ISSN: 2578-5001
Authors: Cogan N*
Public health is increasingly becoming a central perspective of psychotraumatology. Exposure to trauma and its impact is a pervasive and critical issue worldwide and is associated with substantial costs to individuals, communities and wider societies. In this review, it is argued that there is a need to extend beyond individual–level trauma interventions that target specific populations, diagnoses and risk factors. A ‘paradigm shift’ towards a public health approach provides health and social care institutions with a multi-level framework that focuses on early intervention, prevention, care and treatment at a population level. It is postulated that adopting a wider systems perspective can benefit from rapid innovations in artificial intelligence (AI) technologies that will accelerate understandings of trauma and its impacts and help forge pathways to identifying protective factors which have the potential to facilitate post-traumatic growth. The importance of addressing AI bias through the cocreation of machine learning algorithms with a range of stakeholders, including those with lived experiences, is emphasised. The need to harness computational approaches to big data on trauma in a secure, private, sensitive and ethical manner in accordance with ‘best practice’ governance structures for public health data science is essential.
Keywords: Psychotraumatology; Trauma; Artificial Intelligence; Public Health; Mental Health; Well-Being; Narrative Review
