context of misinformation and disinformation by providing a framework for engaging with clients and offering a checklist for ethical practice.

The role of IL-31 and IL-34 in the diagnosis and treatment of chronic periodontitis

This study was devoted to demonstrating the role of IL-31 and IL-34 in the diagnosis and treatment of chronic periodontitis (CP). From the results, we found that the IL-31 and IL-34 levels were significantly increased in GCF and serum of CP patients compared with healthy controls or obese patients. Meanwhile, the area under the curve results further verified the diagnostic potential of IL-31 and IL-34 in terms of discriminating CP from obese patients at the GCF and serum levels. Finally, after 1 year of continuous treatment, we found that IL-31 and IL-34 levels were decreased in CP, suggesting their potential as biomarkers in CP treatment response. Monitoring GCF and serum levels of IL-31 and IL-34 contributed to CP detection and treatment response.

Values and preferences influencing willingness to change red and processed meat consumption in response to evidence-based information: a mixed methods study

OBJECTIVES

The aim of the study is (1) to assess the extent to which omnivores are willing to stop or reduce their consumption of red and processed meat in response to evidence-based information regarding the possible reduction of cancer mortality and incidence achieved by dietary modification; (2) to identify socio-demographic categories associated with higher willingness to change meat consumption and (3) to understand the motives facilitating and hindering such a change.

DESIGN

During an initial computer-assisted web interview, respondents were presented with scenarios containing the estimates of the absolute risk reduction in overall cancer incidence and mortality tailored to their declared level of red and processed meat consumption. Respondents were asked whether they would stop or reduce their average meat consumption based on the information provided. Their dietary choices were assessed at 6-month follow-up. Additionally, we conducted semi-structured interviews to better understand the rationale for dietary practices and the perception of health information.

PARTICIPANTS

The study was conducted among students and staff of three universities in Krakow, Poland.

RESULTS

Most of the 513 respondents were unwilling to change their consumption habits. We found gender to be a significant predictor of the willingness. Finally, we identified four themes reflecting key motives that determined meat consumption preferences: the importance of taste and texture, health consciousness, the habitual nature of cooking and persistence of omnivorous habits.

CONCLUSIONS

When faced with health information about the uncertain reduction in the risk of cancer mortality and incidence, the vast majority of study participants were unwilling to introduce changes in their consumption habits.

Analysis of Content, Social Networks, and Sentiment of Front-of-Pack Nutrition Labeling in the European Union on Twitter

In recent years, concerted political efforts have been made at the national and European Union (EU) level to promote the consumption of healthy foods. The European Commission (EC) expressed the need for a harmonized and mandatory front-of-pack nutrition labeling (FOPL) system at the EU level. The EC will adopt the proposal by the end of 2022. Our research work aims to understand the public discourse on FOPL in the EU via Twitter, by analyzing tweet content, sentiment, and mapping network characteristics. Tweet search and data collection were performed using the Twitter application programming interface (API), with no time or language restrictions. The content was coded with the QRS Nvivo software package and analyzed thematically. Automatic sentiment analysis was performed with QSR Nvivo, and network analysis was performed with Gephi 0.9.2. A total of 4,073 tweets were posted, mostly from the UK, Spain, and France. Themes that have emerged from the discussion on Twitter include the types of food labeling, food industry, healthy vs. unhealthy foods in the context of food labeling, EU regulation, political conflicts, and science and education. Nutri-Score dominated the discussion on Twitter. General topics were perceived negatively by Twitter users with more positive sentiments toward the food industry, while negative sentiments were observed toward the discourse of political conflicts. The network analysis showed that a centralized communication was hardly existed between countries. Our results reveal that the discussion of FOPL on Twitter is limited to a very limited group of people, and it seems necessary to inform a wide range of consumers about existing and upcoming FOPL schemes. Educational programs should empower consumers to understand what a healthy diet is and how it relates to FOPL, regardless of the existing labeling system.

