Open AccessBeyond the Toxic Trio: Exploring Demand Typologies in Children’s Social Care
Author(s) -
Rick Hood,
Allie Goldacre,
Calum Webb,
Paul Bywaters,
Sarah Gorin,
Keith Clements
Publication year - 2021
Publication title -
british journal of social work
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.95
H-Index - 81
eISSN - 1468-263X
pISSN - 0045-3102
DOI - 10.1093/bjsw/bcab058
Subject(s) - latent class model , context (archaeology) , consistency (knowledge bases) , typology , intervention (counseling) , welfare , psychological intervention , psychology , sample (material) , agency (philosophy) , ethnic group , developmental psychology , actuarial science , sociology , business , economics , geography , social science , computer science , chemistry , archaeology , chromatography , artificial intelligence , machine learning , psychiatry , anthropology , market economy
Demand for children’s social care is often conflated with rates of intervention and associated with a limited constellation of parental risk factors. This article reports on a more comprehensive picture of demand obtained through a quantitative study of child welfare interventions in England. Longitudinal child-level data were combined from children’s social care services in six English local authorities over a four-year period (2015–2018). Latent class analysis was undertaken for a random sample of child episodes where an assessment was undertaken (n = 15,000). The results were tested for consistency across LAs and to identify the most appropriate number of classes. Conditional probabilities were used to interpret the demand represented by each class, and to explore the relationship between typologies and child characteristics such as age, gender and ethnicity. The analysis found seven classes, or typologies of demand, to be present in factors at assessment across all the LAs, which were linked to certain child characteristics and intervention pathways. The findings go beyond the ‘toxic trio’ terminology often used to profile risks to children and support the innovative use of administrative data to provide insight into patterns of demand. Implications are discussed for strategic responses to child welfare problems and the multi-agency context of prevention.