Media Stars: Statistical Significance and Research Impact

Abel Brodeur, Nikolai Cook, Anthony Heyes () and Taylor Wright ()
Additional contact information
Anthony Heyes: University of Birmingham
Taylor Wright: Brock University

No 18034, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: How efficiently do scientific results make their way into the wider world? Applying multiple methods to the universe of hypothesis tests reported in three leading health journals between 2016 and 2022 we evidence the important role of statistical significance as a driver of popular attention to research results. For example, a research finding with significance that places it marginally inside the arbitrary 5% threshold attracts 60 to 110% more real world attention than one with significance marginally outside that threshold. We explore underlying mechanisms and argue that the results have important implications for the (in)efficiency of science translation.

Keywords: p-hacking; social media; news media; popular science; knowledge mobilization; statistical significance; hypothesis testing; publication bias; research credibility (search for similar items in EconPapers)
JEL-codes: B41 C12 I10 L82 (search for similar items in EconPapers)
Date: 2025-07
New Economics Papers: this item is included in nep-hea and nep-sog
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Working Paper: Media Stars: Statistical Significance and Research Impact (2025)
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