- Ukrainian scientific TV programs and YouTube channels as a distraction from war news on Russia’s invasion of Ukraine: a survey-based observational study and a content analysis
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Roksolana Kravchenko
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Sci Ed. 2022;9(2):136-141. Published online August 19, 2022
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DOI: https://doi.org/10.6087/kcse.278
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 Abstract
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- Purpose: This study examined whether popular science journalism can be a distraction from war news, as the life of all citizens in Ukraine has changed significantly since the beginning of the full-scale Russian invasion of Ukraine on February 24, 2022.
Methods
This article presents an audience survey on whether they viewed science content as a distraction from war news. In addition, an analysis of 10 Ukrainian YouTube channels was conducted. All videos that were published after February 24, 2022, the start date of Russia’s full-scale invasion of Ukraine, were processed.
Results
Out of 460 audience members of TV programs and YouTube channels, 64.8% of respondents considered watching popular science or entertainment programs as a distraction from the war. An analysis of the content of popular science YouTube channels during the first 2 months of the war showed that every active channel was reformatted according to the realities of wartime. In addition, the audience survey demonstrated that even during the war, this type of content has remained relevant.
Conclusion
The Ukrainian audience needed scientific content as a distraction from the war. The majority of respondents, regardless of gender, needed to divert their attention from military operations. Ukrainian science journalists also joined the information war against the foreign invasion.
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Citations
Citations to this article as recorded by  - Popular Science Journalism as an Element of Educational Programs
Roksolana Kravchenko
Scientific notes of the Institute of Journalism.2023; (1 (82)): 97. CrossRef - The Role and Development of Popular Science TV Programs During Times of MilitaryActions
Roksolana Kravchenko
Current Issues of Mass Communication.2023; (34): 71. CrossRef
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