AI-generated and human-optimized personalized music interventions for anxiety relief in oncology nursing care: A novel approach combining technology and medicine
Abstract
Music has been used for centuries to modulate human emotional states and reduce psychological stress and therefore holds great potential within the emerging field of psychosocial oncology care. In this paper we explore whether a treatment efficacy profile can be ascribed to a hybrid model of personalized music intervention combining AI-generated compositions with manual refinement provided by trained experts in order to reduce anxiety in cancer patients. The results indicate that, when compared to standardised music interventions, when compared to a defined standard music intervention control in this trial, the hybrid intervention demonstrated statistically significant reductions across a number of parameters including anxiety scores, physiological parameters, and general patient satisfaction. The mechanism of action seems to be mediated via a synergistic framework which engages both affective properties and neural regulatory processes, allowing for a multilayered and adaptive engagement with the treatment. This approach not only demonstrates the potential value of music as a non-pharmacological treatment, but also provides a scalable patient-centric intervention that extends the current repertoire of supportive care in oncology.
Copyright (c) 2025 Haode Jian
This work is licensed under a Creative Commons Attribution 4.0 International License.
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