pol116 nikki leaper fitzwilliam college supervisor: dr...
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POL116
Nikki Leaper
Fitzwilliam College
Supervisor: Dr Katrin Müller-Johnson
A Descriptive Study of Repeat Offending after cautioning or charging for
Domestic Violence
Submitted in part fulfilment of the requirements for the Master’s Degree in
Applied Criminology and Police Management
January, 2014
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Abstract
Many public sector agencies are tackling domestic violence on a daily basis and
utilising a significant amount of resources. Therefore there is no better time to gain a
greater understanding of the issues and potential solutions.
The purpose of this research was to investigate repeat offending after cautioning or
charging for domestic violence. This research was based upon a descriptive study, a
retrospective analysis, using archival data from Devon and Cornwall’s Police force
system. The study focussed on male heterosexual offenders in an adult intimate
relationship over a three year period. The study used a sample of offenders who
were arrested for domestic violence in a twelve month period, followed them up at
twelve months and attempted to predict further offences leading to serious injury,
using the Crown Prosecution Service charging standards to define injuries and the
level of injury.
Analysis looked at offenders’ background characteristics and built on findings from
previous research. For prevalence of reoffending within a twelve month period,
alcohol and drugs were predictors. Unemployment was only a predictor for the
disposal groups that experienced either a caution or were charged and convicted,
but not for the disposal group charged no evidence of conviction. For frequency of
reoffending unemployment was found to be a predictor. The victim’s injury by a
further offence was predicted by age and previous violence.
This study will contribute to the research in the field of domestic violence, providing
an evidence-base focusing on offenders’ characteristics. This research is relevant,
for the findings of this study could have implications to change domestic violence
policy and how we deal with offenders. In turn this may lead to police forces and
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other public sector agencies to look at current domestic violence policy and perhaps
become more effective and efficient in dealing with offenders for this particular crime
type.
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Acknowledgements
Foremost I would like to express my sincere gratitude to my supervisor, Dr Katrin
Müller-Johnson, who over the last few years has provided me with encouragement,
motivation and advice throughout my studies, always available for my questions and
sharing vast knowledge.
I would also like to thank colleagues from Devon and Cornwall Police who provided
me with access to considerable volumes of data and to Carola Saunders in providing
the support that enabled me to make sense of that data.
Finally I would like to thank my family for their patience, support and understanding.
Thank you all very much.
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Contents
Abstract
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Acknowledgements
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Contents
5
List of figures
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List of tables
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Introduction
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Literature Review
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What we know
13
Reporting and under-reporting
14
Prediction of domestic violence
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Risk assessment
21
Personal characteristics of offenders
25
Present research aims
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Methods
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Specific research questions
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Data source
31
Data analysis plan
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Preparation of data/selection of cases
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First 5000 crimes – creating the final data set
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Results
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Description of sample
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Ethnicity
46
Age
47
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Occupation
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Q1 What predicts injury/level of injury at the initial offence?
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Q2 Is there a relationship between offenders’ background variables and prevalence of further domestic violence offending?
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Q3 What predicts frequency of reoffending?
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Q4 What predicts injury in further offences?
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Q5 What predicts increases in the severity of injury in further reoffending?
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Discussion
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The sample
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Q1 What predicts injury/level of injury at the initial offence?
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Q2 Is there a relationship between offenders’ background variables and prevalence of further domestic violence offending?
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Q3 What predicts frequency of reoffending?
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Q4 What predicts injury in further offences?
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Q5 What predicts increases in the severity of injury in further reoffending?
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Limitations
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Conclusion
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Appendices
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Appendix A
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Appendix B
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Appendix C
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References
93
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List of figures
Figure 1: First 5000 Crimes
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Figure 2: Overview of crime types, number of cases and disposal
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Figure 3: Levels of injury in relation to initial disposal
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Figure 4: Level of injury in relation to three types of disposal
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Figure 5: Breakdown of repeat offending in relation to the three types of disposal
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Figure 6: Distribution of ethnicity for all offenders
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Figure 7: Age distribution of the total sample
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Figure 8: Age distribution by disposal type
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Figure 9: Occupation distribution comparing the total sample and repeat offending
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Figure 10: Background variables in the total sample
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Figure 11: Background variables split by initial disposal
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Figure 12a: Influence of alcohol and injury levels
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Figure 12b: Influence of drugs and injury levels
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Figure 12c: Influence of unemployment and injury levels
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Figure 12d: Mental Health and injury levels
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Figure 12e: Use of weapon and injury levels
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Figure 13: Survival graph of reoffending
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Figure 14: Levels of injury at first and second offence
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Figure 15: Levels of severity and disposal types
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List of tables
Table 1: Repeat offending within twelve months of initial disposal, for caution versus charge
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Table 2: Standard occupational classifications
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Table 3: Odds ratio for prevalence of injury
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Table 4: Prevalence of a further offence within twelve months given particular offender characteristics
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Table 5: Odds ratio of reoffending
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Table 6: Mean number of further offences by prevalence/absence of particular offender characteristics
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Table 7: Injury levels at first and second offence
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Table 8: Logistic regression coefficients predicting GBH at further offence
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Table 9: Logistic regression coefficients predicting ABH or GBH at further offence
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Table 10: Odds ratio of a more severe injury for the further offence
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Introduction
Domestic violence is a serious crime which affects many communities; it ruins lives
and can have a lasting impact, in some cases fatal. Since the 1990s domestic
violence has been taken seriously as not only a social but major criminal justice
issue. Many public sector agencies are tackling domestic violence on a daily basis
and utilising a significant amount of resources. Therefore there is no better time to
gain a greater understanding of the issues and potential solutions. More recently the
Home Secretary in September 2013 commissioned Her Majesty’s Inspectorate of
Constabulary to look at the effectiveness of the police response to domestic violence
and abuse across England and Wales.
On a local level domestic violence has contributed in over a third of all murders in
Devon, Cornwall and the Isles of Scilly (Peninsular Strategic Assessment, 2012-
2013). Domestic violence is a complex issue and police forces use risk assessments
in dealing with these incidents and crimes. The risk assessments incorporate many
factors, attempting to predict which victims are facing the most risk of being harmed
(Harne and Radford, 2008). However risk assessments focus mainly on the victim
and not on the offender. How the police service defines and assesses risk is a key
component (Perez-Trujillo and Ross, 2008).
The research into domestic violence is growing and many studies have been
conducted over recent years around the world. In the main most have focused on the
victim, repeat offending or on the effect of arrest (Sherman, 1992). However some
research has focused on offender data. “The accuracy (validity) and consistency
(reliability) of predicting dangerousness and violence depends on multiple complex
factors” (Campbell, 2007:9). Some of these predictive factors include history of
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violence, mental illness, substance abuse, gender, age, unemployment, suicidal
markers and the use of weapons (Campbell et al, 2001).
This thesis is based upon a descriptive study, a retrospective analysis, using archival
data from Devon and Cornwall’s Police force system. The data has been captured
over a three year period and relates to those domestic violence crimes that have
been reported to the police force of Devon, Cornwall and the Isles of Scilly. The
study will focus on male heterosexual offenders in an adult intimate relationship.
Farrington’s Cambridge study in Delinquent Development (1995) has looked at early
childhood precursors of offending, including antisocial child behaviour, poor
parenting and economic deprivation. This study will not be addressing these factors,
but it will take a similar methodological approach by taking risk factors at the time of
the first offence in the data set and using them to try to predict future offending.
The study will be both retrospective and prospective in nature. Retrospective due to
the fact the data has been collected over the last few years and prospective as it will
focus on the crimes in the first year of the data set and then follow-up over a twelve
month period.
Furthermore this study focuses on predicting injury and the level of injury at the initial
offence, following a sample of offenders who have previously been arrested for
domestic violence. The study will then measure injury in a particular way, namely it
will use the Crown Prosecution Service (CPS) charging standards to define injuries
and severity.
Using the data set it will look at offenders’ background characteristics including age,
ethnicity, unemployment, mental health and the use of alcohol, drugs and weapons.
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This study aims to provide an original contribution to current research and a new way
of interpreting the data, strengthening the research in this field. The focus is different
from other studies that look at any type of repeats. Unlike other studies which look at
all repeats this study will only look at arrested offenders who go on to commit crimes
of domestic violence. Reviewing those offenders who after initial disposal, have
either received a cautioned, or have been charged no evidence of conviction or
charged and convicted.
In addition this study will look to see if there is relationship between offenders’
background characteristics and frequency of reoffending. The study will then move to
see what factors predict injury in further offences and finally look at what predicts
increases in injury in further offending.
The study hopes to use the data set and variables to go some way to understand the
social issues and try to predict factors that may increase serious injury in domestic
violence. This research is relevant, for the findings of this study could have
implications to change domestic violence policy and how we deal with offenders. For
example, how we use drug and alcohol referrals, or the effects of cautioning versus
charging an offender.
In turn this may lead to police forces and other public sector agencies to look at
current domestic violence policy and perhaps become more effective and efficient in
dealing with offenders for this particular crime type. This is particularly important
when public services are facing more budgetary constraints and have limited
resources. Testing alternative policies could lead to more effective solutions and
drive operational policing in a new direction.
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This thesis is presented over six chapters. To begin, the literature review looks at
research in the field of domestic violence, specifically what we know; the issues of
reporting and under-reporting; prediction of domestic violence; risk assessment and
personal characteristics of offenders. The research questions are then defined and
the design and approach to this study are highlighted in the methods section. This is
followed by a results chapter highlighting the findings in relation to the research
questions. Then follows a discussion on the results and how this study relates to
earlier research highlighted in the literature review. Lastly the thesis makes some
conclusions and looks to recommendations and next steps.
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Literature Review
What we know
Domestic violence research is vast and encompasses many themes; therefore this
literature review has been broken down into four key areas, providing an overview in
relation to the research questions. The following areas are reviewed:
Reporting and under-reporting
Prediction of domestic violence
Risk assessment
Personal characteristics of offenders
The Association of Chief Police Officers (ACPO) definition of domestic violence is
“any incident of threatening behaviour, violence or abuse (psychological, physical,
sexual, financial or emotional) between adults, aged 18 and over, who are or have
been intimate partners or family members, regardless of gender and sexuality”
(NPIA, 2008:7).
However after public consultation the Home Office announced in September 2012
that the domestic violence definition would be amended in March 2013. The new
definition widens the age gap to include persons aged 16-17 recognising that young
people can be victims of domestic violence. The definition also introduces the term
‘coercive behaviour’. Hence there is a greater recognition of patterns of behaviour
with regard to acts of assaults and/or threats rather than just individual incidents
(Home Office, 2013).
The British Crime Survey (BCS) in 2010-2011 estimated 392,000 incidents of
domestic violence, a rise of 35% compared to estimates in 2009-2010. However due
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to the low numbers of domestic violence victims identified in this survey, the results
are subject to variability, nevertheless this percentage rise is similar to those seen in
previous years (Chaplin et al, 2011). Victims of domestic violence frequently
experience repeat victimisation, which in 2010-2011 accounted for three-quarters
(73%) of all incidents of domestic violence (Chaplin et al, 2011).
There have been many studies looking at the issue of domestic violence and in the
main most have focused on the victim, on repeat offending or on the effect of arrest
(Sherman, 1992).
In 2004 the Home Office conducted a domestic violence study and concluded that
women suffer more injuries than men as a result of domestic violence (Walby and
Allen, 2004). Female victims sustain more injuries than male victims i.e. the
percentage within victims of each sex. Those findings showed that 46% of women
sustained a minor physical injury, compared to 4% among men. 20% of women
sustained a moderate physical injury, compared to 14% among men and 6% of
women sustained severe injuries, compared to 1% among men (Walby and Allen,
2004). Severe injuries making up a small sub-group within the spectrum of injury
related domestic violence.
Reporting and under-reporting
Domestic violence incidents are concealed within the community often behind closed
doors making the issue of reporting difficult. On a local level domestic violence has
contributed in over a third of all murders in Devon, Cornwall and the Isles of Scilly
(Peninsular Strategic Assessment, 2012-2013). Only a quarter of those domestic
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homicides over a ten year period reported previous domestic incidents. These mainly
rural areas had the least number of reported domestic violence incidents overall
(Peninsular Strategic Assessment, 2012-2013). The under-reporting issue limits the
understanding of public sector agencies and hinders the ability to address the
problem.
