Developing the actuarial prediction of violent and sexual reoffending

251 Pages·2014·1.59 MB·English

by  Philip Howard

DEVELOPING THE ACTUARIAL PREDICTION OF VIOLENT AND SEXUAL
REOFFENDING

By
PHILIP HOWARD

A thesis submitted to the College of Life and Environmental Sciences of the University of
Birmingham for the degree of DOCTOR OF PHILOSOPHY

School of Psychology
College of Life and Environmental Sciences
The University of Birmingham
April 2013
University of Birmingham Research Archive

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Abstract

This thesis aims to develop and improve the actuarial prediction of violent and sexual offending.
It demonstrates the importance of understanding offence classification and specialisation, and the
value of dynamic risk factors in actuarial risk prediction. Its findings are especially relevant to
prison and probation risk assessment and management practice in England and Wales, where the
National Offender Management Service (NOMS) makes extensive use of the Offender
Assessment System (OASys).
Chapter 1 takes a novel, empirical approach to determining which offences should be counted as
“violent” by a new nonsexual violence risk scale. Chapter 2 then develops this new scale, the
OASys Violence Predictor (OVP), which combines static and dynamic risk factors, and validates
it through comparison with NOMS’s existing scales. Chapter 3 then shows that OVP is also an
equally good or superior predictor of nonsexual violence among offenders with a history of
sexual offending. Chapter 4 shows that OVP’s dynamic risk factors have causal properties and
reassessment over time improves prediction. Chapter 5 demonstrates the significance of offence
specialisation by sexual offenders to risk predictor development. Chapter 6 concludes the thesis
with an overview and discussion of the findings, limitations, practical implications, and future
research directions.

Acknowledgements

I’m very grateful to my supervisor Louise Dixon for her support, guidance and good humour over
the past six years. Louise’s advice on how to write for academic publication - and also navigate
university bureaucracy - has been invaluable. Our chats about rowing, triathlon and our other
sporting adventures have made the PhD experience much more fun than it otherwise would have
been.
Several other people have made vital contributions as both research colleagues and friends. I’ve
greatly enjoyed working with Georgia Barnett, Ruth Mann and Helen Wakeling on chapters of
this thesis, and also appreciate the support of other NOMS colleagues such as Robin Moore and
Rosie Travers. Anna Strevens has provided important reality checks from an operational
probation perspective, and her ability to do this while keeping me company in London’s finest
craft beer establishments has been especially welcome.
My family and friends outside work deserve particular thanks for their patience and
encouragement over what must sometimes have seemed an endless journey. As well as my
sisters, brother and mum, I’d most of all like to thank the Baileys and Marshalls in Croydon,
Ruthie and Gavin in Dulwich, the Lain/Shelley family in Ilkley, Jola in Poland, Xristina in
Greece, and Carol, Gina and Margaret on the other side of the Atlantic!

TABLE OF CONTENTS
Introduction 1-33
Which offences should be targeted in the prediction of ‘violent’ and 1
‘sexual’ offending?
Are violent offenders a separate group? 5
Existing approaches to the prediction of violent and sexual reoffending 8
The history of actuarial risk assessment 8
Generations of risk assessments 10
Professional judgement versus actuarial systems 11
Unstructured professional judgement 11
Structured professional judgement and conceptual actuarial
systems 12
Empirical actuarial systems 12
Commentary on risk assessment typologies 13
Risk factors for violent and sexual reoffending 15
Theoretical explanations for violence 16
Empirical research on the risk factors for future violence 20
Empirical research on the risk factors for sexual reoffending 23
Age and maturity 25
Structure of the thesis 27
Aims 29
Specific aims 30
Samples 30

Statement of Authorship 34

Chapter 1: Developing an Empirical Classification of Violent Offences.
Chapter rationale 35
Howard, P. D., & Dixon, L. (2011). Developing an empirical classification of 37-50
violent offenses for use in the prediction of recidivism in England and Wales.
Journal of Aggression, Conflict and Peace Research, 3, 141-154.
Abstract 37
Introduction 37
Risk assessment in NOMS 38
The need to develop a violence risk scale for NOMS 38
The need to produce a comprehensive classification of violent
offenses 39
Method 40
Overall design 40
Participants 40
Measures 40
Results 41
Determining the nonsexual violent offence content of each offence
group 41
Simple associations between static and dynamic risk factors and
reoffending within each offence type 44
Discussion 47
Conclusion 48
References 49

Chapter 2: The Construction and Validation of the OASys Violence Predictor (OVP)