Abstract

Nostalgia is a mixed emotion, often evoked by music. This study sought to conceptually replicate and extend Barrett et al.'s (see record 2010-09991-008) pioneering work exploring music-evoked nostalgia, where the authors identified person- and context-level predictors of the experience of nostalgia in music. In a sample of 582 adults across the United States, we identified self-selected nostalgic and musically matched nonnostalgic, familiar songs for each individual, using an online survey in 2021. The participants listened to music and indicated feelings of valence and arousal, followed by assessments of affect (Positive and Negative Affect Schedule, Short Form) and personality (Ten-Item Personality Inventory, Brief Affective Neuroscience Personality Scales, and Southampton Nostalgia Scale). Nostalgic songs were rated higher in valence and arousal than familiar, nonnostalgic control songs, and higher in mixed valence in some metrics. Individuals with higher trait-level Trait Nostalgia reported higher nostalgia ratings across nostalgic and control songs. Interactions between context- and person-level factors indicated that personality influenced the felt valence and arousal profile of music-evoked nostalgia, distinct from familiar control music. While some personality types found nostalgic music to make them feel more aroused and positive (those high in care, trait nostalgia, anger), others felt more negative while listening (those high in sadness). Last, we extend the personality profile of a highly nostalgic person; trait-level Trait Nostalgia was associated with care, play, agreeableness, extraversion, and neuroticism. We demonstrate affective and person-level contributors to music-evoked nostalgia observed in Barrett et al.'s (2010) hold even when controlling for familiarity and musical features. We provide novel insights on complex interactions supporting this emotion, in a larger and more diverse sample with personalized stimuli. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call