The police are not always the first to be informed of domestic violence, in fact this
could often be the last call made by a desperate victim. On average women are
assaulted thirty five times prior to reporting (Yearnshire, 1997). Of particular concern
when assessing the scale and impact of domestic violence is the number of reports
and the problem with under-reporting domestic violence offences. It is suggested
that only 28% of domestic violence victims report incidents to the police, 21% being
female victims and 7% being male victims (Marshall and Johnson, 2005).
The British Crime Survey (BCS), aware of this concern and to assist with the data
capture, has produced a self-completion module looking at violent and non-violent
abuse by a partner or family member to hopefully provide better reporting for this
type of offence (BCS, 2010-2011). The self-completion module aims to increase
reporting thereby giving victims some level of confidentiality. The results showed that
victims would report more domestic violence incidents using the self-completion
module due to the added privacy rather than disclose incidents of violence during
face to face interviews. In the BCS 2001, the self-completion module “found
prevalence rates to be three times higher for women and ten times higher for men
than that typically were reported in the BCS” (Marshall and Johnson, 2005:17).
Clinicians have also looked at the issue of under-reporting. A report in the Journal of
Family Violence found that under-reporting was based on “situational factors which
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included relationship characteristics and rational reasons rather than based on
personality traits or social desirability” (Heckert and Gondolf, 2000:423).
Research on reasons for not reporting domestic violence is varied. A domestic
violence study carried out by the Home Office in 2004 raised the issue of under-
reporting and questioned victims as to why they did not report domestic violence
incidents over a given year. Results found that 41% of women and 68% of men
believed the matter to be too trivial. 38% of women and 39% of men believed this to
be a private family matter (Walby and Allen, 2004). Other causes for under-reporting
were that of humiliation, 7% for women and 5% for men. In addition the study found
that 13% of women feared a greater risk of violence especially if the police were
called, yet there was no evident percentage of men who felt the same (Walby and
Allen, 2004).
This fear was also highlighted in other research (Yearnshire, 1997), either fearing the
offender or the fear of losing their children. Furthermore research has highlighted
that not only the fear of retaliation is a reason for under-reporting but also that of
economic and psychological dependence (Buzawa and Buzawa, 2003).
Others argue that victims have not changed their reporting habits since the 1960s
(Felson and Paré, 2005). A National Violence against Women study looked at a
number of physical and sexual assaults reported to the police. Their findings showed
that male victims were disinclined to report assaults by their partners, highlighting the
issue of under-reporting (Felson and Paré, 2005). Interestingly however the study
also suggested that victims of any gender would equally report domestic violence
assaults as well as any other assault if it was caused by people known to them
(Felson and Paré, 2005).
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Research has shown that reporting and under-reporting is one of the key areas to be
considered when working in the field of domestic violence. This chapter will now
move to look at the area of predicting domestic violence.
Prediction of domestic violence
“The foundation for any effort to prevent or control a problem is the capacity to
predict its occurrence” (Sherman and Strang, 1996:10). Studies in this field have
looked at predicting domestic violence in the main whereas others have focused on
predicting injuries from domestic violence. Risk factors have been identified in
various domestic violence studies, providing a useful indicator. These include factors
such employment status (Straus and Gelles, 1990; Kyriacou et al, 1999; Campbell et
al, 2001), substance abuse, alcohol and drugs (Dobash and Dobash 1979; Straus
and Gelles, 1990; Campbell et al, 2001) and location (Rennison and Welchans,
2000).
One such study looked at women who had been victims of domestic violence and
the associated male offenders focusing on behavioural and socio-economic aspects
(Kyriacou et al, 1999). Findings determined that women would be at a greater risk of
injury if their male partners were mainly unemployed, used drugs, drank heavily and
had had a poor education (Kyriacou et al, 1999).
Berrios and Grady (1991) interviewed 218 women who had received injuries as a
result of domestic violence at a local hospital. Of that sample 28% of women were
admitted due to their injuries and 13% required surgery. 86% of those victims had
been a victim of domestic violence previously.
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In a special report conducted for the US Department of Justice, findings showed that
women aged 20-24 were more likely to be victims of intimate partner violence. The
age group for men being slightly higher, ranging from 25-34 years (Rennison and
Welchans, 2000). Results showed that you were more likely to be a victim if you
lived in an urban environment compared to a rural setting. The study also suggested
that you were more likely to be a victim during the hours of 6pm-6am and within your
own home (Rennison and Welchans, 2000). Moreover higher rates of intimate
partner violence were seen for both men and women if they lived in rental
accommodation and another factor, if they were also divorced or separated
(Rennison and Welchans, 2000).
Research has focused on female victims in relation to domestic violence. In the
international arena, research has shown that females are more prone to be
assaulted, injured or even killed by a current or former partner (García-Moreno et al,
2005). The World Health Organisation conducted a multi-country study, analysing
data from over 24,000 women in ten countries. The study determined that between
13% and 61% of women had suffered one incident of physical violence from a
partner (García-Moreno et al, 2005). Therefore if inferences are to be drawn from
domestic violence data consideration should be given to gender bias as well as the
issue of under-reporting as discussed earlier.
One study that has looked at risk factors for physical injury was conducted using
data from the Canadian Violence against Women Survey (Thompson et al, 2001).
The study’s focus was on women assaulted by spouses and studied the victims’
perspective. The results showed that injuries increased when certain factors were
present such as the presence of alcohol and children witnessing the incident
(Thompson et al, 2001).
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Other studies have compared sexual assaults committed by spouses with those
committed by boyfriends and acquaintances (Stermac et al, 2001). The results
showed that women were prone to more physical violence and injury by spouse and
boyfriend assailants than by acquaintances. However women who had been
assaulted by their spouse would be inclined to call the police and seek medical
assistance sooner than women suffering domestic violence committed by boyfriends
and acquaintances (Stermac et al, 2001).
Looking at the issue of prediction researchers have also focused on trying to forecast
murder within a population of probationers and parolees (Berk et al, 2009). This
recent study looked at future dangerousness, to see whether homicide or attempted
homicide would be committed over a defined time-frame. The study looked at
various risk factors, namely, gender, age, criminal history to see what associations
these factors might have on future behaviour (Berk et al, 2009). Results found that
when trying to forecast a charge of homicide or attempted homicide that the most
important variable was that of age, the age of the person on probation or parole
(Berk et al, 2009).
Other important variables included that of the age of the person, when they first
encountered the court system and the number of prior convictions concerning a
firearm (Berk et al, 2009). Results found that this study proved forecasting serious
crime was more reliable than previously thought. However the study found that it was
still impossible to accurately predict future serious crime with regard to statistical
forecasting (Berk et al, 2009). These findings could therefore assist in focusing
activity on those offenders who were more likely to commit serious crime and assist
with the bigger picture of policing with limited resources, focusing on where the
future demand may be.
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The threat from an offender has also been studied as a risk factor in predicting
serious injury in domestic violence. In a study carried out in Milwaukee over 15,000
police reports were examined and over a sixteen month follow-up period found that
no victim had been injured following the threat (Sherman et al, 1991). Furthermore a
study carried out in Victoria, Australia examined police data to test if there was an
escalation of injury for non-fatal domestic violence cases (Strang and Sherman,
1996). The findings showed that there was no escalation in serious injury no matter
how many calls to the police, no empirical evidence, thus negating the “escalation
hypothesis” (Strang and Sherman, 1996:15).
However the problem is the accuracy of these risk factors. Many studies have used
prediction based on victim data rather than offender data. The victim being the
source providing data on the offender, therefore it is a problem of obtaining accurate
information about these factors in a given case. Thus, there may be other risk
factors, but due to under-reporting these may not be known. It is the nature of these
risk factors and how they relate to the individual and in what context.
Thus the realisation of false negatives and false positives needs to be considered in
predicting domestic violence (Sherman and Strang, 1996). False negatives, i.e.
failing to identify offenders who commit violence, and false positives, i.e. incorrectly
identifying persons as offenders. Moreover how do these risk factors operate in
different domestic violence settings? For example do the findings of the Australian
study (Sherman and Strang, 1996) apply to rural Devon and Cornwall?
Risk factors highlight the opportunity of increasing the risk of harm but make
prediction still difficult to determine (Sherman and Strang, 1996). Prediction is about
comparing risk factors to assist in the prevention of these crimes.
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“The accuracy (validity) and consistency (reliability) of predicting dangerousness and
violence depends on multiple complex factors” (Campbell, 2007:9). Some of these
predictive factors include history of violence, mental illness, substance abuse
including alcohol, gender, age, unemployment, suicidal markers and the use of
weapons (Campbell et al, 2001). The prediction of domestic violence is key in
assisting with operational delivery.
Risk assessment
A big problem facing the police is risk assessment and due to the reduction of
resources, focus is now on prioritisation of police work identifying threats, risk and
harm. This research may be able to provide a more focused approach when dealing
with offenders in the future and help safeguard victims.
Domestic violence is a complex issue and police forces use risk assessments in
dealing with these incidents and crimes. The risk assessments incorporate many
factors, attempting to predict which victims are facing the highest risk of being
harmed (Harne and Radford, 2008). However risk assessments focus mainly on the
victim and not on the offender.
There are general issues in using risk assessments. In the field of mental health, risk
assessments have been debated, research has taken place to try and qualify
whether actuarial assessments are better than clinical judgement (Quinsey et al.,
1998). “In assessing violence risk, an actuarial instrument is one that has been
formally and independently tested and shown actually to predict violent outcomes”
(Roehl et al, 2005:6).
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Actuarial assessments look at general factors predictive in the population, many of
which are historical, static and unchanging, for example, gender (Grounds, 2011).
Whilst clinical assessments provide a detailed history of the individual, looking for
repetition of context with dynamic changeable factors, for example, alcohol
intoxication (Grounds, 2011).The issue of which instrument is best is still challenging
in the development of risk assessments in relation to domestic violence (Roehl et al,
2005).
Another issue is that risk assessments over the years have been designed to focus
on different areas, some on predicting lethality and others on re-offending within the
field of domestic violence (Roehl et al, 2005). Furthermore most research has
focused on assessing the risk of future violence with regard to sexual assault (Roehl
et al, 2005).
Better assessments would enable clinicians to identify if there are certain
characteristics that highlight individuals who may be at risk or possible offenders of
domestic violence. Few studies have progressed in this area, leaving the empirical
evidence lacking and in need for further research (Riggs et al, 2000).
Risk assessments therefore can be summed up as “the process of speculating in an
informed way about the aggressive acts a person might commit and to determine the
steps that should be taken to prevent those acts and minimise their negative
consequences” (Kropp et al, 2002:147).
In addition risk assessments have been created using risk factors that have been
determined in various studies. Thereby practitioners are making decisions on risk
using “hindsight rather than foresight, to draw conclusions about causation”
(Sherman, 1992:232). However those identified risk factors are only determined by
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what we know, where is the comparison to what we do not know? In this chapter the
issue of reporting and under-reporting has already been highlighted. Furthermore
the victim provides the source of the offender data. This information could be tainted
for various reasons for example by the presence of other members of the household
in the room at the time the risk assessment is conducted thus the victim not
providing a true account due to fear. Another example could be the gender of the
interviewer, female victims preferring to speak with other females rather than males
(Walby and Allen, 2004).
In the field of research, researchers have highlighted issues with risk assessments.
Walby, 2005 points out that “The development of indicators and methods of
collecting quantitative data on violence against women, is central to both robust
evaluation of policy developments and to the development of explanations” (Walby,
2005:193). Practitioners need to seek ways to develop a consistent approach and to
begin should set similar definitions. Public sector agencies capture different data for
example defining when a domestic violence incident occurs, applying different age
groups and many use different definitions of the term ‘relationship.’ Public sector
agencies need to share their data, so together it can inform a better understanding of
the issues at hand. Walby suggests “indicators of violence against women need to
capture the extent, as measured by both the rate of prevalence and the number of
incidents, to measure severity by including injury levels, and to distinguish between
acts carried out by intimate partners, other family or household members, and
others” (Walby, 2005:193).
Due to the nature of domestic violence, namely that the violence is focused usually
on a particular individual rather than the wider community makes risk assessing a
priority. The police service is there to provide a duty of care and the safety of
24
individuals is foremost. Therefore consideration in assessing risk must also take into
consideration the victim’s perception of the situation, their prediction (Roehl et al,
2005). Furthermore difficulties arise in this field of research due to the possible
actions of victims. For example victims returning to their partners and possibly
putting their safety at risk. Thus any preventative actions taken as part of the risk
assessment make predicting further offences of violence difficult (Roehl et al, 2005).
