Risk rates and profiles at intake in child and adolescent mental health services: A cohort and latent class analyses of 21,688 young people in South London
Barry Coughlan, Matt Woolgar, Rick Hood, Dustin Hutchinson, Ella Denford, Amy Hillier, Keith Clements, Teresa Geraghty, Ava Berry, Paul Bywaters, Andy Bilson, Jack Smith, Taliah Drayak, David Graham, Francesca Crozier-Roche, Robbie Duschinsky
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引用次数: 0
Abstract
Background
Children and young people (CYP) seen by child and adolescent mental health services (CAMHS) often experience safeguarding issues. Yet little is known about the volume and nature of these risks, including how different adversities or risks relate to one another. This exploratory study aims to bridge this gap, examining rates at entry to services and profiles of risk using a latent class analysis.
Methods
Data were extracted for CYP who received at least one risk assessment at CAMHs in South London between January 2007 and December 2017. In total, there were 21,688 risk assessments. Latent class analysis was used to identify profiles of risk from the risk assessments.
Results
Concerns about parent mental health (n = 5274; 24%), emotional abuse (n = 4487; 21%), violence towards others (n = 4210; 19%), destructive behaviour (n = 4005; 18%), and not attending school (n = 3762; 17%) were the most commonly identified risks. Six distinct profiles of risk were identified from the latent class analyses: (1) maltreatment and externalising behaviours, (2) maltreatment but low risk to self and others, (3) antisocial behaviour, (4) inadequate caregiver supervision and risk to self and others, (5) risk to self but not others, and (6) mental health needs but low risk.
Conclusions
These findings provide fresh insights into adverse experiences and risks identified by CAMHS. For professionals, the profiles identified in this study might provide insights into profiles of identified risks, in contrast to traditional cumulative approaches to risk. For researchers, these profiles may be fertile ground for hypothesis-driven work on the association between adversity and later outcomes.