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Maternal Mental Health and Children’s Problem Behaviours: A Bi-directional Relationship?

Emily Lowthian Orcid Logo, Stuart Bedston, Sara Madeleine Kristensen, Ashley Akbari Orcid Logo, Rich Fry Orcid Logo, Katy Huxley, Rhodri Johnson, Hyun Sue Kim, Rhiannon Owen Orcid Logo, Chris Taylor, Lucy Griffiths Orcid Logo

Research on Child and Adolescent Psychopathology, Volume: 51, Issue: 11, Pages: 1611 - 1626

Swansea University Authors: Emily Lowthian Orcid Logo, Stuart Bedston, Ashley Akbari Orcid Logo, Rich Fry Orcid Logo, Rhodri Johnson, Rhiannon Owen Orcid Logo, Lucy Griffiths Orcid Logo

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Abstract

Transactional theory and the coercive family process model have illustrated how the parent-child relationship is reciprocal. Emerging research using advanced statistical methods has examined these theories, but further investigations are necessary. In this study, we utilised linked health data on ma...

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Published in: Research on Child and Adolescent Psychopathology
ISSN: 2730-7166 2730-7174
Published: Springer Science and Business Media LLC 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa63770
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Abstract: Transactional theory and the coercive family process model have illustrated how the parent-child relationship is reciprocal. Emerging research using advanced statistical methods has examined these theories, but further investigations are necessary. In this study, we utilised linked health data on maternal mental health disorders and explored their relationship with child problem behaviours via the Strengths and Difficulties Questionnaire for over 13 years. We accessed data from the Millennium Cohort Study, linked to anonymised individual-level population-scale health and administrative data within the Secure Anonymised Information Linkage (SAIL) Databank. We used Bayesian Structural Equation Modelling, specifically Random-Intercept Cross-Lagged Panel Models, to analyse the relationships between mothers and their children. We then explored these models with the addition of time-invariant covariates. We found that a mother’s mental health was strongly associated over time, as were children’s problem behaviours. We found mixed evidence for bi-directional relationships, with only emotional problems showing bi-directional associations in mid to late childhood. Only child-to-mother pathways were identified for the overall problem behaviour score and peer problems; no associations were found for conduct problems or hyperactivity. All models had strong between-effects and clear socioeconomic and sex differences. We encourage the use of whole family-based support for mental health and problem behaviours, and recommend that socioeconomic, sex and wider differences should be considered as factors in tailoring family-based interventions and support.
Keywords: Maternal mental health, Child development, Structural equation modelling, Millennium Cohort Study, Bayesian analysis
College: Faculty of Humanities and Social Sciences
Funders: This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-9006) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. This work was supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research and Data (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1).
Issue: 11
Start Page: 1611
End Page: 1626