Hanson and Morton-Bourgon conducted a meta-analysis on recidivism risk factors
for sexual offenders (2004). However no such research has been conducted in the
field of domestic violence due to insufficient data (Roehl et al, 2005).
Risk assessments for domestic violence have been developed over the years. A key
component is how the police service defines and assesses risk (Perez-Trujillo and
Ross, 2008). Do police officers consistently complete risk assessments? Does the
current risk assessment hinder police officers in their work due to the lack of
flexibility in completing the form? A risk assessment study carried out in Australia
showed that police officers decisions mainly focused on victim accounts, especially
that of victim fear and not on the risk assessment per se (Perez-Trujillo and Ross,
2008). The police officer using the victims account and being aware of the situation
would then determine the course of action to taken.
In 2005-2006 some forces in England and Wales used a risk assessment known as
SPECSS+ (Separation (child contact), pregnancy (new birth), escalation, culture
(community isolation and barriers to reporting), stalking and sexual assault). The
introduction of the risk assessment was to assist police officers in improving the
quality of response to victims of domestic violence. In turn this would help build the
intelligence picture, improve victim safety and investigation standards. In 2009 this
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model was replaced by the DASH (Domestic Abuse, Stalking and Harassment) risk
assessment model. This model consists of a series of twenty seven questions which
cover a number of high risk factors. The questions are put to the victims of domestic
violence and their answers are then assessed to determine if the level of risk, be it,
standard, medium or high. DASH however is based on data not theory.
In a recent study carried out in 2011, the DASH risk assessment model was found to
be a tool that does not accurately assess risk but more of a tool that ascertains the
potential threat of harm (Thornton, 2011). The study has shown that the evidence for
this risk assessment model is actually very thin through no good evaluation evidence
that is actually accurate. Issues arise due to how the risk assessment is completed
by policing professionals and on the overall data capture, only being used when
there is a call for service (Thornton, 2011). The DASH model was based on a
number of risk factors from thirty murder cases but those risk factors have not been
compared with non-fatal domestic violence incidents (Thornton, 2011). Therefore
with no comparison it is difficult to prove the effects of these risk factors and if there
is a greater risk of violence to the victim when they are present (Thornton, 2011).
Personal characteristics of offenders
Research in developmental criminology, for example, the Cambridge study in
Delinquent Development (Farrington, 1995) has demonstrated the importance of
early childhood factors in predicting future offending, including anti-social child
behaviour, poor parenting and economic deprivation. The longitudinal approach is
important and this study will also focus on offending over time.
26
History of violence is a known predictor of further violence (Campbell, 2007). Mental
illness is also associated with violence (Kropp, 2009). Others argue that research is
unclear as to whether there is a true link between mental health and violence
(Campbell, 2007). Additionally assaults by spouses might be more likely to lead to
serious injury (Stermac et al, 2001) and substance abuse has shown that there are
linkages to violence (Dobash and Dobash, 1979).
Self-control theory (Gottfredson and Hirschi, 2003) explains why some people with
low self-control go on to commit crimes. “The variable low self-control is among the
strongest known predictors of crime” (Hay and Forrest, 2008). Thus the aspect of
stability in life is important; this includes having employment and marital status.
Arresting offenders for domestic violence crimes has shown that the effect of arrest
can deter employed men; however arresting unemployed men can lead to more
violence (Berk et al, 1992). Similarly arresting married men for domestic violence
crimes has shown that they are less likely to reoffend than unmarried men (Berk et
al, 1992).
Walby and Allen’s study found that women were more likely to suffer violence than
men and younger people, those under the age of twenty five, were more at risk than
older people, those over the age of fifty five (2004). Another finding showed that
violence increased in lower income households. However these personal
characteristics or variables that link victims and offenders to domestic violence are
indicators of those who are most vulnerable and must not be confused with the
cause of the violence (Walby and Allen, 2004).
In addition studies have looked at risk factors in relation to intimate partner homicide
(Campbell et al, 2003). This study found that if a male partner had access to a gun or
27
had threatened the female victim with a weapon that there was an increase in
femicide (Campbell et al, 2003). Other research has highlighted that a person’s
criminal history may increase the risk of offending. Those who have offended before
go on to commit further crimes than those who have never committed crime
(Farrington, 1992).
In 1995 a study carried out in Memphis, Tennessee looked at evaluating the
characteristics of victims and offenders of domestic violence (Brookoff et al, 1995).
89% of victims had previously reported assaults and 82% of offenders had used
alcohol or drugs with 28% having previous history of violence (Brookoff et al, 1995).
Furthermore a study in 2006 evidenced that alcohol in both offender and victim can
lead to a greater risk of physical violence (Stuart et al, 2006).
Substance abuse, namely alcohol and drugs, are two areas that have been studied
in relation to domestic violence. Alcohol has been highlighted as a risk factor in
intimate partner violence; offenders under the influence have shown an increase of
physical violence (Fals-Stewart et al, 2003; O’Farrell et al, 2004). Furthermore
offenders have shown that acts of violence under the influence of alcohol tend to be
more severe (Graham et al, 2004). Others argue that there is not enough evidence
based practice to list alcohol as an accepted risk factor (Campbell, 2007). Moreover,
studies have shown the combination of alcohol and drugs, have increased intimate
partner violence (Chermack and Blow, 2002). Drugs such as cocaine and
methamphetamine acts as stimulants and lead those using these stimulants to an
increase in aggression (Von Mayrhauser et al, 2002; Cohen, et al, 2003).
Studies have also looked at other risk factors of domestic violence including those
related to experiences in childhood and stress (Shupe et al, 1987). Studies have
28
highlighted those offenders who during their childhood witness domestic violence
amongst their parents are more likely to commit domestic violence in adulthood
(O’Leary et al, 1994). Research has shown that growing up in physically aggressive
households whereby violence is witnessed in childhood can lead to future violence in
later years (Buzawa and Buzawa, 1996). A more recent study found that the
frequency and severity of violence increased as the level of childhood exposure to
violence also increased (Murrell et al, 2007). Furthermore male offenders who
witnessed domestic violence in their childhood committed the most frequent
domestic violence (Murrell et al, 2007).
Various studies have shown that there are many characteristics associated with
violence in a domestic setting be it substance abuse or unemployment (Straus and
Gelles, 1990). However studies have shown inconsistencies in their findings, some
factors were not measured, for example those of low self-esteem and stress, whilst
other studies show there was no significance in the results (Roehl et al, 2005). Whilst
there are some psychological characteristics that might be predictors, these types of
characteristics may not be apparent to police officers attending domestic violence
crimes and therefore are not measured.
Present research aims
As can be seen from the literature review there is a wide spectrum of knowledge on
domestic violence. There have been many studies in recent years in the field of
domestic violence, mainly focusing on victims. However this study focuses on the
male offender, following a sample of offenders who have previously been arrested
29
for domestic violence. It will use only information that the police have captured for it
is the police service that need to make the first call on the possibility of repeats.
Studies have looked at risk factors for injury to women from domestic violence
(Kyriacou et al, 1999). However the 1999 study carried out victim interviews from
victims that used emergency rooms, such data is biased in that it mainly focus on
injured victims because those who are not injured will not use hospitals. Conversely
this study will look at all injuries within the sample, those requiring hospital
treatments or not.
Other studies have looked at characteristics of participants in domestic violence
carrying out assessments at the scene (Brookoff et al, 1995). However victim data
from risk assessment forms may not be completely accurate, it relies on the victim to
provide offender data. Risk assessment forms may not be completed with all victims,
or other members of the household may be present hence victims may not be
comfortable in disclosing all the information or providing the information to an officer
of the opposite gender (Walby and Allen, 2004). This study will work with the data
provided to the police of Devon, Cornwall and the Isles of Scilly.
Furthermore studies have looked at assessing the risk of severe domestic violence
over a four month period (Weisz et al, 2000). This study will follow offenders over a
longer time period, twelve months.
In Victoria, Australia, a study was conducted to examine police data to test if there
was an escalation of injury for non-fatal domestic violence cases (Strang and
Sherman, 1996). The findings showed that there was no escalation in serious injury
no matter how many calls to the police. This study will see if similar findings are
replicated in a large rural two county force in the UK.
30
Thus this study aims to provide an original contribution to current research by
following offenders over twelve months in a UK setting. This study aims to provide a
new way of interpreting the data, strengthening the research in this field.
The focus is different from other studies that look at any type of repeats, as this
study aims to look at serious injury as a predicted outcome rather than repeat
offending. Unlike other studies which look at all repeats this study will only look at
previously arrested offenders who go on to commit crimes of domestic violence.
The Canadian Violence against Women Survey study (Thompson et al, 2001) looked
at prediction from what was known to women, the victims, whereas this study will
focus on similar factors relating to the offender. The study will look at what variables
could lead to further serious injury towards the victim by focusing on the offender.
The factors that will be studied include employment status (Straus and Gelles, 1990;
Kyriacou et al, 1999; Campbell et al, 2001), substance abuse, alcohol and drugs
(Dobash and Dobash 1979; Straus and Gelles, 1990; Campbell et al, 2001), mental
health (Kropp, 2009) and use of a weapon (Campbell et al, 2003).
Farrington’s study in 2005 used a longitudinal approach and this study will follow
similar methodology which looks at offenders, background characteristics over time.
This study will seek to see if there is a relationship between the selected background
offenders’ characteristics and prevalence of further domestic violence offending.
Thus this study, using the data set will aim to answer specific research questions, in
relation to injury levels, offenders’ background characteristics and the frequency of
reoffending. More information about the design and methodology used in this study
is provided in the next chapter.
31
Methods
This research is based upon a descriptive study, a retrospective analysis, using
archival data from Devon and Cornwall’s Police force system. The data has been
captured over a three year period and relates to those domestic violence crimes that
have been reported to the police force of Devon, Cornwall and the Isles of Scilly.
This chapter will explain the data source, the methodology for this study and the type
of analysis conducted during the research.
This study using the data set will aim to see:
Specific research questions
Q1 What predicts injury/ level of injury at the initial offence?
Q2 Is there a relationship between offenders’ background variables and
prevalence of further domestic violence offending?
Q3 What predicts frequency of reoffending?
Q4 What predicts injury in further offences?
Q5 What predicts increases in the severity of injury in further reoffending?
Data source
The data was obtained from Devon and Cornwall’s Crime and Intelligence System
(CIS). This computer system captures recordable crime as per the National Crime
Recording Standard, a standard for recording crime in accordance with the law
(Home Office, 2011). The data being archival relies on a computer system to collate
32
the information with error checking being applied manually by an analyst. There are
disadvantages to archival research as not all variables may have been captured
(Bachman and Schutt, 2007). Therefore before the data set was collated discussion
took place with operational analysts to understand what variables could be identified
from the force’s crime system.
The data was collected by a strategic analyst and looked at all domestic violence
crimes within the agreed time period that fit within the domestic violence Home
Office counting rules (DV1). The Association of Chief Police Officers (ACPO)
definition of domestic violence is “any incident of threatening behaviour, violence or
abuse (psychological, physical, sexual, financial or emotional) between adults, aged
18 and over, who are or have been intimate partners or family members, regardless
of gender and sexuality” (NPIA, 2008:7).
The data was taken from the CIS, using electronic downloads, no data was
downloaded manually. The data was checked for duplications, any that were
identified were removed manually and the missing data was left and not manually
filled. Once the data was downloaded it was read into Excel and some data was
recoded. Finally the data was then read into SPSS, a statistics software package,
values for the offence codes were cleaned. An assumption was made that the data
was correct on input to SPSS. SPSS was then used to add labels to codes and
assign column order (Field, 2009).
The data set covered a three year period from the 1st October 2008 to the 31st
October 2011. The time period chosen was due to the fact that the force computer
systems were being updated and the task of collating the data would have been
33
harder to compile, the request was made November 20111. Therefore by seeking the
data early it ensured that a full data set could be gathered.
Devon and Cornwall Police during this three year period received over 20,500
crimes, averaging over 6500 crimes a year. In addressing how the crimes were
selected to be representative of the population, no selection was made specifically,
except for the time period chosen. As discussed in the literature review, domestic
violence is known to be under-reported and this current research therefore only looks
at those crimes reported to the police within the communities of Devon, Cornwall and
the Isles of Scilly. Thus it does not look at crimes of domestic violence that may have
occurred in the area during this time period but go un-reported.
