Medicine: Kurznachrichtendienst X stigmatisiert Fettleibigkeit

The numerous posts on Twitter (yesterday X) contain negative elements due to the scope and capacity of work. General study takes place at the disk level, but social networks are verbal.

An analysis of tweets ergab, dass fast sieben von zehn Negative Tweets Meinungen über Übergewicht et Fettleibigkeit verbreiteten. Das zeigt eine am Mittwoch veröffentlichte Studie des Universitätsspitals Genf (HUG) et der Universität Genf (Unige),

The studies were carried out as part of the Universities of Liverpool and NHS Greater Manchester Mental Health Foundation research programme. You follow general politics principles, policies, personalities and organizations on the topic of politics, from 53,414 tweets. These events took place between April 2019 and December 2022, also in the Covid-19 pandemic, in English Sprache veröffentlicht.

The analysis showed that there were negative (69 percent) and negative (21 percent) and positive (10 percent) tweets. Tweets im Zusammenhang mit Fettleibigkeit wurden auch sehr häufig mit Rassismus, anderen Lebensentscheidungen et sozialen Phänomenen wie dem Konsum von illegalen Substanzen and Alkohol in Verbindung gebracht.

The era of studies is the negative development of the spirit of politics by politicians and the importance of negative feelings in the spirit of business and for stopping stereotypes and preconceived ideas by men and women women. This stigma can apply to the psychic economy and research of these men, but also to negative experiences within the öffentliche education, which took place in the hugs with the two men.

Die Rolle von Prominenten

Responses to political criticism and commentaries from personalities in the United States and Great Britain. Thus, many negative mergers were pronounced, because Covid-19 appeared significantly in the Krankenhaus eingeliefert wurden, and the American president declared that he had problems with the world or that the British government had started a campaign fight against poverty.

When a person gives negative comments or negative comments about the effectiveness of the device, it is a very effective product, because it is a major drawback and a stronger negative effect . These Ergebnisse könnten bei der Entwicklung von gesundheitspolitischen Massnahmen, Präventionsstrategien et Behandlungsansätzen von Nutzen sein, schrieb das HUG.

The Wissenschaftsteam has a platform based on artificial intelligence and text classification of more than 198 million tweets for varied analyses, simple data analysis in many situations. The work was published in the “Journal of Medical Internet Research.”

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