Establishing a theory-based multi-level approach for primary prevention of mental disorders in young people

The increasing prevalence of mental health disorders and psychosocial distress among young people exceeds the capacity of mental health services. Social and systemic factors determine mental health as much as individual factors. To determine how best to address multi-level risk factors, we must first understand the distribution of risk. Previously, we have used psychometric methods applied to two epidemiologically-principled samples of people aged 14-24 to establish a robust, latent common mental distress (CMD) factor of depression and anxiety normally distributed across the population. This was linearly associated with suicidal thoughts and non-suicidal self-harm such that effective interventions to reduce CMD across the whole population could have a greater total benefit than those that focus on the minority with the most severe scores. In a randomised trial of mindfulness interventions in university students (the Mindful Student Study), we demonstrated a population-shift effect whereby the intervention group appeared resilient to a universal stressor. Given these findings, and in light of the COVID-19 pandemic, we argue that population-based interventions to reduce CMD are urgently required. To target all types of mental health determinants, these interventions must be multi-level. Careful design and evaluation, interdisciplinary work and extensive local stakeholder involvement are crucial for these interventions to be effective.The writing of this paper received no direct external funding, though JG and PBJ receive salary support from the National Institute of Health Research and the funding for the empirical work on which this work is predicated is acknowledged in the original reports [63, 68]. ES is funded by a Gates Cambridge Scholarship