Furthermore this study looked at domestic violence crimes resulting in serious
physical injury. Incidents where the police attended and documented that only a
verbal argument took place, i.e. no physical injury were not included. The study also
focused on arrested male offenders with brought to justice outcomes, i.e. those that
had been cautioned or charged at initial disposal, rather than those that were just
linked or resulted in no further action. The study also focused on arrested male
offenders who were in an intimate heterosexual relationship. Thus this study did not
look at female offenders, same sex relationships or parent/child/sibling domestic
violence crimes.
The data set covered many variables including crime reference numbers, the types
of crime, specifically crimes of family violence, domestic violence adult family or
crimes of criminal damage and theft in a domestic setting. The data also captured
1 The author of this study had to intermit for a year due to ill health.
34
the dates and times of these crimes, the addresses and outcomes, for example
whether the offender was convicted.
Furthermore the data set also captured the modus operandi (MO) of each crime
which included brief details of the crime, the MO text, code fields and highlighted if
weapons were used. The data set also captured descriptive variables addressing
particular aspects of the offender. These variables included the offenders’ age,
ethnicity, whether they are in employment and other warning markers such as
mental health, alcohol, drugs and use of weapons. The warning markers have been
captured as a result of the police attending the scene and seeing the offender being
in drink, ‘uses alcohol’ or on drugs at the time of arrest or that the victim has alleged
at the time of the assault that the offender was in drink, using drugs or had mental
health problems. These descriptive variables will be looked at in turn, linking back to
those highlighted in the literature review.
These variables were selected for analysis as the literature review has shown that
assaults by spouse might be more likely to lead to serious injury (Stermac et al,
2001). History of violence is also known a predictor of further violence (Campbell,
2007). Mental illness is associated with violence (Kropp, 2009). Substance abuse
has shown that there are linkages to violence (Dobash and Dobash, 1979).
In addition self-control theory (Gottfredson and Hirschi, 2003) explains why some
people with low self-control go on to commit crimes. Thus the aspect of stability in
life is important, stability through employment. Therefore unemployment as a
descriptive variable will be viewed in this study.
There are many crimes associated with domestic violence and this study specifically
looked at physical injury. However those crimes of breaching a restraining or non-
35
molestation order as well as criminal damage in a domestic setting were included to
see whether these crimes lead to a future domestic violence crime resulting in
physical injury to the victim. Domestic violence crime classifications that were
included in the study were as follows:
Common Assault and Battery
Assault Occasioning Actual Bodily Harm (ABH) – S.47
Wound of cause Grievous Bodily Harm (GBH) with intent to do GBH S.18
Inflicting GBH without intent S.20
Malicious wounding S.20
Rape of a female aged 16 or over / Sexual Offences
Threats to kill
Homicide / Attempt Murder
Harassment / Stalking breach of restraining order
Harassment / Stalking without fear of violence
Breach of non-molestation order
Criminal Damage to Dwelling and / or vehicle
Data analysis plan
Preparation of data/selection of cases
This was investigated by focusing on the first 5000 crimes of the data set. The first
5000 crimes covered the time period October 2008-October 2009 and were chosen
to ensure there was enough time to analyse any further crimes of domestic violence,
within the twelve month follow-up period from October 2009 to October 2010. Of
36
those 5000 crimes, further selection of cases took place: only male arrested
offenders and those crimes that relate to an adult intimate heterosexual relationship
were included.
The data analysis provided first an overview of the prevalence of the different crime
types among the cases in the study, number of cases and type of initial disposal,
namely whether offenders were cautioned, charged no evidence of conviction or
charged and convicted. Developing this further the sample was split into those
offenders who are cautioned or charged and compared the level of injury to the
victim. The data was analysed to look at repeat offending in relation to the initial
disposal. Ethnicity, age and occupation of offenders were also investigated.
A retrospective analysis of statistical differences in the background variables
between those who repeat offend and those offenders who do not commit further
offences took place through the use of bivariate analyses, t-tests and chi-square-
tests. Offenders who reoffended in domestic violence were tracked to see if they
reoffended within the first twelve months. This outcome variable would ensure the
study looked at the same length follow-up period for any offender within twelve
months. In predicting frequency of reoffending an analysis of variance was
conducted, the dependent variable being the number of repeats within twelve
months and the independent variable being the type of initial disposal.
Moving on the study looked at what predicts injury and the level of injury in further
reoffending. If there was reoffending in relation to domestic violence, the study would
focus on what were the levels of injury the victim received. To ascertain an agreed
level of injury, the study followed the Crown Prosecution Standards (CPS) charging
37
standards. Thus the standard of injury was met by the CPS charging standard to
either caution or charge the offender with an associated crime.
Cases where the offender had been cautioned or charged with common assault
classified injuries as minor. Cases where the offender had been cautioned or
charged with Assault Occasioning Actual Bodily Harm (ABH) classified injuries as
moderate. Finally, cases where the offender had been cautioned or charged with
Grievous Bodily Harm (GBH) classified injuries as severe. For example, if an
offender commits a further offence within the first twelve months, the study shows if
the offender is charged with a similar offence or an offence where there has been an
escalation of injury. For example, an original charge of ABH with further offending,
leading to a charge of GBH.
Therefore coding of the physical injury data was met through the CPS
cautioning/charging standards. If an offender committed two crimes on the same
day the most severe injury was coded. Logistical regression analyses were carried
out to predict the presence of an ABH-level or GBH-level injury at the first repeat
offence, using the level of injury as an outcome and background offenders’
characteristics as predictors.
Finally the study specifically looked at what predicts increases in injury in further
reoffending. Analysis grouped the repeat offences at twelve months. Analysing those
offenders that committed further domestic violence crimes, resulting in severe
physical injuries towards the victim than that of the initial offence. The study then
compared this group with those offenders, who committed less severe or the same
level of physical injury towards the victim. A retrospective analysis of statistical
38
differences in the background variables between the two groups at the initial offence
was conducted using bivariate analyses, t-tests and chi-square-tests.
First 5000 crimes – creating the final data set
Taking the first 5000 crimes over the time period October 2008–October 2009, only
crimes with male offenders in an adult intimate heterosexual relationship were kept
which reduced the number of crimes from 5000 to 3380. See figure 1 overleaf which
shows a breakdown of the data set.
These 3380 crimes were carried out by 3092 offenders/nominals. Working with the
data set the focus moved to those 3092 offenders. The data was then broken down
into various crime types, those domestic violence crimes with the most number of
offenders. The crime types include common assault, breach of harassment or non-
molestation orders and GBH. For example 748 offenders committed common
assault, n=748 and 1357 offenders committed actual bodily harm, n=1357. There are
many offences with low numbers of offending such as threats to kill, vehicle taking
and theft in a domestic setting and these crimes have been added together under
the heading ‘other’.
The data further defines three categories of initial disposal in relation to the offender
outcome, identifying those offenders who were either cautioned for the specific
offence, charged no evidence of conviction or those charged and convicted. These
offenders having been presented at a police station within Devon and Cornwall
received one of these disposal pathways. For example of the 1357 offenders who
39
committed ABH, 515 offenders were cautioned, 319 offenders were charged, no
evidence of conviction and 523 offenders were charged and convicted.
Due to the lack of resource and data capture across various computer systems the
study cannot determine how many times an offender may have carried out a prison
term and for how long they may have served. Thus further analysis grouped the two
types of charge disposal together i.e. charged and convicted and charged no
evidence of conviction. From a police perspective the disposals would be cautioned
or charged, this information would be relevant to frontline officers dealing with
offenders. The study has distinguished between the two charged groups for the
reoffending analysis because those offenders who are convicted could be in prison
thus not having an opportunity to reoffend.
Figure 1: First 5000 Crimes
Having reviewed the design and approach to this study, the next chapter will now
highlight the key findings.
40
Results
This study focuses on domestic violence crimes within Devon, Cornwall and the Isles
of Scilly, specifically looking at male heterosexual offenders within the data set. This
chapter will provide a description of the sample and then work through each of the
specific research questions in turn.
Description of sample
As highlighted earlier in the thesis, the first 5000 crimes were taken from the overall
data set. The first 5000 crimes covering the time period October 2008-October 2009
have been chosen to ensure there is enough time to analyse any further crimes of
domestic violence within a twelve month follow up period and examine repeat
offending. Of the initial 5000 crimes, only male heterosexual arrested offenders in an
adult intimate relationship were listed. Female offenders and parent/child, sibling or
same sex relationships were removed from the data set. This resulted in a sample of
3380 crimes and 3092 cases/number of offenders. Figure 2 provides an overview of
crime types, the number of cases and the type of initial disposal.
41
Figure 2: Overview of crime types, number of cases and disposal
Among the 3092 cases that met the inclusion criteria for this study were offences of different types. The cases were grouped under the most common offence types
within the data set. There were many offences with low numbers of offending, under
crime types such as threats to kill, vehicle taking and theft in a domestic setting and
these crimes have been added together under the heading ‘other’. The majority of
cases were classified as ABH, n=1357 (43.9%), Common Assault, n=748 (24.2%)
and Criminal Damage in a domestic setting, n=375 (12.1%).
The three disposal types, cautioned, charged no evidence of conviction (i.e. no entry
in the data that the offender was convicted) and charged and convicted, are broken
down under each offence type. Of the ABH cases, 38% of offenders were cautioned,
23.5% were charged no evidence of conviction and 38.5% charged and convicted.
For the cases of common assault, 53.7% of offenders were cautioned, 15.9% were
42
charged no evidence of conviction and 30.4% were charged and convicted. Common
assault offence types use cautioning as the preferred method of disposal, whereas
for ABH both cautioning and charging and convicting are similar in result.
Of the total number of cases 41.8% of offenders were cautioned, 20.5% were
charged no evidence of conviction and 37.7% were charged and convicted. Thus
more offenders were cautioned at initial disposal overall in the sample.
The sample was then split into those offenders who have been cautioned and those
who have been charged, (both charged and no evidence of conviction and charged
and convicted). These two groups were analysed with regard to the level of injury the
victim received at initial disposal. Injuries were classed as minor for common assault,
moderate for an ABH injury and severe for a GBH injury. Figure 3 shows the levels
of injury in relation to these disposal types.
A greater number of offenders are charged when the victim receives a moderate or
severe injury. In the subsample of offenders, who cause a severe injury (n=140),
82.9% were charged (n=116). Whereas injuries received by the victim that are minor
in nature resulted in more offenders being cautioned versus than being charged.
Offenders cautioned, N=402, 55.8% compared to offenders charged N=319, 44.2%.
Interestingly offenders who do not inflict any injury to the victim are charged more,
N=525, 60.6% charged compared to N=341, 39.4% cautioned.
43
Figure 3: Levels of injury in relation to initial disposal
Analysis also took place to show the level of injury in relation to the three disposal
types. Figure 4 overleaf shows that although overall a charge is more likely than a
caution, with exception of the minor injuries group, there is a considerable number of
cases that are charged but do not have evidence of conviction. This is particularly
the case for offences with moderate injury, N=322, 10.4%.
44
Figure 4: Level of injury in relation to three types of disposal
Further analysis was taken in reviewing repeat offending. It can be seen at Figure 5
that the number of offenders who go on to repeat offend in comparison to those
offenders who do not repeat offend, depend on the initial disposal.
45
Figure 5: Breakdown of repeat offending in relation to the three types of
disposal
The difference in reoffending rates is also illustrated at table 1. This shows the
difference in reoffending, 6.6% between cautioned offenders within the first twelve
months and offenders who were charged 13.7%, χ²(1, N=3089) =38.84, p=.000,
OR=2.23, thus offenders who were charged were two times as likely to reoffend.
Table 1: Repeat offending within twelve months of initial disposal, for caution
versus charge
Caution N
Caution %
Charged N
Charged %
Total N
Total %
No 1209 93.4% 1549 86.3% 2758 89.3%
Yes 1294 6.6% 249 13.7% 334 10.7%
Note: here “charged and convicted” and “charged no evidence of conviction” are grouped
together, which explains the different Ns in each group compared to figure 5.
46
The data in table 1 differs to that in figure 5 due to both types of charge disposal
being added together i.e. charged and convicted and charged no evidence of
conviction. From a police perspective the disposals would be cautioned or
charged, this information would be relevant to frontline officers dealing with
offenders. The study has distinguished between the two charged groups for the
reoffending analysis because those offenders who are convicted could be in prison
thus not having an opportunity to reoffend.
