Cause for Concern(s): A Latent Class Analysis of Grounds for Referral to the Children’s Hearings System in Scotland - Soraghan, Joanna; Porter, Robert (International Journal of Population Data Science, 2025)
Objectives The Children’s Hearings System is Scotland’s care and justice system for infants, children and young people. While official statistics indicate how many children are referred to the system under each of a defined set of concerns (or ‘grounds’) annually, little is known about the interplay between the different types of concerns that lead to a child’s referral. Methods As part of the Growing Up in Kinship Care project, data was available on 13,874 referrals for 4,259 children who had spent time living in kinship care and had been referred to the Children’s Hearings System between the years of 2013 and 2019. Latent class analysis was applied to the data on children’s referrals to understand how commonly different concerns were co-reported for children and young people. Results The analysis showed that 79% of the referrals only included one individual ground for concern for the child involved, with 15% of referrals including two concerns for the child. It was far less common for children to be referred on three or more grounds within any one referral. Our Latent Class Analysis identified 7 common groupings (or classes) of concerns that were co-reported – with the class defined as a lack of parental care being the most common (representing 33% of referrals). This was followed by the classes dominated by referrals on the grounds of school attendance/behaviour (15%), alleged offences (14%) and exposure to domestic abuse (13%). Demographic differences for individuals receiving different classes of referrals will also be presented. Conclusion It is widely understood that there are many inter-related and complex challenges faced by children and young people who become involved with the Children’s Hearings System. Our findings suggest that this complexity is not accurately reflected within the administrative data. Explanations for (and implications of) this finding will be considered.