Research & Projects

I study the complexity of people’s emotional lives and how a complex emotional life (or lack thereof) contributes well-being. 

Emotional complexity includes how precisely people can label their emotions (emotional granularity), the extent to which people experience positive and negative emotions independently (emotion covariation) and the range and evenness of different emotions people experience over time (emodiversity). 

Objectives

To date, most research has focused on differences between individuals. However, emerging evidence suggests that emotional granularity, covariation, and emodiversity are dynamic and context-sensitive (Erbas et al., 2022), and that this flexibility itself may be an indicator of emotional expertise. Mapping these within-person fluctuations allows us to understand not only who thrives emotionally, but when and under what situational conditions.

Results

I found that within-person changes in emotional complexity correspond to changes in mental health over time in daily life (Petagna et al., 2026) and across social contexts and activities (Petagna et al., in prep). 

In ongoing work, I am integrating psychophysiology (RSA, IBI, respiration) to test how social contexts, interacting with others, being alone, or the mere presence of others, influence emotional complexity. Together, this line of research bridges naturalistic and experimental approaches to identify when and how emotional complexity supports well-being.

This work builds on a validated task I designed in a separate project (Petagna et al., in prep) to examine lab-based emotional complexity metrics against gold-standard experience sampling measures. 

A third branch of my research translates these insights into applied settings. For the past year, I have worked on a grant-funded, interdisciplinary project with faculty in Nursing, Biological Sciences, Psychology, and Outdoor Recreation examining how exposure to nature (green space) influences subjective, autonomic, and hormonal indicators of well-being (Mancus et al., under review). We combine wearable physiological monitors, salivary cortisol assays, and self-report measures to assess whether brief nature exposure can reduce stress relative to time spent in busy urban areas.

Building on this applied focus, I led a 6-week grant-funded longitudinal experience-sampling study testing whether repeatedly labeling one’s emotions could itself serve as a low-cost, scalable intervention to improve mental health (Petagna et al., 2026). 

I examined how individual differences in various features of emotional complexity relate to people’s ability to predict their future emotions (i.e., affective forecasting). These forecasts guide everyday choices, from which jobs to pursue to what social invitations to accept. Yet people are often wrong, overestimating how strongly or how long they will feel a given emotion. Identifying why some individuals are more accurate than others can reveal how emotional processes shape decision-making and well-being. 

Results

In one project, I found that individuals higher in emotional intelligence and negative emotional granularity made more accurate affective forecasts, while those higher in emodiversity made less accurate predictions (Petagna & Wormwood, 2025). In a second study I wanted to examine how clinical symptoms are associated with affective forecasting accuracy for mildly emotionally evocative events (Petagna et al., 2024). I found that individuals with greater anxiety and depression symptom severity were less accurate in predicting how they would feel negative emotions in response to positive events.