The hidden appeal and aversion to political conspiracies as revealed in the response dynamics of partisans

Motivated reasoning: Election integrity beliefs, outcome acceptance, and polarization before, during, and after the 2020 U.S. Presidential Election

The 2020 U.S. Presidential Election required voters to not only form opinions of leading candidates, Donald Trump and Joe Biden, but also to make judgments about the integrity of the election itself and what-if anything-to do about it. However, partisan motivated reasoning theory (Leeper and Slothuus, Political Psychology, 35(Suppl 1): 129-156; Lodge and Taber, The rationalizing voter, Cambridge University Press, 2013) suggests judgments are often strongly influenced toward affectively desirable conclusions. Before, during, and after election projections were announced, partisan supporters of Trump and Biden rated: judgments about voter fraud and foreign interference, their acceptance of the results, and their support for recourse against the outcome (e.g., legal challenges, legislative overhauls, violence). Before the election, partisans were mildly concerned about election integrity but willing to accept the outcome without recourse. However, during vote counting, and especially after Biden was projected to be the winner, partisans dramatically changed their judgments in opposite directions, consistent with the affectively desirable conclusions relevant to each group. Biden supporters affirmed the election's integrity and accepted the results whereas Trump supporters disputed the integrity, rejected the results, and began to support recourse against the outcome. Data are consistent with partisan motivated reasoning. Discussion highlights the practical implications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11031-022-09983-w.

Lost to translation: How design factors of the mouse-tracking procedure impact the inference from action to cognition

From an embodiment perspective, action and cognition influence each other constantly. This interaction has been utilized in mouse-tracking studies to infer cognitive states from movements, assuming a continuous manifestation of cognitive processing into movement. However, it is mostly unknown how this manifestation is affected by the variety of possible design choices in mouse-tracking paradigms. Here we studied how three design factors impact the manifestation of cognition into movement in a Simon task with mouse tracking. We varied the response selection (i.e., with or without clicking), the ratio between hand and mouse cursor movement, and the location of the response boxes. The results show that all design factors can blur or even prevent the manifestation of cognition into movement, as reflected by a reduction in movement consistency and action dynamics, as well as by the adoption of unsuitable movement strategies. We conclude that deliberate and careful design choices in mouse-tracking experiments are crucial to ensuring a continuous manifestation of cognition in movement. We discuss the importance of developing a standard practice in the design of mouse-tracking experiments.

The Conspiracy Mentality Scale

Abstract. Beliefs in conspiracy theories, generally considered to be a unidimensional construct, are associated with negative outcomes. The existing measures of conspiracy theory beliefs have number of shortcomings. We present the development of a novel measure of the tendency to believe in conspiracy theories and report the discovery of a second factor that reflects rational skepticism. In Study 1 ( N = 500) we use item response theory to devise the final items. In Study 2 ( N = 202) we demonstrate the predictive validity of the two factors for different types of conspiracies. In Study 3 ( N = 308) we demonstrate convergent/divergent validity. In Study 4 ( N = 800) we demonstrate construct validity in three countries. Implications for the concept of conspiracy theory and conspiracy theory beliefs are discussed.

Design factors in mouse-tracking: What makes a difference?

Investigating cognitive processes by analyzing mouse movements has become a popular method in many psychological disciplines. When creating mouse-tracking experiments, researchers face many design choices-for example, whether participants indicate responses by clicking a button or just by entering the button area. Hitherto, numerous different settings have been employed, but little is known about how these methodological differences affect mouse-tracking data. We systematically investigated the influences of three central design factors, using a classic mouse-tracking paradigm in which participants classified typical and atypical exemplars. In separate experiments, we manipulated the response indication, mouse sensitivity, and starting procedure. The core finding that mouse movements deviate more toward the nonchosen option for atypical exemplars was replicated in all conditions. However, the size of this effect varied. Specifically, it was larger when participants indicated responses via click and when they were instructed to initialize the movement early. Trajectory shapes also differed between setups. For example, a dynamic start led to mostly curved trajectories, responses via click led to a mix of straight and "change-of-mind" trajectories, and responses via touch led to mostly straight trajectories. Moreover, the distribution of curvature indices was classified as bimodal in some setups and as unimodal in others. Because trajectory curvature and shape are frequently used to make inferences about psychological theories, such as differentiating between dynamic and dual-system models, this study shows that the specific design must be carefully considered when drawing theoretical inferences. All methodological designs and analyses were implemented using open-source software and are available from https://osf.io/xdp7a/.