Ethnicity
The following figure shows the distribution of ethnicity for all offenders within the
study. As figure 6 shows 95.8% of the offenders in the sample were White European.
This is a similar to the overall distribution of ethnicity in Devon, Cornwall and the
Isles of Scilly. It is currently estimated that non-white ethnic groups make up 4.5% of
the population (Peninsular Strategic Assessment, 2012-2013).
47
Figure 6: Distribution of ethnicity for all offenders
Age
The age distribution of the sample is depicted in figure 7. It ranged from the age of
16 to 87, with a mean of 31 years, with the majority of offenders in their late twenties
to early forties. The age distribution varies by disposal type, as can be seen in figure
8. With an average of 34.99 years (SD=11.50), the cautioned group was older than
the two charged groups. Charged and convicted (M=32.66, SD=10.53), charged no
evidence of conviction (M=31.35, SD=10.88). In order to investigate if these age
differences were statistically significant an analysis of variance (ANOVA) was
conducted. This revealed an overall significance, F(2,3091)=11.30, p=.000. Post-hoc
95.8%
1.7% 0.4% 1.0% 0.5% 0.2% 0.4% 0.1%
48
tests showed a significant difference between the cautioned group and the charged
and convicted group, p=.000, but no difference between any of the other groups,
p>.05.
Figure 7: Age distribution of the total sample
49
Figure 8: Age distribution by disposal type
Occupation
Occupation classifications were analysed at two levels, firstly looking at the total
sample and again for those who reoffend. Occupation classifications have followed
the Office of National Statistics, Standard Occupational Classifications of 2010 and
are shown at table 2. There are four skill levels; occupations classified under level
four are the most skilled.
Mean Age
Cautioned: 34.99, SD=11.50
Charged, no evidence of conviction: 31.35, SD=10.88
Charged and convicted: 32.66, SD=10.53
50
Table 2: Standard occupational classifications
Level 4 Corporate managers and directors Science, research, engineering and technology professionals Health professionals Teaching and educational professionals Business, media and public service professionals
Level 3 Other managers and proprietors Science, engineering and technology associate professionals Health and social care associate professionals Protective service occupations Culture, media and sports occupations Business and public service associate professionals Skilled agricultural and related trades Skilled metal, electrical and electronic trades Skilled construction and building trades Textiles, printing and other skilled trades
Level 2 Administrative occupations Secretarial and related occupations Caring personal service occupations Leisure, travel and related personal service occupations Sales occupations Customer service occupations Process, plant and machine operatives
Transport and mobile machine drivers and operatives Level 1 Elementary trades and related occupations
Elementary administration and service occupations
Figure 9 below shows the breakdown of occupation classifications within the total
sample and for those offenders who reoffend within twelve months. Both sets of bars
follow similar patterns. Purely looking at the skill level it shows most employed
offenders are skilled at level two and the fewest at level four. However the largest
category is the unemployment category for both sets of bars.
In Devon, Cornwall and the Isles of Scilly the unemployment rate is estimated at
5.3% of the working age population (Peninsula Strategic Assessment, 2012-2013).
In comparison the total sample shows 44.5% of offenders unemployed and 57.3% go
on to reoffend in twelve months from the first offence within the sample. The
51
importance of unemployment as a predictor to further offending will be explored later
in this chapter.
Figure 9: Occupation distribution comparing the total sample and repeat
offending
Further analysis examined the background characteristics/variables of the offenders
within the sample, namely, alcohol, drugs, mental health and the use of weapons.
The analysis looked at all offenders within the sample, see figure 10 and then looked
at these variables within the initial disposal groups of cautioned, charged no
evidence of conviction and charged and convicted, see figure 11.
-10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Perc
en
tag
e
Employment Classifications
Total Sample
Repeat Offending
52
Figure 10: Background variables in the total sample
The findings show that in the total sample 39.5% of offenders use alcohol, 20.8%
use drugs, 21.5% have mental health problems and 8.2% use a weapon. The use of
alcohol was the highest percentage in the make-up of background variables.
In figure 11 the same background variables were used but this time analysis looked
at these in relation to the initial disposal. Findings show that more offenders are
charged and convicted in conjunction with all background variables, followed by
cautioning and then charged no evidence of conviction.
0
500
1000
1500
2000
2500
3000
Alcohol Drugs Mental Health Weapons
Nu
mb
er
of
Off
en
ders
Background Variables
Yes
No
60.5%
91.8%
8.2%
78.5%
21.5%
79.2%
20.8%
39.5%
53
Figure 11: Background variables split by initial disposal
Having described the sample, the results chapter will now move to address each
specific research question in turn.
Q1 What predicts injury/level of injury at the initial offence?
The beginning of the section presents analyses on what predicts, whether the victim
was injured at the initial offence. Later in this section analyses examine what factors
predict the level of this injury.
In order to analyse the question of predicting injury and level of injury in the initial
offence, injury was classified into three levels. The injury level was determined by
the CPS charging standards. Injuries such as those received under a common
assault charge were classified as minor. Injuries such as those received under a
charge of actual bodily harm were classified as moderate and injuries received under
a charge of grievous bodily harm were classified as severe.
0
100
200
300
400
500
600
Alcohol Drugs Mental Health Weapons
Nu
mb
er
of
Off
en
ders
Background Variables
Cautioned
Charged, no evidence ofconviction
Charged and convicted
54
Table 3 shows the odds ratio for prevalence of injury in relation to the initial disposal
received and compares the background variables. All these odds ratios and
significances are based on chi-square tests. A supplemental table with the test
statistics for each of these offenders’ characteristics is included in Appendix A.
Table 3: Odds ratio for prevalence of injury
Cautioned Charged, no evidence of conviction
Charged and convicted
Total Sample
Alcohol
0.58 0.89 1.10 0.87
Drugs
0.69 0.63 0.76 0.69
Unemployed
0.76* 0.91 1.12 0.78*
Mental Health
1.44 0.85 0.90 0.85
Weapons
16.27** 4.58* 5.89** 6.77**
Note. * : χ² tests significant at .05 level ** : χ² tests significant at .001 level
A supplemental table with each of the test statistics for each of the offenders’ characteristics is
included in Appendix A.
As can be seen in table 3 the presence of weapons at the offence was only
significant background variable for injury in all three disposal types. Offenders who
were charged and convicted were nearly six times more likely to cause injury when
using a weapon at the first offence compared to those who do not. Those who were
charged but there was no evidence of conviction in the file were about five times
more likely to have caused injury when a weapon was involved than when there was
not. However offenders who were cautioned2 and used weapons at the first offence
were sixteen times more likely to cause injury than those who did not use weapons.
2 CPS determine charging standards
55
Interestingly unemployment was also found to be a significant background variable
for those offenders who were cautioned, but it decreased the risk of injury,
particularly for the cautioned group (no significance was found with unemployed
offenders who were either charged no evidence of conviction or charged and
convicted).
By contrast the chi-square tests showed no significant relationship between alcohol
and the presence of injury, either for the total sample or for each of the three types of
disposal. Similarly the use of drugs or mental health problems were not significantly
related to injury.
The following figures show the background variables and the level of injury received
within the sample. Of all the cases with injuries, 0.6% resulted in severe injuries to
the victim when the offender was under the influence of alcohol, compared to 4.0%
of victims that received severe injuries when the offender was not under the
influence of alcohol, see figure 12a.
Of all the cases with injuries, 0.4% resulted in severe injuries to the victim when the
offender was under the influence of drugs, see figure 12b. However 4.2% of victims
received severe injuries when the offender was not under the influence of drugs. In
both figures it shows that levels of injury were less when under the influence of either
alcohol or drugs.
Similar findings were seen with unemployment and mental health. Of all the cases
with injuries overall fewer injuries were received by the victim when offenders were
unemployed compared to those offenders employed or retired, see figure 12c. In
figure 12d it shows that offenders without mental health problems injure their victims
more than those with mental health problems.
56
Figure 12a: Influence of alcohol and injury levels
Figure 12b: Influence of drugs and injury levels
22.7%
1.1%
25.6%
22.1%
41.2%
4.0%
0.6%
2.9% 2.4%
26.8%
42.7%
4.2% 1.2%
0.5% 1.5%
0.4%
F(1,3136)=.099,p=.753
F(1,3136)=.015,p=.903
57
Figure 12c: Influence of unemployment and injury levels
Figure 12d: Mental Health and injury levels
14.5% 13.9%
25.2%
2.4%
13.5%
9.4%
19.0%
2.1%
33.3%
20.2%
18.5%
3.1%
7.7%
4.8%
10.9%
1.4%
F(1,3136)=2.98,p=.085
F(1,3136)=.146,p=.702
58
Of all the cases with injuries, figure 12e shows that more injuries were caused to
victims without the use of weapons. When weapons were used they caused 1.4%
severe injuries.
Figure 12e: Use of weapon and injury levels
In conclusion a series of analyses of variance were conducted to investigate this
relationship between offenders’ background variables (one variable as independent
variable per ANOVA) and level of injury (as dependent variable). The results of these
ANOVAs with the whole sample are reported in figures 12 a-e. No significant
relationship was found in relation to alcohol, drugs and mental health.
Subsequently analysis took place for each disposal type. Unemployment was found
to be a significant background variable for offenders who were cautioned but not in
the other two disposal groups, charged and convicted, and charged no evidence of
27.2%
21.7%
39.2%
3.1%
0.8% 1.6%
5.0%
1.4%
F(1,3136)=112.68,p=.000
59
conviction. However the use of a weapon was significantly related to increased
levels of injury in all three disposal types.
Q2 Is there a relationship between offenders’ background variables and
prevalence of further offending?
In order to set the scene for investigating the impact of particular offenders’
background variables an analysis examined how many offenders reoffended. To
investigate this, a survival graph was created, see figure 13. This graph shows that,
20% of offenders who reoffend did so by 15 days after the initial offence, 50% of
offenders by 75 days after the initial offence and 80% of offenders by 200 days after
the initial offence.
Figure 13: Survival graph of reoffending
60
In order to analyse the question of predicting further offending, a series of offender
characteristics were selected, namely, alcohol, drugs, unemployment, mental health
and use of weapons. Analyses of reoffending, was split firstly by disposal and then
by whether a specific characteristic was present or not. Reoffending was
operationalised as any further offence within the first twelve months, and coded as
‘Yes’ or ‘No’ and was used as the outcome variable.
The prevalence of a further offence given the presence of these variables is
presented in table 4. This table shows that the rate of reoffending between those that
have a certain characteristic, namely alcohol, drugs, unemployment, mental health
and use of weapons and those who do not are very different. For instance within the
group that was cautioned, 55 offenders used alcohol, of these 67.3% reoffended.
1239 offenders did not use alcohol, of these 3.8% reoffended.
However other characteristics do not seem to increase the risk of reoffending such
as mental health problems or weapon use. Table 4 gives us overall numbers and an
indication of which characteristics may be related to reoffending for example alcohol,
drugs, unemployment but it does not say anything about the size of these effects.
This is depicted in table 5.
61
Table 4: Prevalence of a further offence within twelve months given particular
offender characteristics
Reading example: Within the group that was cautioned, 55 offenders used alcohol. Of these 67.3%
reoffended. 1239 offenders did not use alcohol. Of these 3.8% reoffended.
Table 5: Odds ratio of reoffending
Cautioned Charged, no evidence of conviction
Charged and convicted
Total Sample
Alcohol
52.13** 29.95** 37.42** 42.39**
Drugs
65.73** 38.86** 80.63** 67.64**
Unemployed
1.71* 1.57 1.47* 1.79**
Mental Health
1.13 1.12 1.17 1.20
Weapons
0.72 1.03 1.39 1.26
Note. * : χ² tests significant at .05 level ** : if smaller than p=.001
A supplemental table with each of the test statistics for each of the offenders’ characteristics is
included in Appendix B.
62
All these odds ratios and significances are based on chi-square tests. For
readability’s sake only the stars denoting significance are presented in table 5. The
corresponding complete test statistics for each of these chi-square tests is included
in Appendix B.
Table 5 illustrates that for the alcohol example chi-square tests showed a significant
relationship between alcohol and prevalence of reoffending in all three groups,
cautioned, charged no evidence of conviction, charged and convicted.
Other significant relationships were found for drugs and reoffending, again chi-
square tests showed a significant relationship between drugs and prevalence of
reoffending in all three groups, cautioned, charged no evidence of conviction,
charged and convicted. For unemployment a significant relationship to reoffending
was found in only two groups, those offenders who were cautioned and those who
were charged and convicted.
