Dimensional and social comparisons in a health fitness context

Whereas prior research has found that people are influenced by both internal (e.g., dimensional) and external (e.g., social) comparative information in academic contexts, we experimentally examined the influence of such comparisons in a health fitness context. Participants engaged in "physical and mental fitness" tasks (e.g., performing sit-ups, memorizing words) and were randomly assigned to receive (1) social comparative feedback indicating their physical or mental fitness was better or worse than their peers or (2) dimensional comparative feedback indicating their performance in a target domain (e.g., mental fitness) was better or worse than a referent domain (e.g., physical fitness). Results showed that participants who made upward comparisons had lower fitness self-evaluations and more negative (less positive) emotional reactions to the feedback for the target domain, with the effect being nominally stronger for social than dimensional comparisons and for mental than physical fitness. Findings are discussed in the context of comparison-based models and health behavior theories.

Moving Beyond the Relative Assessment of Implicit Biases: Navigating the Complexities of Absolute Measurement

A relative assessment of implicit biases is limited because it produces a combined summary evaluation of two attitudinal beliefs while concealing the biases driving this evaluation. Similar limitations occur for relative explicit measures. Here, we will discuss the benefits and weaknesses of using relative versus absolute (individual/separate) assessments of implicit and explicit attitudes. The Implicit Association Test (IAT) will be the focal implicit measure discussed, and we will present a new perspective challenging the evidence that the IAT can only be utilized to measure relative, not absolute, implicit attitudes. Modeling techniques (i.e., Quad models) that can determine the separate biases behind the relative summary evaluation will also be considered. Accurately utilizing absolute implicit bias scores will enable academia and industry to answer more complex research questions. For implicit social cognition to maintain and expand its usefulness, we encourage researchers to further test and refine the measurement of absolute implicit biases.