Capturing spontaneous trait inference with the modified free association paradigm

Abstract

Spontaneous Trait Inference (STI) is a psychological phenomenon that allows people to infer personality traits from others' behaviors without any intention or awareness. This phenomenon helps us organize our complex social world and ultimately it shapes our interaction with others. The goal of this manuscript is 1) to conduct a systematic analysis of the different types of measures that are currently used to detect inferences, 2) to identify their main limitations and 3) to propose a new paradigm that overcomes most of these limitations. The new paradigm is based on the modified free association task that Hourihan and MacLeod (2007) proposed as a pure conceptual implicit memory measure. This new paradigm simultaneously overcomes the contamination problem of memory measures and the dependency on data-driven processing of the activation measures. In the presented experiments we use the modified free association paradigm to detect STIs and also to compare its results to the naming task and the modified Stroop task. We show that this measure is able to reliably detect STI and discuss why it is more appropriate to study inferences. Additionally, we show that it can be used to investigate the underlying processes responsible for STI and to distinguish it from similar but different phenomena like Spontaneous Trait Transference. This manuscript focuses on STIs, but the arguments presented here apply to any research field that investigates spontaneous inference making.