However there were no significant relationships between mental health and
reoffending or the use of a weapon and reoffending, meaning that offenders with
mental health problems or who use weapons at the first offence were no more likely
to reoffend within twelve months than those who did not have mental health
problems or did not use weapons. The effect sizes were also small.
In terms of effect sizes for alcohol and drug use, although there was a significant
relationship to reoffending for all disposal groups, effect sizes differed. Cautioned
offenders were fifty two times more likely to reoffend when using alcohol than when
not, while those charged and convicted were thirty seven times more likely to
reoffend when using alcohol as opposed to not. Charged and convicted offenders
who used drugs were eighty times more likely to reoffend compared to those who did
63
not, and cautioned offenders were sixty five times more likely to reoffend when they
used drugs as compared to those who did not. In terms of effect sizes for
unemployment, offenders were 1.71 times more likely to reoffend when cautioned
and 1.47 times more likely to reoffend when charged and convicted.
In conclusion the use of alcohol and of drugs at the initial offence is a considerable
predictor of repeat offending regardless of disposal. Mental Health and the use of
weapons were not significant predictors and unemployment showed mixed results,
depending on which initial disposal the offender was given. The relationship
between unemployment and reoffending was significant for offenders who were
cautioned and who were charged and convicted but not for offenders who were
charged no evidence of conviction.
Q3 What predicts frequency of reoffending?
Further analysis took place to look at those offenders who went on to reoffend within
the sample to examine if offenders background characteristics also predicted
frequency of offending with the next twelve months. Frequency of reoffending was
operationalised as number of further offences. These ranged from one further
offence to six within twelve months. To begin an analysis of variance was conducted
with the number of repeats within twelve months as the dependent variable and
initial disposal as the independent variable. The results of the ANOVA indicated that
initial disposal was not significant. F, (2,328)=2.66, p=.071. This means that
offenders in the cautioned; charged no evidence of conviction and charged and
convicted groups who had at least one further offence did not differ in the number of
further offences.
64
Independent t-tests were also conducted to see whether there was any relationship
between offenders’ background variables and frequency of reoffending. Table 6
shows the means and standard deviations for the frequency of reoffending given
certain background characteristics.
Table 6: Mean number of further offences by prevalence/absence of particular
offender characteristics
Number of offenders Mean number of
further offences
Standard
Deviation
Alcohol Not present N=171
Present N=162
1.26
1.40
.597
.837
Drugs Not present N=236
Present N= 97
1.36
1.27
.768
.608
Unemployment Employed N=144
Unemployed N=189
1.24
1.39
.689
.748
Mental Health Not present N=240
Present N=93
1.29
1.41
.691
.811
Weapons Not present N=298
Present N=35
1.33
1.34
.733
.684
A series of independent t-tests were conducted to examine if these differences in
average reoffending frequency were significant. These showed that the presence of
alcohol at the first offence was not significantly related to frequency of reoffending,
t(289.86)=-1.79,p=0.73.
65
Similarly, not significant results were found for the presence of drugs at the first
offence t(223.73)=1.60,p=.111, the presence of mental health at the first offence,
t(146.55)=-1.19,p=.238 and the use of weapons at the first offence,
t(331)=-.133,p=.894.
However unemployment at the first offence was found to be significantly related to
the frequency of offending, t(319.2)=-2.03, p=.043. Unemployed offenders had a
higher number of further offences.
Overall these analyses have shown that unemployment at the first offence is the only
offender background variable predicting frequency of offending.
Q4 What predicts injury in further offences?
In order to analyse what predicts a victims’ injury in a further offence the level of
injury at the first and second offence was reviewed, see figure 14 and table 7. As can
be seen from the following figure, figure 14, the severity injury at the second offence
decreases in both the cautioned and charged no evidence of conviction disposal
types.
However the charged and convicted disposal type shows an increase. Though the
percentage changes from 4.5% at the first offence to 7.8% at the second offence
consideration should be given to the number of cases. Fifty three offenders were
charged and convicted out of a hundred and forty cases at the first offence and
thirteen were charged out of twenty one cases in the second offence. Thus there
were less second offence cases but more offenders were charged the second time.
66
Figure 14: Levels of injury at first and second offence
Table 7 shows that seventy six cases resulted in no injury, 64.4% in both the first
and second offence. Severe injuries in the data set are rare; only one offender
commits GBH both at the first and second offence, 8.3%. The table highlights those
cases where there was a repeat offence. So if injuries at t1 were caused to the victim
but there was no repeat offence they would not be shown below.
Table 7: Injury levels at first and second offence
t2
t1
No Minor Moderate Severe
No N=76 64.4%
N=22 30.1%
N=34 24.3%
N=4 33.3%
Minor N=7 5.9%
N=16 21.9%
N=21 15.0%
N=0 0.0%
Moderate N=29 24.6%
N=32 43.8%
N=74 52.9%
N=7 58.3%
Severe N=6 5.1%
N=3 4.7%
N=11 7.9%
N=1 8.3%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
No
Inju
ry
Min
or
Mo
der
ate
Seve
re
No
Inju
ry
Min
or
Mo
der
ate
Seve
re
No
Inju
ry
Min
or
Mo
der
ate
Seve
re
Charged no evidence ofconviction
Charged andConvicted
Injury First Offence
Injury Second Offence
Cautioned
67
To continue to analyse this question a logistic regression analysis was conducted to
predict the presence of a GBH-level injury at the first repeat offence, i.e. the second
offence (t2). Predictor variables were a GBH-level injury at the first offence and
offender background characteristics, namely alcohol, drugs, unemployment, mental
health and the use of weapons. The offender background characteristic of age was
also included in this analysis. This model was not significantly better than the
constant-only model χ² (7, N=3138)= 7.24, p=.405 (see also the logistic regression
coefficients in Table 8), thus it was not possible to predict a GBH-level injury at the
second offence significantly with these included characteristics. Interestingly, a
previous GBH-level injury did not significantly predict a GBH-level injury at the repeat
offence.
Table 8: Logistic regression coefficients predicting GBH at further offence
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
injury_severe .277 1.121 .061 1 .805 1.319
r_WeaponsOffenceR1 -.047 .794 .004 1 .952 .954
r_AlcoholOffenceR1 .846 .522 2.622 1 .105 2.330
r_DrugsOffenceR1 .599 .501 1.431 1 .232 1.821
r_unemployed -.424 .476 .795 1 .373 .654
r_mental_health .374 .504 .550 1 .458 1.453
nom_age1 -.004 .022 .026 1 .872 .996
Constant -3.250 .846 14.751 1 .000 .039
a. Variable(s) entered on step 1: Severe Injury, Weapons, Alcohol, Drugs, Unemployed, Mental Health, Age.
R²=.02(Cox and Snell), .06(Nagelkerke). Model χ² (7)=7.24, p<.01.* p<.01.
To continue to analyse this question a further logistic regression analysis was
conducted to predict the presence of an ABH-level injury or a GBH-level injury at the
first repeat offence. Thus instead of only including the most severe injury as the
Age
Mental Health
Severe Injury
Weapons
Alcohol
Drugs
Unemployed
68
dependent variable, this time moderate or severe injury was included as the
dependent variable. Predictor variables were an ABH-level injury and a GBH-level
injury at the first offence and offender background characteristics, namely alcohol,
drugs, unemployment, mental health and the use of weapons. The offender
background characteristic of age was also included in this analysis. This time, the
logistic regression model was significantly better than the constant only model. The
logistic regression coefficients are presented in table 9.
Table 9: Logistic regression coefficients predicting ABH or GBH at further
offence
Variables in the Equation
B S.E. Wald Df Sig. Exp(B)
Step 1a
r_WeaponsOffenceR1 .070 .400 .031 1 .861 1.073
r_AlcoholOffenceR1 .227 .242 .883 1 .347 1.255
r_DrugsOffenceR1 .218 .260 .701 1 .403 1.244
r_unemployed .412 .235 3.088 1 .079 1.510
r_mental_health -.083 .268 .097 1 .756 .920
nom_age1 -.025 .011 4.679 1 .031 .976
injury_mod_sev .987 .237 17.275 1 .000 2.683
Constant -.141 .414 .116 1 .733 .868
a. Variable(s) entered on step 1: Weapons, Alcohol, Drugs, Unemployed, Mental Health, Age, Moderate/Severe
Injury
R²=.09(Cox and Snell), .11(Nagelkerke). Model χ² (7)=30.0, p<.01.*p<.01.
Thus, as can be seen in the above table, moderate, ABH–level injury or severe,
GBH-level injury at the repeat offence is predicted by previous moderate or severe
injury, as well as offenders age and, marginally significantly, by unemployment.
A t-test was conducted to investigate the relationship between age and injury at the
further offence. Where a victim suffered a moderate or severe injury at the repeat
Weapons
Alcohol
Drugs
Unemployed
Mental Health
Age
Moderate/Severe Injury
69
offence, the offender was younger (mean age: 31.58, SD =9.32) than where the
victim was not injured or only minor injuries were inflicted at the repeat offence
(mean age: 34.13, SD =11.85), t (331.73)=2.22, p=.027.
In conclusion it was not possible to predict severe injury, i.e. GBH, at the second
offence significantly with the chosen offender background characteristics. A previous
GBH-level injury did not significantly predict a GBH-level injury at the repeat offence.
This may have been due to the fact that a GBH-level injury was rare in the data set
only one case (n=1) for the second offence.
However it was possible to predict moderate, ABH–level injury, or severe GBH-level
injury at the repeat offence. This was predicted by previous moderate or severe
injury, as well as offenders age and, marginally significantly, by unemployment.
These findings will be discussed in the next chapter.
Q5 What predicts increases in injury in further reoffending?
In order to analyse this question the repeat offences were reorganised into two
groups. This way I compared those repeat offences that were more severe in injury
than the initial offence with those repeat offences with less or same severity of injury.
Analysis of the statistical differences in the offender background variables between
the two groups at the initial offence were conducted through the use of t-tests and
chi-square tests.
The following figure, figure 15, shows levels of severity in relation to injury and initial
disposal. Severe injuries being less within each of the initial disposal types.
70
Figure 15: Levels of severity and disposal types
Table 10 shows the odds ratios of severity in relation to the initial disposal received
and compares the offenders’ background variables.
71
Table 10: Odds ratio of a more severe injury for the further offence
Cautioned Charged, no evidence of conviction
Charged and convicted
Total Sample
Alcohol
0.40 1.29 1.76 1.13
Drugs
1.24 1.14 1.12 1.17
Unemployed
1.01 1.28 1.55 1.36
Mental Health
0.29 1.29 3.20 0.80
Weapons
2.46 0.70 1.25 1.14
Note. * : χ² tests significant at .05 level ** : if smaller than p=.001
A supplemental table with each of the corresponding test statistics for each of the offenders’
characteristics is included in Appendix C.
As can be seen in table 10 none of the offender background variables are significant
predictors of increases in injury regardless of disposal. Chi-square tests were
conducted on all background variables and none of them yielded a significant result.
A supplemental table with each of the test statistics for each of the offenders’
background characteristics is included in Appendix C.
Alcohol, drugs, unemployment, mental health and use of weapons are not significant
in relation to identifying a more severe injury in a further offence when comparing the
three types of disposal. The odds ratios are also small in number. In conclusion none
of the offenders’ background characteristics are significant predictors of injury in
further offences regardless of disposal.
72
Discussion
The purpose of this research was to investigate repeat offending after cautioning or
charging for domestic violence. This research was based upon a descriptive study, a
retrospective analysis, using archival data from Devon and Cornwall’s Police force
system. The study focussed on male heterosexual offenders in an adult intimate
relationship over a three year period. The study began by focusing on the domestic
violence crimes in the first year of the data set and then followed-up over a twelve
month period. The study focussed on predicting further offences leading to serious
injury, following a sample of offenders who have previously been arrested for
domestic violence, using the Crown Prosecution Service charging standards to
define injuries and the level of injury. The data set included offenders’ background
characteristics including age, ethnicity, unemployment, mental health and the use of
alcohol, drugs and weapons.
This chapter will review the findings; it will begin by looking at the overall sample.
Then it will move to address the specific research questions in turn.
