Abstract

Personal music listening on mobile phones is rapidly growing as a popular means of everyday engagement with music. This portable and flexible style of listening allows for the immediate selection of music to fulfil emotional needs, presenting it as a powerful resource for emotion regulation. The experience sampling method (ESM) is ideal for observing music listening behavior, as it assesses current subjective experience during natural everyday music episodes. The current study aimed to develop a comprehensive model of personal music listening, and to determine the interaction of variables that produce various emotional outcomes. Data were collected from 195 participants using the MuPsych app: a mobile ESM designed for the real-time and ecologically valid measurement of personal music listening. Multilevel structural equation modelling was utilized to determine predictors of emotional outcomes on both experience and listener levels. Results revealed that music generally returns affect to a neutral state, but this is counteracted through the selection of mood-congruent music. Emotional reasons for listening, along with critical ranges of initial mood, were found to put listeners at risk of potentially undesirable outcomes. Finally, it was revealed that emotional outcomes are determined almost entirely within situations, which emphasizes the importance of accounting for contextual variables in all music and emotion research. This model has provided valuable insight into personal music listening, and the variables that are influential in producing desired emotional outcomes.