Lacey, Rebecca;
(2023)
Network Analysis as an Emerging Method in Adversity Research – a Reflection on Pollman et al. (2022).
Research on Child and Adolescent Psychopathology
, 51
pp. 1785-1787.
10.1007/s10802-023-01063-y.
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Abstract
In this issue, Pollmann and colleagues (2022) apply network analyses to childhood and adolescent adversity data. They use the rich, longitudinal data from the Avon Longitudinal Study of Parents and Children. By applying network analyses, they draw-out clusters of adversities and the strength of relationships between these clusters and individual adversities with later mental health, substance use and wellbeing. The authors additionally look at adversity clusters in two developmental stages - childhood and adolescence. This commentary discusses how adversity clustering has typically been captured in studies in the past, what network analyses might offer this area of research, and the contribution of the study by Pollmann et al. (2022). The commentary concludes with some reflections and recommendations for the future of adversity clustering research.
Type: | Article |
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Title: | Network Analysis as an Emerging Method in Adversity Research – a Reflection on Pollman et al. (2022) |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/s10802-023-01063-y |
Publisher version: | https://doi.org/10.1007/s10802-023-01063-y |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10168231 |
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