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| Funder | Economic and Social Research Council |
|---|---|
| Recipient Organization | University of Bath |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Mar 30, 2028 |
| Duration | 1,277 days |
| Number of Grantees | 1 |
| Roles | Student |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2914706 |
Abstract
Antisocial behaviour (AB) and substance use (SU) are major public health concerns that carry an enormous financial burden and increase the risk of adverse outcomes. Numerous studies indicate that many risk and protective factors are common to both AB and SU. Some findings suggest that AB frequently co-occurs with SU.
However, there is also evidence of heterogeneity in AB (e.g., aggression, delinquency) and SU (e.g., alcohol, smoking). For example, SU seems to share greater commonality with delinquency than aggression, while aggression is associated with the simultaneous use of alcohol with methamphetamine but not ecstasy. What is the nature and extent of the relationship between AB and SU?
What is the stability and change of co-occurrence of AB and SU, and which factors predict the developmental pattern of these associations across time? What are the core features and bridge symptoms of AB and SU, and the predictive features of co-occurring AB and SU across time? What are the strongest risk and protective factors for classifying co-occurring AB and SU?
To address these unsolved questions, the overall objective is to investigate the mechanisms for the development of co-occurrence of AB and SU in young people across time by conducting four quantitative studies using a current ESRC-funded UK birth cohort. Findings will provide clinical implications on the prevention and intervention programmes for AB or SU alone or in combination.
Technical Summary
Four quantitative studies employing cross-sectional and longitudinal designs will be conducted applying multiple statistical and programming skills for data analysis from an interdisciplinary perspective, including systematic review and meta-analysis, latent variable modelling, network analysis and machine learning algorithms. Each study will use statistical programme code to handle datasets using R programming and Mplus, especially three of the four studies that feature a large longitudinal birth cohort sample using advanced quantitative methods in social science.
Planned Impact
The proposal research will address a major societal challenge of co-occurring AB and SU in young people by generating new knowledge to advance our understanding of the co-occurrence of AB and SU as well as identifying factors predicting co-occurring AB and SU from adolescence to early adulthood using advanced quantitative methods from an interdisciplinary perspective. This research has the potential to translate the clinical implications of the complex interplay between AB and SU to practitioners by informing targeted and personalized strategies to decrease risks for severe adverse outcomes in practice.
Findings will help inform the timing and focus of prevention and intervention programmes for these conditions individually and in combination, with potential benefits for young people and their families, mental health researchers, health, social care, education and legal practitioners and services, and policymakers.
University of Bath
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