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Child protection systems monitoring is key to ensuring children's wellbeing. In England, monitoring is rooted in onsite inspection, culminating in judgements ranging from 'outstanding' to 'inadequate'. But inspection may carry unintended consequences where child protection systems are weak. One potential consequence is increased child welfare intervention rates. In this longitudinal ecological study of local authorities in England, we used Poisson mixed-effects regression models to assess whether child welfare intervention rates are higher in an inspection year, whether this is driven by inspection judgement, and whether more deprived areas experience different rates for a given inspection judgement. We investigated the impact of inspection on care entry, Child Protection Plan-initiation, and child-in-need status. We found that inspection was associated with a rise in rates across the spectrum of interventions. Worse judgements yielded higher rates. Inspection may also exacerbate existing inequalities. Unlike less deprived areas, more deprived areas judged inadequate did not experience an increase in the less intrusive 'child-in-need' interventions. Our findings suggest that a narrow focus on social work practice is unlikely to address weaknesses in the child protection system. Child protection systems monitoring should be guided by a holistic model of systems improvement, encompassing the socioeconomic determinants of quality. [ABSTRACT FROM AUTHOR]

In England, administrative data on children's needs are recorded following a social work assessment. These data are typically used to understand prevalence of individual risk factors and to inform processes, such as the work of local safeguarding partners and multi-agency services. However, reporting individual factors at assessment cannot capture the complexity and heterogeneity of multiple and overlapping needs. This study aimed to identify common types of demand, via a limited number of clusters, using the factors recorded in a national data-set of over 4.2 million assessments carried out between 2014 and 2021, of which 3.6 million had at least one factor recorded. Latent class analysis was used to identify twelve distinct categories of demand for children's social care services, which were consistent across local authorities. Conditional probabilities were used to interpret the demand represented by each category, in consultation with stakeholders. The most prevalent category was domestic abuse and violence (19.7 per cent), followed by complexities around parental mental health (18.4 per cent). Other categories included disability, child mental health, risks outside the home, complex domestic abuse and concerns about another person in the family or household. This article examines some of the operational and planning implications of categorising demand in this way. [ABSTRACT FROM AUTHOR]

Randomised controlled trials are often inappropriate for many forms of preventative children's services; as such, observational studies using administrative data can be valuable for evidence-based policymaking. However, estimates of effectiveness can be confounded by differences in thresholds of intervention and national policies that exert pressure on local trends. This study adjusted for these factors using methods developed in clinical psychology to control for individual traits and developmental trajectories, Autoregressive Latent Trajectory Models with Structured Residuals, to analyse the relationship between local authority preventative spending and Children in Need (CIN) rates in England. Higher spending was associated with significant decreases in CIN rates between 2010/11 and 2014/15, but not from 2014/15 onwards. In the first half of the decade, 1% increases in expenditure were associated with between 0.07% and 0.157% decreases in CIN rates. Based on average local authority spending cuts, this translates to an additional 13,000 to 16,500 children and young people put or kept at risk of developmental or health impairments nationally for each year between 2011 and 2015. These findings highlight the potential of early help/family support policies and concerns around how their effectiveness has changed consequent to prolonged austerity and a deliberate policy focus on 'what works'. [ABSTRACT FROM AUTHOR]

Research exploring inequalities in UK child welfare interventions has produced counter-intuitive findings with respect to Northern Ireland (NI). Despite experiencing the highest levels of deprivation, NI also displays the lowest rates of children in care of all the UK nations. With reference to wider evidence in the field of child welfare inequalities, this article details the findings of two exploratory mixed methods case studies, located within NI Health and Social Care Trusts. Drawing on the narratives offered by child and family social workers, a series of possible explanations for NI's significantly lower out of home care rates are considered. We suggest the operation of intersecting factors at multiple levels, including social work systems and practices, early help systems and structures, communities and families. These findings extend understandings of NI's out of home care rates whilst raising broader questions for social work research and practice. [ABSTRACT FROM AUTHOR]

Delineation of the full integration of quantitative and qualitative methods throughout all stages of multisite mixed methods case study projects remains a gap in the methodological literature. This article offers advances to the field of mixed methods by detailing the application and integration of mixed methods throughout all stages of one such project; a study of child welfare inequalities. By offering a critical discussion of site selection and the management of confirmatory, expansionary and discordant data, this article contributes to the limited body of mixed methods exemplars specific to this field. We propose that our mixed methods approach provided distinctive insights into a complex social problem, offering expanded understandings of the relationship between poverty, child abuse, and neglect. [ABSTRACT FROM AUTHOR]