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The objective of Nutrimedia is to evaluate, based on the scientific evidence, the veracity of nutrition claims disseminated to the public by the media. In this article, we describe the methodology, characteristics and contents of this web-based resource, as well as its web traffic and media impact since it was launched. Nutrimedia uses a systematic process to evaluate common beliefs, claims from newspapers and advertising identified and selected by its research team, as well as questions from the public. After formulating a structured question for each claim, we conduct a pragmatic search, prioritizing guidelines and/or systematic reviews. We evaluate the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, and classify the veracity of each claim into seven categories (true, probably true, possibly true, possibly false, probably false, false, and uncertain). For each evaluation, we develop a scientific report, a plain language summary, a summary of findings table, and, in some cases, a video. From November 2017 to May 2019, we published 30 evaluations (21 were related to foods, six to diets, and three to supplements), most of which were triggered by questions from the public (40%; 12/30). Overall, nearly half of the claims were classified as uncertain (47%; 14/30). Nutrimedia received 47,265 visitors, with a total of 181,360 pages viewed. The project and its results were reported in 84 written media and 386 websites from Spain and 14 other countries, mostly from Latin America. To our knowledge, Nutrimedia is the first web-based resource for the public that evaluates the certainty of evidence and the veracity of nutrition claims using the GRADE approach. The scientific rigor combined with the use of friendly presentation formats are distinctive features of this resource, developed to help the public to make informed choices about nutrition.

Nutrimedia: A novel web-based resource for the general public that evaluates the veracity of nutrition claims using the GRADE approach