Forecasting The Population At Risk of Generating Public Law Work

1. Forecasting The Population At Risk of Generating Public Law Work PETER SHIER 10th June 2011 A workstream of the ‘Access to Justice Forecasting Development Project’

2. TRENDS IN PUBLIC LAW CHILDREN ACT PROCEEDINGS Climbie Trial Concludes Jan 2001 Death of Peter Connolly Aug 2007 Death of Victoria Climbie Feb 2000 Total Public Law Children Act Cases New Child Protection Plan Registrations Numbers of Social Workers

3. MODEL 3 Public Law Proceedings MODEL 1 Domestic Violence MODEL 5 Financial Provision inc Ancillary Relief MODEL 2 Private Law - Children MODEL 4 DIVORCE PROJECTIONS MODEL 3 : Public Law Proceedings DIVORCE PRIVATE LAW PUBLIC LAW  3

4. WHAT DRIVES PUBLIC LAW WORK ?We Have Drawn Upon A Wide Range of Expertise • CAFCASS • Relate • Resolution • British Association of Social Workers • Family Law Bar Association • Magistrates Association • NSPCC • Justices Clerk Society • Colleagues across MoJ, HMCS and also DFE, DWP & ONS. 4

5. Advisory group workshops revealed a complex system for Public Law work with many inter-relating drivers DEMOGRAPHIC EXTERNAL • Age of Children under 4 • Numbers of children • Population Growth • External agencies better at sharing information • Public awareness increased • Number of health visitors prevents cases worsening • Shock events (Death of Peter Connolly , Victoria Climbe) FINANCIAL ECONOMIC POTENTIAL DEMAND DEMAND COURTS & LEGAL AID Take Up • Income Deprivation • Child Poverty • Level of unemployment • Schools , GPs, Police more aware of risk factors • Capacity constraints , Number of Social Workers • Local Authority perception of risks • Increasing complexity / nastiness of cases • Care Reforms, more pre-court preparation & Use of alternatives eg EPOs • Court Fees (see Plowden Report) • Benefit Reforms / Changes • Levels of Central Government Funding BEHAVIOURAL ATTITUDINAL • Prevalence of parental mental health • Long term illness • Drug & alcohol abuse • Inter-generational effects • Prevalence of hard to reach families • Family stresses, recent divorce, partnership dissolution, loss of employment • At risk of Domestic Violence 5

6. Advisory group workshops revealed a complex system with many inter-relating drivers …..and then if we add-in the feedback loops! DEMOGRAPHIC EXTERNAL • Age of Children under 4 • Numbers of children • Population Growth • External agencies better at sharing information • Public awareness increased • Number of health visitors prevents cases worsening • Shock events (Death of Peter Connolly , Victoria Climbe) + FINANCIAL ECONOMIC POTENTIAL DEMAND DEMAND COURTS & LEGAL AID Take Up • Income Deprivation • Child Poverty • Level of unemployment • Schools , GPs, Police more aware of risk factors • Capacity constraints , Number of Social Workers • Local Authority perception of risks • Increasing complexity / nastiness of cases • Care Reforms, more pre-court preparation & Use of alternatives eg EPOs • Court Fees (see Plowden Report) • Benefit Reforms / Changes • Levels of Central Government Funding + BEHAVIOURAL ATTITUDINAL • Prevalence of parental mental health • Long term illness • Drug & alcohol abuse • Inter-generational effects • Prevalence of hard to reach families • Family stresses, recent divorce, partnership dissolution, loss of employment • At risk of Domestic Violence + 6

7. A simpler conceptual model was developed to form the basis of our investigations. CHILD POPULATION Number of Social Workers NEW CPP REGISTRATIONS INITIAL ASSESSMENTS DEMAND COURTS & LEGAL AID Take Up INTERVENTION SUCCESSFUL REFERRED by GPs, School, Police, Other Protection Agencies. At Risk of Domestic Violence • Other Household Characteristics • Drug / Alcohol Abuse • Parental Mental Health • Income Deprivation including impact on mental health, long term illness, benefits etc, Child Poverty AT RISK POPULATION 7

8. Working Assumption : The size of the “At Risk population drives the number of initial assessments CHILD POPULATION Number of Social Workers NEW CPP REGISTRATIONS INITIAL ASSESSMENTS DEMAND COURTS & LEGAL AID Take Up INTERVENTION SUCCESSFUL REFERRED by GPs, School, Police, Other Protection Agencies. At Risk of Domestic Violence • Other Household Characteristics • Drug / Alcohol Abuse • Parental Mental Health • Income Deprivation including impact on mental health, long term illness, benefits etc, Child Poverty AT RISK POPULATION 8

9. Problem: We have very little descriptive data about previous ‘customers’ Solution: Use a tool called MOSAIC How Do We Identify and Measure the “At Risk population? We do have address details What is MOSAIC? It uses many different data sources to describe the neighbourhood of each postcode. For example my area is described as… Demographics and Family Structure Home Sharers Married/cohabiting 5-9 yrs or less than 1 yr Age 26-35 Economic No savings Net household wealth £10,000-£25,000 Individual income >£1,000 or <£2,500 Singles and sharers occupying converted Victorian houses MOSAIC Descriptive information about the customer base Postcodes of people granted legal aid MOSAIC descriptions of neighbourhoods + =

