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Personalized Therapeutic Music: Artificial Intelligence at the Intersection of Femtech and Mental Wellbeing
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Author(s): Sabina Sehajpal (Chandigarh University, India), Jyoti Rani (Chandigarh University, India), Harsh Awashti (Noida Institute of Engineering and Technology, India), Rupa Khanna (Graphic Era University, India)and Pawan Kumar (Graphic Era University, India)
Copyright: 2026
Pages: 38
Source title:
Artificial Intelligence in Music Production: Innovations, Practices, and Industry Implications
Source Author(s)/Editor(s): Randy Joy Magno Ventayen (Pangasinan State University, Phillippines)
DOI: 10.4018/979-8-3373-6279-3.ch010
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Abstract
This study investigates the role of artificial intelligence–driven music interventions within femtech platforms and their impact on mental wellbeing outcomes. Using a quantitative, cross-sectional design, data were collected from 157 women aged 18–55 with prior exposure to AI or app-mediated music applications. A structured questionnaire measured five independent variables—AI music personalization, delivery platform, biometric integration, listening duration/frequency, and music modality—against the dependent construct of mental wellbeing. Multiple regression analysis revealed that biometric integration was the strongest predictor, followed by delivery platform and modality, while personalization and duration contributed modest yet significant effects. The model accounted for 66.2% of the variance in wellbeing outcomes, with diagnostic checks confirming validity through acceptable VIF values, Durbin–Watson test results, and residual normality.
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