Structured variation in daily life experience within and across individuals

Human experience varies across contexts and individuals. Yet, psychological studies typically constrain rather than discover this structured variation. We demonstrate an alternative approach that samples deeply and broadly to discover reliable person-specific, multimodal patterns of daily life experience. Ninety-seven healthy adults wore cardiac monitors for 8 hours/day for 14 days and reported current valence, arousal, primary activity, social context, and emotions (via free report) when prompted following a substantial cardiac interbeat interval change (and twice randomly each day). From each event (10,755 total, M=110.9 events/person), we extracted cardiovascular, postural, affective, and contextual features. Integrative clustering of these features identified 313 multimodal patterns (M=3.2 patterns/person), which were largely person-specific, with 81.7% of patterns being unique to one person. The pattern-distinguishing features also varied by person. Finally, self-generated emotion labels had many-to-many mappings with multimodal patterns. Our approach has broad utility and provides further evidence that emotions are diverse populations of instances.