Harmonised collection of data in youth mental health: Towards large datasets. (January 2020)

• Record Type: Journal Article
• Authors: Lavoie, Suzie; Allott, Kelly; Amminger, Paul; Bartholomeusz, Cali; Berger, Maximus; Breakspear, Michael; Henders, Anjali K; Lee, Rico; Lin, Ashleigh; McGorry, Patrick; Rice, Simon; Schmaal, Lianne; Wood, Stephen J
• Is Part Of: Australian and New Zealand journal of psychiatry. Volume 54:Number 1(2020)
• Page Start: 46
• Page End: 56
• Publication Date: 2020-01
• Subjects: Harmonisation -- data sharing -- transdiagnostic -- neurocognition -- neuroimaging; Psychiatry -- Periodicals; Psychiatry -- Australia -- Periodicals; Psychiatry -- New Zealand -- Periodicals; 616.89005
• DOI: 10.1177/0004867419844322
• Languages: English
• ISSNs: 0004-8674

Abstract

Objective: The current international trend is to create large datasets with existing data and/or deposit newly collected data into repositories accessible to the scientific community. These practices lead to more efficient data sharing, better detection of small effects, modelling of confounders, establishment of sample generalizability and identification of differences between any given disorders. In Australia, to facilitate such data-sharing and collaborative opportunities, the Neurobiology in Youth Mental Health Partnership was created. This initiative brings together specialised researchers from around Australia to work towards a better understanding of the cross-diagnostic neurobiology of youth mental health and the translation of this knowledge into clinical practice. One of the mandates of the partnership was to develop a protocol for harmonised prospective collection of data across research centres in the field of youth mental health in order to create large datasets. Methods: Four key research modalities were identified: clinical assessments, brain imaging, neurocognitive assessment and collection of blood samples. This paper presents the consensus set of assessments/data collection that has been selected by experts in each domain. Conclusion: The use of this core set of data will facilitate the pooling of psychopathological and neurobiological data into large datasets allowing researchers to tackle important questions requiring very large numbers. The aspiration of this transdiagnostic approach is a better understanding of the mechanisms underlying mental illnesses.