The sample
Of the initial 5000 crimes only male heterosexual arrested offenders in an adult
intimate relationship were listed. This resulted in a sample of 3380 crimes and 3092
offenders. Of those 3092 offenders, the majority of offenders n=1357 were arrested
for an offence of actual bodily harm (43.9%). Arrests for common assault making up
24.2 % (n=748) and arrests for grievous bodily harm making up 3.5% (n=109) within
the sample.
73
Of the three disposal types, cautioned, charged no evidence of conviction (i.e. no
entry in the data that the offender was convicted) and charged and convicted,
cautioning was the preferred method of disposal for common assault offences.
Whereas for ABH offences, both cautioning and charging and convicting were the
preferred methods of disposal. For GBH offences charged no evidence of conviction
was the preferred method of disposal. Results showed that a greater number of
offenders were charged when the victim received moderate or severe injury.
Interestingly offenders who do not inflict any injury to the victim were charged more
often.
However further analysis showed that only 6.6% of offenders who were cautioned
went on to reoffend within the first twelve months whereas 13.7% of offenders who
were charged, no evidence of conviction were two times more likely to reoffend. This
finding could be important in that within the sample a greater number of offenders
were charged for no injury offences. Charged offenders being twice more likely to
reoffend. Unfortunately the data set cannot ascertain whether those offenders in the
charged no evidence of conviction group served time. This was mainly due to the
lack of time to research each offender within a number of databases. However had
this been available it would perhaps strengthen this finding. Further research into
the effect of method of disposal would be useful for further policing and criminal
justice issues. Previous studies have already looked at the effect of the arrest
(Sherman, 1992).
The sample for this study showed that 95.8% of offenders were White European.
This reflected the overall distribution of ethnicity within Devon, Cornwall and the Isles
of Scilly. Non-white ethnic groups make up 4.5% of the population (Peninsular
Strategic Assessment, 2012-2013). Therefore as this sample is made up
74
predominantly of White European offenders it would be interesting to see if similar
findings were found for a different demographic group of offenders. The
generalisability of this study would need to be tested.
The age of offenders ranged from 16 to 87 years with a mean of 31 years.
Interestingly those offenders who were cautioned were significantly older than the
other two disposal groups, offenders being 34 years old. Research has shown that
age is an important variable, (Berk et al, 2009). That is the age of the person on
probation or parole, when the offender first encountered the court system and the
number of prior convictions (Berk et al, 2009). Had there been time it would have
been interesting to see the offenders’ criminal background within the sample. History
of violence is a known predictor of further violence (Campbell, 2007).
With regard to occupation, the sample highlighted that 44.5% of offenders were
unemployed, with 57.3% going on to reoffend within twelve months from the first
offence. Unemployment has been highlighted in previous research as being a factor
related to domestic violence (Straus and Gelles, 1990; Kyriacou et al, 1999;
Campbell et al 200; Berk et al, 1992).
Thus this study provides a contribution to research building the knowledge. Quite a
bit is known about domestic violence, studies have been conducted around the
world, mostly evidence from the United States (Brookoff et al, 1995; Sherman, 1992)
and Australia (Strang and Sherman, 1996). However this study has been conducted
in the UK. This study uses police data whilst many studies have used other sources,
for example surveys (Thompson et al, 2001; Graham et al, 2004).
75
Q1 What predicts injury/level of injury at the initial offence?
Analysis took place having classified injury into three levels determined by Crown
Prosecution Standards (CPS) charging standards, common assault for minor
injuries, Actual Bodily Harm (ABH) for moderate injuries and Grievous Bodily Harm
(GBH) for severe injuries. The odds ratio of injury was looked at in relation to the
initial disposal and comparing the background characteristics of offenders, namely,
alcohol, drugs, unemployment, mental health and use of weapons.
Alcohol and drugs showed no significant relationship in relation to injury when
comparing the three types of disposal. Of those offenders who were under the
influence of alcohol only 0.6% resulted in severe injuries to the victim, a smaller
percentage for those offenders under the influence of drugs, 0.4%. Levels of injury
were less when offenders were under the influence of alcohol and drugs. Previous
research has shown that injuries to victims increase in severity when offenders are
under the influence of alcohol and/or drugs (Fals-Stewart et al 2003; O’Farrell et al,
2004; Graham et al, 2004).
However findings within this study differed perhaps due to the different information
sources. Research by Fals-Stewart et al (2003) looked at only 149 male offenders
who were either married or cohabiting that had entered a drug abuse treatment
programme over a fifteen month period. Research by O’Farrell et al (2004) reviewed
303 male alcoholic patients who attended behavioural couple’s therapy. While
research by Graham et al (2004) carried out a survey, asking respondents questions
in relation to their drinking habits and physical aggression. Thus this study only used
police data, what was known to the police. There was no sight of any medical
information. The sample size in this study was also larger, 3092 offenders.
76
Furthermore previous studies have determined that women would be at a greater
risk of injury if their male partners were under the influence of alcohol and drugs
(Kyriacou et al, 1999). Drugs have being linked as a factor in relation to domestic
violence (Dobash and Dobash, 1979; Chermack and Blow, 2002). Women assaulted
by spouses have shown that injuries increase when certain factors such as presence
of alcohol are present (Thompson et al, 2001). Others have argued that there is not
enough evidence-based practice to list alcohol as an accepted risk factor. Given that
no significant link between alcohol and/or drugs and injury was found for either the
first or second offence, this study agrees with this latter course of thinking.
A similar finding with alcohol and drugs was seen with offenders who had been
marked in the police records as suffering mental health problems in that there was
no significant relationship in relation to injury when comparing the three disposal
types. Of all the cases with injuries within the sample, offenders who have mental
health problems, only 1.4% resulted in severe injuries to the victim. Offenders who
did not have mental health problems injure their victim more, 3.1%. However some
offenders may have been suffering from mental health problems but perhaps not
identified by the police data. Again some research has shown that mental illness is
associated with violence (Kropp, 2009). However others argue that the research is
unclear as to whether there is a link between mental health and violence (Campbell,
2007). This study supports the latter view. Here no direct link was observed.
Interestingly unemployment was found to be a significant background variable for
offenders who were cautioned, decreasing the risk of injury. There was no
significance for those unemployed offenders who were either charged and no
evidence of conviction of charged and convicted. Research previously has found that
women would be at a greater risk of injury if male partners were unemployed
77
(Kyriacou et al, 1999). Findings in this study showed that unemployment was
marginally significant in predicting an ABH-level injury or GBH-level injury at the
repeat offence.
However the use of a weapon was significantly related to more severe levels of
injury in all three disposal types. Offenders who were charged and convicted were
five times more likely to cause injury when using a weapon at the first offence
compared to those who do not. More importantly those offenders who were
cautioned3 were sixteen times more likely to cause injury when using a weapon at
the first offence compared to those who do not. This finding concurs with previous
research that the use of weapons not only has links to domestic violence but leads to
serious injury to the victim (Campbell et al 2001; Campbell et al 2003).
Q2 Is there is a relationship between offenders’ background variables and
prevalence of further offending?
Findings showed that there was a significant relationship between alcohol and the
prevalence of reoffending in all three disposal groups, cautioned, charged no
evidence of conviction, charged and convicted. Similar findings were seen with
drugs, a significant relationship between drugs and the prevalence of reoffending in
all three disposal groups.
For unemployment a significant relationship was found only in two groups.
Relationships existed between unemployment and reoffending for those offenders
who were either cautioned or for those who were charged and convicted. No
3 CPS determine charging standards
78
significant relationship was seen for the group of offenders who were charged no
evidence of conviction.
For both mental health and use of weapons no significant relationships were found
across all three disposal groups. Thus offenders with mental health problems at the
first offence were not likely to reoffend within twelve months. Similarly offenders who
used weapons at the first offence were not likely to reoffend within twelve months.
Therefore the use of alcohol and drugs is a considerable predictor of repeat
offending regardless of disposal. Whereas mental health and use of weapons are not
important predictors. Unemployment showing mixed results depending on the initial
disposal. These findings align with previous research where substance abuse and
unemployment have shown they are characteristics associated with domestic
violence (Straus and Gelles, 1990).
These findings help strengthen the use of alcohol and drug referral programmes for
offenders. This study has shown that offenders who use alcohol and/or drugs are
more likely to reoffend. By providing early support to substance abuse offenders, it
may reduce reoffending in the future.
Furthermore unemployment was found to be significant in further offending for those
who were cautioned or charged and convicted. Better signposting for these offenders
may help to reduce reoffending, use of the third sector and volunteering, providing
training and skills opportunities.
79
Q3 What predicts frequency of reoffending?
Having conducted an analysis of variance the findings showed that the initial
disposal was not significant. Thus if offenders were cautioned, charged no evidence
of conviction, charged and convicted who had at least one further offence they did
not differ in any subsequent number of further offences.
The findings also showed that unemployment is the only offender background
characteristic that can predict frequency of offending at the first offence. Thus
unemployed offenders had a higher number of further offences. Alcohol, drugs,
mental health and use of weapon were not significant in predicting frequency of
offending.
As we have seen earlier unemployment was already highlighted as one of the
offenders’ background characteristics linked to prevalence of further domestic
violence offending. Here we see that it too is significant in the frequency of
reoffending.
Q4 What predicts injury in further offences?
The findings showed that the severity of injury at the second offence decreases in
both the cautioned and charged no evidence of conviction disposal types. However
the charged and convicted disposal type showed a slight increase. Though the
percentage changed from 4.5% at the first offence to 7.8% at the second offence
consideration should be given to the number of cases. Fifty three offenders were
charged and convicted out of a hundred and forty cases at the first offence and
80
thirteen were charged out of twenty one cases in the second offence. Thus there
were less second offence cases but more offenders were charged the second time.
Within the sample seventy six cases resulted in no injury, 64.4% in both the first and
second offence. Only one offender commits a GBH-level injury at the first and
second offence, 8.3%. Reasons for the low numbers could be due to lack of data,
unable to determine the percentage of offenders who are convicted and length of
time served affecting the results.
The offenders’ background variables were used as predictors, namely alcohol,
drugs, unemployment, mental health and use of weapons. Predictor variables of
GBH at the first offence and age were also included in the analysis. Results showed
that a previous GBH offence did not significantly predict a GBH at the repeat offence.
A similar analysis was conducted as above using the above predictor variables but
this time using ABH and GBH at the first offence. This highlighted that a moderate,
ABH-level, injury or severe, GBH-level, injury at the repeat offence is predicted by
previous moderate of severe injury. Not only this, but the offenders age is significant
with unemployment being marginally significant. Research has previously shown
that a history of violence is a known predictor of further violence (Campbell, 2007). A
person’s criminal history may increase the risk of offending (Farrington, 1992).
Interestingly the initial findings have shown that a previous ABH/GBH-level injury can
predict a further injury of ABH/GBH. Due to lack of time this study was unable to
review offenders’ previous history and convictions and may have helped strengthen
this finding.
81
Furthermore age has been found to be a predictor of injury in further offences.
Previous research that tried to forecast a charge of homicide or attempted homicide
found that the most important variable was that of age, the age of the person on
probation or parole, when the offender first encountered the court system and the
number of prior convictions concerning a firearm (Berk et al, 2009).
Unemployment was only found to be marginally significant in predicting injury in
further offences but should be noted alongside the earlier findings.
Q5 What predicts increases in injury in further reoffending?
Results have shown that none of the offenders’ background characteristics are
significant predictors of increases in injury regardless of disposal. Alcohol, drugs,
unemployment, mental health and use of weapons are not significant in relation to
identifying a more severe injury in a further offence when comparing the three types
of disposal.
Limitations
Due to the limitation in time it was not possible to develop the research further. It
would have been interesting to see if there was any difference in result when
combining the offender’s background characteristics (Chermack and Blow, 2002).
Another area to develop would perhaps be reviewing the victims’ background
variables at the same time as the offender. Research has shown higher rates of
domestic violence occurs when both men and women are separated or divorced
(Rennison and Welchans, 2000).
82
It would be interesting to see if similar findings were found for domestic violence
crimes which included same sex relationships, male victims and between different
family members, to ease gender bias. Also this would assist in the generalisability of
this study.
As this study was based on archival data the dataset was already captured by Devon
and Cornwall Police thus limiting the research to certain variables that had been
collated over three years. Furthermore the study was limited in that only male
heterosexual offenders in an adult intimate relationship were studied in the sample
and only over a twelve month period with the data timeframe. For example, an
offender who committed domestic violence on the 13th May 2011 and did not offend
again until 13th November 2012 was not included in this study. The study hoped to
review offenders within a twenty four month period but due to the low number of
cases being only thirty three within this data set it was not feasible to continue
research in this regard.
