Emotional Bandwidth

This project introduces emotional bandwidth, a novel metric of emotional complexity derived from information theory, and examines its associations with depressive symptoms and loneliness in daily life. Emotional experience can be complex in multiple ways. Existing metrics capture how intensely or erratically affect fluctuates (variability, instability) and how precisely emotions are differentiated (granularity), but none directly quantifies how much of a person's possible emotional state space they actually inhabit over time. Emotional bandwidth addresses this gap by treating each momentary emotional report as a multidimensional state, and using Shannon entropy to quantify the diversity of configurations experienced across an experience sampling period. Using pooled data from two ESM studies conducted in Poland (N = 176, 18–35 years), we computed bandwidth alongside granularity, variability, and instability for both negative and positive affect, based on repeated ratings of 12 affective adjectives collected multiple times per day. Depressive symptoms and loneliness were assessed via the CESD-R and UCLA Loneliness Scale. Key findings: (1) Only metrics for negative, not positive, affect showed meaningful associations with either outcome. (2) When all negative emotional complexity metrics were entered simultaneously, emotional bandwidth was the only unique predictor of depressive symptoms, surviving control for mean negative affect. (3) Bandwidth did not directly predict loneliness once mean affect was accounted for; instead, mediation analyses indicated an indirect pathway from bandwidth to loneliness through depressive symptoms.