children and crime – guidelines for the development of an index of youth crime indicators
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CHILDREN AND CRIME – GUIDELINES FOR THE DEVELOPMENT OF AN INDEX OF YOUTH CRIME INDICATORS
Willem JH RoestenburgAssociate Professor: University of JohannesburgCo-Director: Afri.Yze Consult (Pty) Ltd. & A.Yze LLC (USA)
OBJECTIVES OF THE PRESENTATION
To provide an overview of the author’s work regarding a South African developed system of Family Well Being indicators designed for the Social Welfare field (Roestenburg, W, 1999)
To show how the Family Well being indicators performed in another study involving youth offenders (Roestenburg & Oliphant, 2008)
To explore possible programme effectiveness indicators from the Youth offender study.
To provide some guidelines regarding the way forward in developing youth crime indicators in South Africa
WHY ARE SOCIAL INDICATORS NOT USED MORE EXTENSIVELY IN THE SOUTH AFRICAN SOCIAL WELFARE FIELD?
The White Paper for Social Welfare (1997) frequently refers to the lack of information in many areas of social welfare planning.
Dept of Social development uses various international and macro level indicators
The level of knowledge in the welfare field not as developed as in other countries
Social welfare Indicators not a field that attracts many scholars
THE INDICATORS OF FAMILY WELL BEING STUDY (ROESTENBURG: 1999)
Commissioned project to develop a system of indicators for the welfare field.
This had to be used as information tools in the field of social welfare planning
The initial development had to be done within Gauteng, a province in South Africa
METHOD OF DEVELOPMENT
Stage 1: Description of the information problem – What is meant by “welfare” and what is to be measured?
Stage 2: Identification of relevant theory/pragmatic base
Stage 3: Indicator identification, selection and primary measure design
Stage 4: Measurement of subjective QOL and Indicators
Stage 5: Statistical Indicator Model and Index development
Stage 6: Implementation
RESULTS OF THE FW-INDICATOR STUDY Ecological paradigm as theory Focus groups of Social Workers were used to determine a gross list of
indicator variables Measures were self designed based on Ecological concepts as outlined. Well
being was measured on 7 dimensions: Power management, Goal inclination, Emotional functioning, Responsible functioning, Dependency, Value-based decision making and Social Aspects of poverty
A multi-cultural quota sample was selected by means of accidental selection method. The study aimed to reach a cross section of households in the population. Population statistics were used to determine the population size
508 respondents participated in the study Scale dimensions were established from second order Principle Axis factor
analysis and reliability analysis by means of Cronbach’s Alpha Indicators were identified by means of General Linear Modeling (GLM)
technique. The best fitting overall model is presented here Indexes were compiled for five of the seven dimensions based on model
significance levels and adjusted R2 values.
OVERALL BEST FITTING INDICATOR MODEL
Variable Value F - value DF P
Language .605 3.04 16 .000**
A17: Residential mobility .775 3.09 8 .004**
A18-3: Home-ownership .823 2.28 8 .029**
A21: Alcohol consumption changes .833 2.13 8 .041**
Educational qualifications .602 3.07 16 .000**
Marital status .738 3.78 8 .001**
Family composition .739 1.74 16 .044**
KEY INDICATORS IN FW STUDY
Language group (English, Afrikaans or African) (Used as grouping variable)
Marital status (Married or unmarried and single) married = + and single = -
Household size (1 – 3, 4 – 5, 6+ members) Large = +, small = - Educational level (Below 10th grade, Gr 11 – 12, Post School
qualification) Residential mobility (Measures whether families moved
residence during the past five years) Yes = + and No = - Home ownership (Whether residents own the house they live
in). Yes = + and No = - Changes in Alcohol consumption over the past five years.
