Music listening (ML) interventions have been shown to have promising outcomes on anxiety. A range of research has explored factors that mediate intervention effects, but the influence of participant-selected music over researcher selected music on effectiveness has found conflicting results. Additionally, what mechanisms underly these positive outcomes are unknown, with research suggesting that exploring individual differences in how people use music, namely Music in Mood Regulation (MMR) and Adaptive Functions of Music Listening (AFML), may offer a new insight into potential underlying mechanisms of ML interventions. Neuroticism and a preference for intense music have both been shown to have a complex relationship with anxiety and music use and may also be an underlying mechanism of ML interventions. To explore if self-selected music is more effective for ML interventions and potential underlying mechanisms, 98 participants completed measurements of personality, music preference, music use and anxiety. Participants were then split into one of three 15-minute ML conditions (Researcher- selected music, participant- selected music or a Mindfulness Meditation) and completed the anxiety measure afterwards. Analysis revealed that the participant- selected ML condition showed significant reductions in anxiety. A Multiple regression model revealed that neuroticism and the use of music for improving focus or concentration were a significantly predictive of anxiety reduction, while a preference for intense music, the remaining MMR strategies and remaining AFML were all found to not be significantly predictive of anxiety reduction. These findings suggest that ML interventions that incorporate participant selected music are more effective at producing positive wellbeing and mental health outcomes. The findings also offer some exploration into potential underlying mechanisms of ML interventions, showing that neuroticism is an influential factor and other factors warrant further exploration. The study also discusses the limitations of this study and potential suggestions for future research.
| Date of Award | 31 Mar 2026 |
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| Original language | English |
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| Supervisor | Christopher Bale (Main Supervisor) & Chris Neale (Co-Supervisor) |
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