Unfortunately there was no entry in the data to confirm whether offenders who were
charged no evidence of conviction were actually convicted or not. Thus findings
within the sample showing charged offenders are twice more likely to reoffend would
perhaps strengthen this finding if it could be ascertained whether those offenders
served time and for how long.
There are limitations to this study in that the data has also been linked to the
Domestic Abuse, Stalking and Harassment Risk Assessment Model (DASH).
However DASH was implemented in March 2010 and therefore did not cover the
whole data set, which commenced in October 2008. Nevertheless where this data
existed it highlighted the risk level and various qualifiers of drugs and alcohol, to
83
provide further evidence in looking at risk factors and offending behaviour. The data
sets were matched by crime reference number to align and mitigate problems
associated with using two data sets.
This study followed a cohort of offenders. A cohort is “the best method for
determining the incidence and natural history of a condition” (Mann, 2003:20:54).
However confounding variables are a major problem in analysing cohort studies
along with bias. Bias is caused by both subject selection and the loss of offenders to
follow-up (Mann, 2003). However this study was conducted over a short-time frame
which may have lessened such issues. Furthermore this study used police records
and followed offenders from the first offence in the data set, so the loss would occur
if the offender had moved away or died, thus bias is perhaps not such a big problem
in this study. Cohort progression of the effect of a variable in a particular time is
important but these studies cannot say conclusively they are caused by this; other
factors need to be considered and cannot be ruled out.
Furthermore this study looked at incidence cases per period of time to see if there is
any progression in resulting physical injury to the victim having arrested the offender.
However this study only shows if the offender goes on to commit further crimes,
whether there is an injury to the victim and if there is any severity.
In addition this study only looks at reported domestic violence crimes, those that
come to the police attention, there are likely to have been further injuries without the
offences having been reported. However as a police force we need to react to calls
of service and understand domestic violence thus research on the basis of police
reports is of use, even if it is only looking at part of the problem.
84
A more rigorous study for the future would perhaps need to look at other external
factors for example, different demographics, temporal changes and hours of the day.
Further research has shown that there are links between when domestic violence
occurs and that of the weather and or temporal differences (Cohn, 1993). However
due to the limitations of time and data recording issues this data was not available in
usable format for this study.
Research in the past has looked at the level of psychological abuse within a
relationship (Bennett et al, 2000). However this study was limited in that it only
looked at physical injuries and not psychological injury.
This study has taken data from domestic violence crimes committed in Devon,
Cornwall and the Isles of Scilly and although this is a large two county force, most of
its patrol area is rural. Therefore a further study could take place focusing on more
urban areas. Research has shown that you would be more likely to be a victim of
domestic violence in an urban environment compared to a rural setting (Rennison
and Welchans, 2000).
Overall this research had made a contribution to domestic violence research. The
sample was prospective in nature focusing on male heterosexual offenders over a
three year period within the geographic area of Devon, Cornwall and the Isles of
Scilly. No other study has been conducted with such a large sample, a data set that
covers a two county rural force and over a long period of time.
This study aimed to provide an original contribution to current research and a new
way of interpreting the data, strengthening the research in this field. The focus was
different from other studies that look at any type of repeats. Unlike other studies
which look at all repeats this study specifically focused on arrested offenders who go
85
on to commit crimes of domestic violence, reviewing those offenders who after initial
disposal have either received a cautioned, or been charged no evidence of
conviction or charged and convicted.
Therefore this study’s perspective could have important policy significance. Assisting
with policy setting, not only for police forces, providing practical operational
relevance for the police service but other public sector agencies, as a large amount
of time and money is spent dealing with domestic violence incidents.
The study used police records to go some way to understand the social issues and
to try to see what predicts injury and the level of injury in domestic violence. This
research is relevant, for the findings of this study could have implications to change
domestic violence policy and how we deal with offenders.
In turn this may lead to police forces and other public sector agencies to look at
current domestic violence policy and perhaps become more effective and efficient in
dealing with offenders for this particular crime type. Testing alternative policies could
lead to more effective solutions and drive operational policing in a new direction. For
example, how we use drug and alcohol referrals, or the effects of cautioning versus
charging an offender.
86
Conclusion
Many public sector agencies are tackling domestic violence on a daily basis and
utilising a significant amount of resources. More recently the Home Secretary in
September 2013 commissioned Her Majesty’s Inspectorate of Constabulary to look
at the effectiveness of the police response to domestic violence and abuse across
England and Wales. Therefore there is no better time to gain a greater
understanding of the issues and potential solutions.
A big problem facing the police is risk assessment and due to the reduction of
resources, focus is now on prioritisation of police work identifying threats, risk and
harm. The prediction of domestic violence is key in assisting with operational
delivery.
Previous research highlighted that “The accuracy (validity) and consistency
(reliability) of predicting dangerousness and violence depends on multiple complex
factors” (Campbell, 2007:9). Some of these predictive factors include history of
violence, mental illness, substance abuse including alcohol, gender, age,
unemployment, suicidal markers and the use of weapons (Campbell et al, 2001).
This study found similar findings confirming and building on previous research.
This study highlighted the relationship between offender’s background
characteristics and the prevalence of further domestic violence, namely the use of
alcohol and drugs for all three disposal types. These findings align with previous
research (Straus and Gelles, 1990). However this study goes further not only
highlighting alcohol and drugs as considerable predictors of repeat offending but
linking this to different types of disposal.
87
Furthermore this study showed that unemployment as a predictor of repeat offending
had mixed results depending on the initial disposal. Unemployment is important
when offenders are either cautioned or charged and convicted.
In addition other findings have shown that unemployment predicts frequency of
reoffending with a marginal significance in predicting injury in further offences.
Previous ABH/GBH-level crimes have shown to be predictors in injury in further
offences along with age of the offender. Research has previously shown that a
history of violence is a known predictor of further violence (Campbell, 2007).
However no predictors were found in predicting increases in injury in further
reoffending.
A more rigorous study for the future would perhaps need to look at the victims’
characteristics, or the offenders’ criminal history. Research has shown that a
persons’ criminal history may increase the risk of offending (Farrington, 1992).
This study has taken data from domestic violence crimes committed in Devon,
Cornwall and the Isles of Scilly and although this is a large two county force, most of
its patrol area is rural. Therefore a further study could take place focusing on more
urban areas.
The study ideally would be extended, to run over a longer period. Enabling offenders
to be followed up, not only at twelve months but again at twenty four months, to see
if similar findings could be found.
The study used the data set and variables to go some way to understand the social
issues and try to predict factors that may increase serious injury in domestic
violence. This research is relevant, for the findings of this study could have
88
implications to change domestic violence policy and how we deal with offenders. For
example, the use of drug and alcohol referrals, or the effects of cautioning versus
charging an offender.
The findings of this study help strengthen the use of alcohol and drug referral
programmes for offenders. This study has shown that offenders who use alcohol
and/or drugs are more likely to reoffend. By providing early support to substance
abuse offenders, it may reduce reoffending in the future.
Furthermore unemployment was found to be significant in further offending for those
who were cautioned or charged and convicted. Better signposting for these offenders
may help to reduce reoffending, the use of the third sector and volunteering,
providing training and skills opportunities to all.
However it should be always be remembered that domestic violence incidents are
under-reported and remain concealed within the community often behind closed
doors. This research may be able to provide a more focused approach when dealing
with offenders in the future and help safeguard victims.
90
Appendix A
Summary table of Chi-square test statistics, for the impact of offender characteristics on prevalence of injury,
(supplement to table 3).
Cautioned Charged no evidence of conviction
Charged and convicted Total Sample
Alcohol
χ²(1,N=1294)=3.67, p=.056,
OR =0.58
χ²(1,N=635)=0.121, p=.728,
OR =0.89
χ² (1,N=1169)=0.196, p=.658,
OR =1.10
χ² (1,N=3136)=.911, p=.340,
OR =0.87
Drugs
χ² (1,N=1294)=.726, p=.394,
OR =0.69
χ² (1,N=635)=1.35, p=.246,
OR =0.63
χ² (1,N=1169)=1.03, p=.309,
OR =0.76
χ² (1,N=3136)=3.41, p=.062,
OR =0.69
Unemployment
χ² (1,N=1294)=4.39, p=.036,
OR =0.76
χ² (1,N=635)=.243, p=.622,
OR =0.91
χ² (1,N=1169)=3.69, p=.055,
OR =1.12
χ² (1,N=3136)=9.17, p=.002,
OR =0.78
Mental Health
χ² (1,N=1294)=.321, p=.571,
OR =1.44
χ² (1,N=635)=.582, p=.446,
OR =0.85
χ² (1,N=1169)=.556, p=.456,
OR =0.90
χ² (1,N=3136)=3.04, p=.081,
OR =0.85
Weapons
χ²(1,N=1294)=27.16, p=.000,
OR =16.27
χ²(1,N=635)=9.99, p=.002,
OR =4.58
χ²(1,N=1169)=.34.85, p=.000,
OR =5.89
χ²(1,N=3136)=70.7, p=.000,
OR =6.77
91
Appendix B
Summary table of Chi-square test statistics, for the impact of offender characteristics on prevalence of further offences,
(supplement to table 5).
Cautioned Charged no evidence of conviction
Charged and convicted Total Sample
Alcohol
χ²(1,N=1294)=349.59, p=.000,
OR =52.13
χ²(1,N=630)=173.26, p=.000,
OR =29.95
χ² (1,N=1163)=385.53, p=.000,
OR =37.42
χ² (1,N=3122)=966.79, p=.000,
OR =42.39
Drugs
χ² (1,N=1294)=198.70, p=.000,
OR =65.73
χ² (1,N=630)=129.75, p=.000,
OR =38.86
χ² (1,N=1163)=298.65, p=.000,
OR =80.63
χ² (1,N=3122)=692.60, p=.000,
OR =67.64
Unemployment
χ² (1,N=1294)=5.75, p=.016,
OR =1.71
χ² (1,N=630)=3.57, p=.059,
OR =1.57
χ² (1,N=1163)=5.01, p=.025,
OR =1.47
χ² (1,N=3122)=24.95, p=.000,
OR =1.79
Mental Health
χ² (1,N=1294)=.214, p=.643,
OR =1.13
χ² (1,N=630)=.208, p=.649,
OR =1.12
χ² (1,N=1163)=.708, p=.400,
OR =1.17
χ² (1,N=3122)=2.00, p=.158,
OR =1.20
Weapons
χ²(1,N=1294)=.409, p=.523,
OR =0.72
χ²(1,N=630)=.004, p=.947, OR
=1.03
χ²(1,N=1163)=1.68, p=.195, OR
=1.39
χ²(1,N=3122)=1.49, p=.222, OR
=1.26
92
Appendix C
Summary table of Chi-square test statistics, for the impact of offender characteristics on a more severe injury for the further
offence, (supplement to table 10).
Cautioned Charged no evidence of conviction
Charged and convicted Total Sample
Alcohol
χ²(1,N=87)=3.45, p=.063,
OR =0.40
χ²(1,N=86)=.333, p=.564,
OR =1.29
χ² (1,N=161)=2.56, p=.109,
OR =1.76
χ² (1,N=336)=.297, p=.586,
OR =42.39
Drugs
χ² (1,N=87)=.157, p=.692,
OR =1.24
χ² (1,N=86)=.80, p=.777,
OR =1.14
χ² (1,N=161)=0.92, p=.761,
OR =1.12
χ² (1,N=336)=.435, p=.510,
OR =1.17
Unemployment
χ² (1,N=87)=000, p=.983,
OR =1.01
χ² (1,N=86)=.309, p=.578,
OR =1.28
χ² (1,N=161)=1.45, p=.228,
OR =1.55
χ² (1,N=336)=1.65, p=.199,
OR =1.36
Mental Health
χ² (1,N=87)=.214, p=.643, OR
=1.13
χ² (1,N=86)=.208, p=.649,
OR =1.12
χ² (1,N=161)=.708, p=.400,
OR =1.17
χ² (1,N=336)=2.00, p=.158,
OR =1.20
Weapons
χ²(1,N=87)=.810, p=.368,
OR =2.46
χ²(1,N=86)=.226, p=.635,
OR =0.70
χ²(1,N=161)=.200, p=.654,
OR =1.25
χ²(1,N=336)=.112, p=.738,
OR =1.14
93
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