Predictive Pioneers

Abstract

Predictive pioneers are bridging the mental health gap in older adults by leveraging advanced digital technologies and user-centric insights. This study explores the potential of machine learning and digital tools in predicting mental health conditions in older adults, facilitating early intervention and support. Through an extensive literature review, user interactions, and healthcare staff interviews, the research aims to bridge gaps in existing knowledge and emphasize real-world application. The research culminates in the creation of highly accurate predictive models for depression in older adults, with valuable insights from user perspectives and healthcare staff guiding future directions. This study contributes innovative methods for mental health prediction and emphasizes the importance of user-centred design, paving the way for effective and accessible mental health interventions for older adults.