(Increase or decrease in drinking alcoholic beverages) Decrease = +; increase = -
ILLUSTRATION OF INDEX WEIGHTS: POWER MANAGEMENT
No(-1.947)
Yes
Changes inAlcohol
Consumption
EducationalQualifications
ResidentialMobility
HomeOwnership
MaritalStatus
FamilyComposition
No(8.150)
Yes6+
Members4-5
Members(6.443)
1-3Members(2.281)
NotMarried(4.648)
MarriedNo(.313)
Yes
Certificate/
DegreeStd 9-10(2.653)
<= Std 8(6.245)
Copyright, 1998 W Roestenburg
INDICATOR INDICES
Family Power Management Responsibility management Goal Inclination Emotional functioning Value-based functioning
EXAMPLE 2: CHARACTERISTICS OF YOUTH OFFENDER STUDY
Purpose: To begin evaluation of Social Development programmes to youth. Obtain profile of factors of crime; perceptions about programmes
Method: quantitative survey of children in programmes measuring a) Factors of crime and b) programme perceptions. Qualitative description of service provider views on factors and outcomes
Sample: 309 male/females children 15 – 18 years of age. All were either in Secure Care or had just completed a variety of Diversion programmes.
Measures: Self-developed measures – developed from literature and a panel’s input
Measures designed for low reading level (Grade 5 – 7)
MEASURES USED
Family Risk Behaviour measure (FRB) (22 items; α = .859, “negative” scale)
Service perceptions Index (SPI) (11 items; α = .796; “positive” scale)
Programme Impact Index (PI) (11 items; α .847; “positive” scale)
Post Programme Behaviour Index (PPB) (29 items: α = .910; “positive” scale)
Post programme Insight (PPI) (12 Items; α = .865; “positive” scale)
Post programme remorse (PPR) (12 items: α = .765; “positive” scale)
MAIN RESULTS OF YOUTH STUDY: FW INDICATORS
Home ownership: 80% of parents owned the houses they lived in and in
Mobility: 42% social mobility. Marital status: 66% single parent families. (In 39% of
cases both parents took care of children, 46% grew up primarily with a single caregiver.)
Education: 54% of parents have an education below 10th Grade
Family composition: Mean family size 3.5 members. The smallest number was 2 and the largest 8
Alcohol consumption: 84% of respondents indicated a decrease in the family’s alcohol consumption over the past 5 years
INSTANCES WHERE INDICATORS PLAYED A SIGNIFICANT ROLE
Indicator Dimension P – value Interpretation
Residential mobility
•Family Risk Behaviour•Service Perceptions
.041
.026
Less mobile = more riskMore mobile = Less positive about programme
Home ownership Service Perceptions
.037 Own = more positive about programme
Marital status Service Perceptions
.006 Divorced = less positive about programme
Educational level of parent
No differences - -
Alcohol consumption
No differences - -
Family Size No differences - -
Language No differences - -
OTHER POTENTIAL INDICATORS OF CHILD WELL BEING
Item Dimension
P-value
Interpretation
Participation in religious group
PPI .045 Participation = More insight
Periodic homelessness
FRBPPR
.016
.046Homeless = more riskAt home = more positive
School attendance
PIPPIPPRPPB
.020
.001
.011
.004
School attending = more impactSchool attending = more insightSchool attending = more remorseSchool attendance = improved behaviour
Child’s drug use prior to offence
PPB .051 Used before = more negative
At home at time of crime
FRBPIPPBPPI
.001
.002
.022
.002
= less problematic family= more impact= improved behaviour= more insight after programme
THE WAY FORWARD (FWI)
System not implemented by Government. Data availability remained a problem Implementation required further work which received
no further budget Author practically tested the FW indices to assess
family QOL in a Botswana Mining Village (2001) where family abuse was reported. Results: FWI identified and confirmed family abuse risk in village. Confirmed results from focus groups and survey
System is currently implemented as part of a case management Information system at a major NGO in welfare called FAMSA (Families South Africa)
PRODUCT LOGO FOR WEB-BASED DATA MANAGEMENT SYSTEM
INDICATOR DATA ENTRY POINTS
SCREENSHOT OF FAMSA CLIENT WELL BEING PROFILE
CONCLUSIONS
The South African Indicator System for use in the welfare sector is under constant development
This system has potential to be adapted for use with youth offender programme evaluation as shown
A few potential programme indicators for youth offenders have been identified that need to be developed and tested in further research
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