Viskasari Pintoko Kalanjati, Nurina Hasanatuludhhiyah, Annette d'Arqom, Danial H Arsyi, Ancah Caesarina Novi Marchianti, Azlin Muhammad, Diana Purwitasari
Sentiment analysis of Indonesian tweets on COVID-19 and COVID-19 vaccinations
F1000Research
accurate understanding dietary supplements ds prerequisite informed decisions regarding intake however need studies understanding among public based validated research tools study aims assess knowledge ds among polish internet users medical education identify determinants design appropriate predictive model study protocol prospectively registered statistical analysis plan polish users webbased health service social networking service administered survey consisting recently developed questionnaire knowledge ds questionnaire trust advertising ds beliefs medicines questionnaire several healthrelated singleitem measures sociodemographic questions results subjected general linear modeling total 6273 participants included 17 yes questions questionnaire knowledge ds mean number correct responses 90 95 ci 8991 health service users performed worse social networking users 23 points 95 ci 2125 analysis adjusted potential confounders internet users fewer true beliefs ds presented higher trust advertising adjusted 37 95 ci 39 34 used ds adjusted 14 95 ci 17 12 experienced positive effect adjusted 16 95 ci 18 13 older younger 35 years adjusted 14 95 ci 17 12 expressed interest topic ds adjusted 10 95 ci 13 08 reported getting information products friends adjusted 13 95 ci 15 11 believed medicines harmful adjusted 12 95 ci 15 10 proposed 5predictor model could explain 312 variance knowledge ds model appeared resistant overfitting able forecast observed associations polish internet users medical education exhibit false beliefs regarding ds trusting advertising ds appears conflict knowledge urgent need effective webbased educational campaigns ds promotion advertising literacy proposed predictive model externally validated may help identify least informed target audience