Predictive risk modelling to prevent child maltreatment and other adverse outcomes for service users: inside the "black box" of machine learning

Gillingham, Philip (2016) Predictive risk modelling to prevent child maltreatment and other adverse outcomes for service users: inside the "black box" of machine learning. The British Journal of Social Work, 46 4: 1044-1058. doi:10.1093/bjsw/bcv031

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Author Gillingham, Philip
Title Predictive risk modelling to prevent child maltreatment and other adverse outcomes for service users: inside the "black box" of machine learning
Journal name The British Journal of Social Work   Check publisher's open access policy
ISSN 0045-3102
1468-263X
Publication date 2016
Year available 2015
Sub-type Article (original research)
DOI 10.1093/bjsw/bcv031
Open Access Status Not Open Access
Volume 46
Issue 4
Start page 1044
End page 1058
Total pages 15
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Collection year 2016
Language eng
Formatted abstract
Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can ‘learn’, it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the ‘black box’ of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services.
Keyword Predictive risk modelling
Risk assessment
Preventative intervention
Social work
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Nursing, Midwifery and Social Work Publications
 
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Created: Sun, 12 Apr 2015, 19:22:59 EST by Philip Gillingham on behalf of School of Nursing, Midwifery and Social Work