10. MOSAIC TYPE (15 CLUSTERS)

11. Correlation Between Public Law Take – Up Rates & Mosaic Indices …and about 900 Other Mosaic Indices R2

12. Results - Snapshot

13. Public Law Children Mosaic Descriptions of Previous Households Involved In Public Law Proceedings Used For Forecasting The “At Risk” Population Neurotic Drugs a big problem in the area Depression Bi-polar disorder Age 26-30 Small properties Gross income less than £10,000 Schizophrenia Single Dependant children Long term sick/disabled Cohabiting Council/Housing Association Unemployed Lone parents Incapacity Benefit JSA Claimants Children aged 0-4 Domestic Violence Homesharers Black African or Black Caribbean Net wealth less than £10,000 Filter used Indicators used

14. Parent Profiles Concerns About Mental Health 48% of cases in Hunt et al (1999) 43% of cases in Brophy (2003) Substance Abuse 23% of cases included allegations of drug abuse (Brophy 2003) 20% of cases included drug & alcohol abuse (hunt et al 1999) Domestic Violence 45% of cases (Brophy 2003) upto 65% in White British Group. 51% of cases (Hunt et al) Step Families 58% of children were not full siblings of an “index child” ((Hunt et al 1999) Income Support 84% of parents dependant on income support (Hunt et al 1999) Parents Involved In Crime 61% of cases (Hunt et al 1999) 20% of Cases (Brophy et al 2003) Independent ResearchDCA Research Series 5/06 May 2006Research Review : Child Care Proceedings Under the Children Act 1989

15. How Can We Use The Suggested Characteristics of Households That Generate Public Law Work to Forecast an “At Risk” Population ? Public Law Proceedings Household Characteristics Suggested By Mosaic Indices FAMILY RESOURCES SURVEY

16. Estimating An Index For The Number of Households “At Risk” of Public Law Proceedings Individual R-Squared Values Reflect The correlation between specific Mosaic Variables & The Take-Up for Public Law work(certificates issued per 1000 of population)

17. Estimating An Index For The Number of Households “At Risk” of Public Law Proceedings

18. 0 Trends within population with dependant children Unemployed Cohabiting Lone Parents Children aged 0-4 We estimate that the “At Risk population has been increasing since 2001. Cohabitation or An Increase in Step Families Appears To Be A Key Driver.

19. CPP Registrations as a % of at risk population New Registrations for Child Protection Plans (CPPs) as a percentage of the estimated population “at risk” have been very stable. At Risk Population New CPP Registrations Climbie Trial Concludes 12th January 2001 Death of Victoria Climbie 25th February 2000 Baby-P trial concludes November 2008 Report on Victoria Climbie’s Death Published

20. Looking At The Data In Different WaysPopulation Effects:In 2008 there were more women under 30 years of age, with children, in households with higher risk indicators for public law proceedings, compared to 2004

21. Looking At The Data In Different WaysPopulation Effects:In 2008 there were more women under 30 years of age, with children, in households with higher risk indicators for public law proceedings, compared to 2004

22. Looking At The Data In Different WaysPopulation Effects:In 2008 there were more women under 30 years of age, with children, in households with higher risk indicators for public law proceedings, compared to 2004 • Emergency Department Admissions : Parental Violence Towards ChildrenAged Under 10: [1] • 8% Increase in 2008-9 • 20% Increase in 2009-10 [1] Violence in England & Wales in 2010 An Accident & Emergency Perspective

23. Inward migration appears to have played a key role Younger people more likely to have pre-school aged children Less Likely To Access Public Services eg 22% of entitled non recipients of income support are under 25 compared to 16% of all recipients Speculated that whilst the potential size of the “at risk” population may have increased, families with younger children may be less visible: Substantial number of immigrants

24. CPP Registrations as a % of at risk population How Can We Forecast The “At Risk” Population ? At Risk Population New CPP Registrations ? Climbie Trial Concludes 12th January 2001 Death of Victoria Climbie 25th February 2000 Baby-P trial concludes November 2008 Report on Victoria Climbie’s Death Published

25. Cohort Effects : Risk Tracked Through Generations FRS 2000 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 Estimated “At Risk” Population Aged 25 Born 1975

26. Cohort Effects : Risk Tracked Through Generations FRS 2000 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 Estimated “At Risk” Population Aged 25 Born 1975 Estimated “At Risk” Population Aged 20 Born 1980

27. Cohort Effects : Risk Tracked Through Generations FRS 2000 FRS 2001 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 Estimated “At Risk” Population Aged 26 Born 1975 Estimated “At Risk” Population Aged 21 Born 1980

28. Cohort Effects : Risk Tracked Through Generations FRS 2000 FRS 2001 FRS 2002 FRS 2003 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 Etc….. Estimated “At Risk” Population Aged 28 Born 1975 Estimated “At Risk” Population Aged 23 Born 1980

29. Tracking the size of the at risk population in all generations allows us to predict future generational patterns and therefore forecast the at risk population

30. QUESTIONS ?