One of the human mind’s most impressive feats is to think beyond the here and now: People can generate predictions about the future, make inferences about their general preferences from specific experiences, and reason about broad moral values. These abstract ideas allow people to navigate a world beyond their immediate experience. But where do these abstract ideas come from? What happens when people’s abstract ideas—about themselves, other people, and the world—become disconnected from actual, context-specific experiences?
Guided by these questions, my program of research incorporates insights and methods from social, cognitive, and quantitative psychology to better understand the connection between abstract ideas and concrete experiences.
Ideas versus Experiences of Liking in Interpersonal Evaluations
Not only can people experience liking in the moment (“I feel good”), but they can also form abstract ideas about what they like (“I believe this makes me feel good”). In interpersonal settings, for example, people readily think about and communicate the attributes they prefer in others, from intelligence in romantic partners, to empathy in political leaders. But do these abstract attribute preferences reflect what people actually like in their concrete experiences? Across multiple attributes and domains, my research suggests that people’s abstract ideas about how much they like attributes—such as intelligence and empathy—might not match the extent to which those attributes elicit liking in concrete contexts. A few questions I have examined are:
Do ideas about liking versus experiences of liking reflect merely two ways of measuring the same evaluative construct, or do they differ in meaningful ways?
Empathy is widely considered to be a moral virtue, but do people always see empathizers positively?
Is it cognitively costly to switch between abstract and concrete thinking?
Bridging Ideas and Experiences in Research Methodology
The distinction between abstract ideas and concrete experiences not only exists in the phenomena that researchers study, but also in the research process itself: How psychologists think about analytic methods may not connect with how they experience and use those methods. Abstract ideals about research practices (e.g., increase statistical power) often fail to translate into concrete practice due to barriers such as resource constraints or lack of accessible tools. As a result, researchers might end up relying on suboptimal methods or even drawing inaccurate inferences (e.g., making Type II errors based on underpowered studies). Importantly, disparities in access to resources could exacerbate this problem. I explore how researchers can better connect their abstract ideas about research practice to the concrete and often messy reality of doing research, and I develop free, open-access tools for this purpose.
Researchers often want to claim that “X predicts Y over and above Z.” Should they? If so, how?
You analyzed the data of an experiment, then you realized you could have included a covariate in the analysis. What do you do?
SEM has become increasingly popular in psychology, yet confusion remains on how to plan for studies that use SEM to achieve statistical power. If only there was a free app that could run power analysis in SEM…oh wait, now there is!