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Child and adolescent mental health
Five models for child and adolescent data linkage in the UK: a review of existing and proposed methods
  1. Karen Laura Mansfield1,2,
  2. John E Gallacher1,
  3. Miranda Mourby3,
  4. Mina Fazel1,4
  1. 1 Department of Psychiatry, University of Oxford, Oxford, UK
  2. 2 Oxford Health NHS Foundation Trust, Oxford, UK
  3. 3 Centre for Health, Law and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
  4. 4 Children's Psychological Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
  1. Correspondence to Dr Karen Laura Mansfield, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; karen.mansfield{at}


Over the last decade dramatic advances have been made in both the technology and data available to better understand the multifactorial influences on child and adolescent health and development. This paper seeks to clarify methods that can be used to link information from health, education, social care and research datasets. Linking these different types of data can facilitate epidemiological research that investigates mental health from the population to the patient; enabling advanced analytics to better identify, conceptualise and address child and adolescent needs. The majority of adolescent mental health research is not able to maximise the full potential of data linkage, primarily due to four key challenges: confidentiality, sampling, matching and scalability. By presenting five existing and proposed models for linking adolescent data in relation to these challenges, this paper aims to facilitate the clinical benefits that will be derived from effective integration of available data in understanding, preventing and treating mental disorders.

  • child & adolescent psychiatry
  • depression & mood disorders

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  • Contributors KLM, MF and JEG conceived the study. KLM drafted the manuscript. MF and JEG helped refine the manuscript and MM provided additional input on ethical, legal and governance aspects. All authors have read and approved the final version.

  • Funding This paper represents independent research funded by an MRC Mental Health Data Pathfinder award to the University of Oxford (MC_PC_17215) and by the NIHR Oxford Health Biomedical Research Centre (BRC-1215-20005). MF was funded by the National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) Oxford and Thames Valley. DPUK provided infrastructure for this project through MRC grant ref MR/L023784/2. The views expressed are those of the authors and not necessarily those of the MRC, NHS, the NIHR or the Department of Health and Social Care.

  • Competing interests MF has an honorary contract with Oxford Health NHS Foundation Trust (OHNHSFT). KM is supported by the Oxford Health BRC, a collaboration between the University of Oxford and OHNHSFT.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data sharing not applicable as no datasets generated and/or analysed for this study. There are no data sets associated with this manuscript.

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