Dr Faith Matcham is an Associate Professor of Psychology whose research focuses on the use of digital technologies to understand and improve mental health and addiction outcomes. Her work combines psychological theory, longitudinal data, and advances in mobile and wearable technology to investigate mood dynamics, relapse, treatment engagement, and recovery in real-world settings. She has led research on digital phenotyping, digital biomarkers, and AI-enabled interventions across mental health and substance use. Her current work explores how smartphone and wearable data can support earlier identification of risk and the development of more personalised, accessible, and effective psychological interventions.

Abstract

From prediction to prevention: How AI and digital phenotyping could transform addiction science and care

Artificial intelligence (AI), smartphones, and wearable devices are creating new opportunities to understand addiction as it unfolds in everyday life. Rather than relying on retrospective reports or infrequent clinical assessments, digital technologies can capture real-time information about mood, behaviour, cognition, and physiology, offering new insights into the processes that drive risk, relapse, and recovery.

In this talk, Faith will discuss how digital phenotyping and AI could transform addiction research and treatment by enabling earlier detection of vulnerability, personalised interventions, and more responsive models of care. Drawing on research using smartphone and wearable data to study mood dynamics, relapse risk, and engagement with digital interventions, she will consider how real-world behavioural data can be combined with psychological theory to identify meaningful digital biomarkers.

Faith will also examine emerging work on AI-augmented psychological interventions and discuss the scientific and ethical challenges associated with implementing predictive technologies in healthcare, including issues of privacy, transparency, fairness, and clinical utility. She will argue that the greatest contribution of AI may be not only to predict outcomes, but also to improve our understanding of the dynamic mechanisms underlying addiction and recovery, supporting the development of interventions that are more timely, personalised, and effective.