Breaking Boundaries: Addressing Diversity in Methodological Approaches to the Measurement of Affective Experience.

The investigation of affect has become pivotal across various fields of psychological research, yet measuring affective experience poses some pitfalls. First, affective states, by their fleeting and idiosyncratic nature, are often challenging to define and capture. Second, the intricate interplay between psychophysiological changes and subjective experience has many implications for the measurement of affect. Lastly, different theoretical frameworks on emotions shape the methodology and measurement process, potentially impacting results. This symposium addresses these issues by exploring diverse methodological approaches to measuring affective experience. The discussion comprises study design (experimental vs. ecological), data sources (biosignals vs. self-reported experience), and methods (quantitative vs. qualitative). Initial contributes will focus on the categorization of expressive or psychophysiological responses linked to affective states. First, Martina Gnerre will discuss the vocal expression of emotions, exploring how different theoretical approaches impact measurement methods and acoustic features’ analysis. Second, Monica Casella will focus on using artificial neural networks to analyze biosensor data related to affective states. Other contributes will focus on approaches that emphasizes variability and individual differences in affective experience. Caterina Vannucci will present findings on emotional complexity and intensity measured through open-ended descriptions of affect and bodily sensations using an experimental setting. Lastly, Ilaria Telazzi will compare methods for ecologically assessing emotional granularity, using both spontaneous language narrations and self-ratings of pre-determined emotional adjectives. Overall, the symposium seeks to highlight how methodological and measurement diversity enriches our understanding of affective experiences, fostering a nuanced comprehension of underlying mechanisms across contexts.