‘Exploring the Influence of Social Media Influencers on Intention to Attend Cervical Screening in the UK: Utilising the Theory of Planned Behaviour’

Objectives

Cervical cancer is 99.8% preventable when detected early; however, uptake of screening in the United Kingdom is at a 20-year low. Recently, a number of social media influencers have video logged about their experiences of cervical screening through narrative communication with their audience. Here we aimed to explore if accessing cervical screening information from a social media influencer can impact the theory of planned behaviour variables and predict intention to attend cervical screening appointments.

Design

Utilising a cross-sectional design a volunteer sample of 102 UK women (mean age = 28; SD = 3.10; range = 25–35) took part in an online questionnaire study.

Results

Hierarchical regression modelling revealed attitude as a significant predictor of intention to attend a cervical screening appointment and that social media influencers affect attitudes of their audience, indirectly influencing intention to attend.

Conclusion

Health messages communicated by social media influencers are effective in promoting positive attitudes but not directly influence intention to attend towards cervical screening. Further research should explore influencer impact on attitudes towards this health behaviour with the ultimate aim of increasing attendance and consequently saving lives.

Illusion of Truth: Analysing and Classifying COVID-19 Fake News in Brazilian Portuguese Language

Public health interventions to counter the COVID-19 pandemic have accelerated and increased digital adoption and use of the Internet for sourcing health information. Unfortunately, there is evidence to suggest that it has also accelerated and increased the spread of false information relating to COVID-19. The consequences of misinformation, disinformation and misinterpretation of health information can interfere with attempts to curb the virus, delay or result in failure to seek or continue legitimate medical treatment and adherence to vaccination, as well as interfere with sound public health policy and attempts to disseminate public health messages. While there is a significant body of literature, datasets and tools to support countermeasures against the spread of false information online in resource-rich languages such as English and Chinese, there are few such resources to support Portuguese, and Brazilian Portuguese specifically. In this study, we explore the use of machine learning and deep learning techniques to identify fake news in online communications in the Brazilian Portuguese language relating to the COVID-19 pandemic. We build a dataset of 11,382 items comprising data from January 2020 to February 2021. Exploratory data analysis suggests that fake news about the COVID-19 vaccine was prevalent in Brazil, much of it related to government communications. To mitigate the adverse impact of fake news, we analyse the impact of machine learning to detect fake news based on stop words in communications. The results suggest that stop words improve the performance of the models when keeping them within the message. Random Forest was the machine learning model with the best results, achieving 97.91% of precision, while Bi-GRU was the best deep learning model with an F1 score of 94.03%.

Perception of Healthcare Providers About the Use of Social Media to Manage a Healthy Diet in Saudi Arabia

Purpose: The objective of this study is to investigate the perceptions of healthcare providers about the use of social media for healthy diet management in Saudi Arabia.

Participants and Methods: A cross-sectional study was designed to investigate the use of social media healthy diet management. The sample constituted 308 healthcare professionals from Saudi Arabia. The social media application, WhatsApp is employed to distribute the questionnaire, which has achieved a response rate of 50.61%. Out of the total participants, 55% of the participants were under 30 years of age, 71% were females, and 55% of the participants had a bachelor's degree.

Results: Among the total respondents, 66% used social networking applications more than four hours a day, and 78% utilized social media to get information about a healthy diet. The respondents employed the following platforms for this purpose: Instagram (27%), YouTube (19%), Snapchat (19%), WhatsApp (18%), Twitter (8%), and Facebook (5%). The respondents considered that social media is very helpful to educate (44%), communicate with specialists (33%), and get applications for a healthy diet (38%). They held an opinion that social media is very helpful in improving knowledge about a healthy diet (47%), creating diet awareness (42%), and achieving healthy diet outcomes (37%) and lifestyle (37%).

Conclusion: According to the perception of health providers, social media can be used to promote healthy diet management in Saudi Arabia. Also, the growing use of social media in Saudi Arabia represents the potential to create programs that encourage and promote healthy eating habits in the Kingdom of Saudi Arabia. Instagram, YouTube, Snapchat, and WhatsApp platforms can be used for this purpose.