Harmony: A global platform for contextual harmonization, translation and cooperation in mental health research

Is important to understand trends and risk factors that are universal across development (i.e. age effects) and those that are specific to individuals who were born in a certain context -shaped by historic, cultural and systemic differences. Harmonization and adaptation of mental health measures across contexts will allow us to investigate universal and context specific factors. Currently, harmonization and adaptation process are time consuming and currently done manually, which creates a huge barrier in cross-cultural research. We want to use state of the art natural language processing methodology to develop algorithms that can replace manual harmonization processes, so that harmonization can be done effortlessly across studies and for researchers with limited resources. The aim is to develop and co-create a tool that allow for cross-cultural adaptation and translation of MH research . How will we conduct this research? NLP : We will build on previous harmonization work within CLS cohorts to develop new AI based algorithms that allow automated harmonization of mental health measures. PPI: We will conduct scoping exercises with researchers and young people which form the basis of future co-creating work that will inform the development of the harmonization tool and platform. Platform: the new tool and global research platform will collate MH measures of different cohort studies, and will aid research harmonization and collaboration.