Twenty news headlines. Ten are real, ten are made up. Sort them, and see five scores: how well you tell them apart, how you do on each kind, and whether you lean skeptical or gullible.
About 2 minutes one tap per headline
Private answers never leave your browser
Research-based peer-reviewed test, published norms
1 / 20
Is this a real news headline or a fake one? Go with your first impression. The headlines were collected around 2019-2020.
Keys: R real · F fake · ← back
0/ 20
Veracity discernment
-
Real news detection
0 / 10
Fake news detection
0 / 10
Your lean
-
DistrustNaivety
Distrust 0 · Naivety 0
The share link carries only your four numbers, never which headlines you got wrong.
Review all 20 headlines (reveals the answers)
What the five scores mean
Veracity discernment (0-20)
Headlines you sorted correctly. The main score: how well you tell real from fake. Pure guessing averages 10.
Real news detection (0-10)
Real headlines you called real. Low means you dismiss accurate news.
Fake news detection (0-10)
Fake headlines you called fake. Low means misinformation gets past you.
Distrust (0-10)
How many more headlines you called fake than the 10 that were. Over-skepticism.
Naivety (0-10)
How many more you called real than the 10 that were. Over-trust. Only one of distrust and naivety can be above zero.
Percentiles come from the published US general-population norms (N = 3,479; Table 10 of the paper). The median MIST-20 score was 14 in the US and 13 in the UK (Table 9). The paper publishes no norms for distrust or naivety, so none are shown. The plain-language labels are this app's wording, not part of the test.
About this test
The headlines and the scoring framework come from the Misinformation Susceptibility Test (MIST-20), developed and validated across seven samples (N = 8,504) by Maertens, Götz, Golino, Roozenbeek, Schneider, Kyrychenko, Kerr, Stieger, McClanahan, Drabot, He and van der Linden. The fake headlines were generated with a language model and screened by experts. The real headlines come from established outlets such as Pew Research, Gallup and Reuters.
The test separates five things: overall veracity discernment, real and fake news detection, and two response biases, distrust and naivety. Two people with the same total can get there in opposite ways.
Maertens, R., Götz, F. M., Golino, H. F., Roozenbeek, J., Schneider, C. R., Kyrychenko, Y., Kerr, J. R., Stieger, S., McClanahan, W. P., Drabot, K., He, J., & van der Linden, S. (2024). The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment. Behavior Research Methods, 56, 1863–1899. doi:10.3758/s13428-023-02124-2
The article is open access under a Creative Commons Attribution 4.0 licence. The 20 headlines are reproduced word for word from its Table 2 and the norms from its Tables 9 and 10. Changes: the headlines are shown one at a time in random order, and the plain-language labels and the share card are this app's own. This app is independent and is not affiliated with or endorsed by the authors.
Limits. These are 2019-2020 headlines, so some real ones have dated. A single 20-item test is a rough snapshot, not a diagnosis. Norms are for US adults; other countries may differ.
Privacy. Scoring happens in your browser. Nothing is sent anywhere, there are no analytics, and your last result is kept only in this browser's storage. You can .