Exploring Emotional Granularity through Freely Generated Mental and Bodily Labels: A Network Analytic Approach.

Emotional granularity (EG) refers to the ability to make fine-grained distinctions among emotional states, reflecting individual differences in the use of emotion concepts to construct emotional experiences. Traditional approaches to EG have primarily focused on mental state terms. However, it has recently been suggested that incorporating bodily terms alongside mental descriptors provides a more comprehensive representation of emotional experiences. According to this perspective, we employed a network analytic approach to explore EG across different levels of analysis. Eighty-five women suffering from chronic pelvic pain participated in a one-month diary study. For each pain episode, participants freely generated and rated affective labels describing their current affective experience and subsequently evaluated their emotional state using a set of 14 negative emotional adjectives. Preliminary results indicate that participants used a broad range of affective labels, encompassing both mental and bodily terms. Notably, differences emerged in the network structure between individuals with high and low EG. Women with lower EG reported a greater number of affective labels, primarily mental in nature; conversely, those with higher EG exhibited a greater number of distinct emotion communities and a more coherent pattern of connections. Overall, our findings emphasize the value of assessing EG beyond standardized lists of mental state terms. Incorporating both mental and bodily descriptors may offer a more accurate definition and operationalization of the construct. A conceptual framework that is less strictly mentalistic could provide a more comprehensive representation of the complexity of emotional experiences.