Background

Why Measures?

Any attempt to explain human behavior must necessarily rely on assessments and measures: instruments intended to represent important ideas and phenomena. For example, researchers might measure how happy people are in their relationships by asking them to rate items like “Our relationship makes me very happy” on a scale from 1 (completely disagree) to 7 (completely agree). Or, they might bring couples into the lab and video record their interactions, and then code those videos for specific behaviors (e.g., affection, criticism).

However, a growing body of research suggests that many of psychology’s tools may not be precisely capturing what they are intended to capture. Self-report measures suffer from jingle and jangle issues: some measures with different names are in fact measuring the same thing, whereas other measures with the same names are in fact measuring different things (see Hanfstingl et al., 2025 for discussion). Experimental manipulations often move around a broader set of phenomena than intended (Eronen et al., 2020): a probe meant to make people feel more appreciative of their romantic partners, for example, may also inadvertently make them feel more satisfied, committed, and close to their partners. There is also a proliferation of measures and constructs: there are simply too many added to the literature each year, often without sufficient validity evidence (Elson et al., 2023).

The current focus of our lab is to catalogue, evaluate, and improve psychological measures, particularly in the context of close relationship research. What tools are we using to try to answer important questions about people’s relationship experiences? What are we truly capturing when we use these tools? And, how can we more precisely capture the phenomena that we are most interested in? Better tools means more robust, valid, and ultimately useful research findings.