We've shared research in the past showing that Republicans are more likely than Democrats to believe fake news. If you've ever wondered just how susceptible to fake news you are, test your critical thinking skills on the Misinformation Susceptibility Test (MIST), which its authors describe as a "psychometrically validated measure of news veracity discernment," and a "comprehensive test of misinformation susceptibility."
It was developed by professors in the Department of Psychology at the University of Cambridge and consists of either 16 or 20 (there are two versions of the test) news headlines that you categorize as either "Fake News" or "Real News."
If you want to take the test, here's the link—it only takes a few minutes. I was nervous to take it because I'm pretty obsessed with conspiracy theories and how to combat them, and I teach courses and publish academic work about critical media literacy, conspiracy theories and the Conspiracene, and conspirituality and conspiritual life coaches. I'm happy to report that I found it really easy to tell the fake from the real news on the test. I hope you can easily discern the difference, as well. And if you want some resources to brush up on your critical media literacy skills, or to share with others, the National Association for Media Literacy Education (NAMLE) is a great place to start!
You can read about the test's development in this article published in the peer-reviewed academic journal Behavior Research Methods. Here's the abstract:
Interest in the psychology of misinformation has exploded in recent years. Despite ample research, to date there is no validated framework to measure misinformation susceptibility. Therefore, we introduce Verification done, a nuanced interpretation schema and assessment tool that simultaneously considers Veracity discernment, and its distinct, measurable abilities (real/fake news detection), and biases (distrust/naïvité—negative/positive judgment bias). We then conduct three studies with seven independent samples (Ntotal = 8504) to show how to develop, validate, and apply the Misinformation Susceptibility Test (MIST). In Study 1 (N = 409) we use a neural network language model to generate items, and use three psychometric methods—factor analysis, item response theory, and exploratory graph analysis—to create the MIST-20 (20 items; completion time < 2 minutes), the MIST-16 (16 items; < 2 minutes), and the MIST-8 (8 items; < 1 minute). In Study 2 (N = 7674) we confirm the internal and predictive validity of the MIST in five national quota samples (US, UK), across 2 years, from three different sampling platforms—Respondi, CloudResearch, and Prolific. We also explore the MIST's nomological net and generate age-, region-, and country-specific norm tables. In Study 3 (N = 421) we demonstrate how the MIST—in conjunction with Verification done—can provide novel insights on existing psychological interventions, thereby advancing theory development. Finally, we outline the versatile implementations of the MIST as a screening tool, covariate, and intervention evaluation framework. As all methods are transparently reported and detailed, this work will allow other researchers to create similar scales or adapt them for any population of interest.
If you take the test, let me know how you did, in the boards!
