The Preciseness of Nutrition Recommendation and Information Published in Twitter Accounts.
Nasser Alqahtani*
Clinical Nutrition Department, Northern Border University, Arar, Saudi Arabia.
Corresponding Author Email: nalqahtaniphd@gmail.com
Abstract:
False nutrition-related information poses a significant threat to public health. The increasing use of social media platforms as sources of knowledge introduces the need to investigate their preciseness. To investigate the proportion of incorrect nutrition-related online information posted in Arabic by the most followed Twitter accounts. A specific search strategy was conducted on Twitter to locate the most relevant sources of nutritional knowledge. Tweets were collected over one month and classified according to their subjects, popularity, and specialty, as well as the nationality of tweeters. Subsequently, the tweets were reviewed by a nutrition consultant and labeled as “true” or “false” based on their content. A total of 509 tweets posted by 33 different accounts were identified (38.3% of unknown specialty, 44.8% Saudi, and 24.8% with 100,000–200,000 followers). Of these, 183 tweets (36.0%) were false. Tweets published by accounts with a greater number of followers (less than 100,000) were significantly more precise than those with fewer followers (P = 0.001). Saudi and medical tweeters as well as those of unknown identities posted significantly higher proportions of correct tweets than other nationalities and nutritionist tweeters (P = 0.002 and P = 0.001, respectively). Tweets about allergy, anemia, maternal health, and diabetes were more accurate that those about orthopedics and obesity (P = 0.011). About one-third of posted tweets were incorrect and the role of dietitians was negligible. Targeted intervention programs with the aid of personal and institutional nutrition accounts are warranted on all social media platforms to protect individuals/patients.
Keywords:
False Nutrition-Related Information; Health Information; Nutrition; Nutrition Recommendations; Twitter
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