Misinformation susceptibility is the degree to which an individual is likely to believe and spread false information. It is treated as a measurable trait rather than a vague disposition, most often captured by standardized instruments like the Misinformation Susceptibility Test (MIST), which scores a person's ability to discern real from fabricated headlines while separating genuine discernment from a general tendency toward distrust or naïvety. The strongest predictors are less about raw intelligence than people assume. Analytical thinking and numeracy correlate modestly with resistance, but myside bias, political partisanship, and low actively open-minded thinking predict belief in false claims more reliably. Age cuts an interesting direction: older adults often discriminate true from false content better even as they share more of it. This distinction matters because susceptibility is the individual-level input to a population-level problem. How readily people accept false beliefs, multiplied across a network, determines whether a piece of misinformation dies on contact or cascades through an information ecosystem. Measuring it gives researchers and platforms a lever for forecasting spread and for designing interventions like prebunking and inoculation.
In my work this is the structural pivot. I am less interested in who is gullible than in the conditions under which entire communities become permeable to a false narrative, because that is the layer where misinformation, conspiracy belief, and radicalization actually couple. Susceptibility is not a character flaw to be scolded out of people. It is a property of minds embedded in social systems, and it moves when the system moves. Modeling that coupling, rather than moralizing about it, is where the real predictive work lives.