POL116 Nikki Leaper Fitzwilliam College Supervisor: Dr ...library.college.police.uk/docs/repeat-offending-after-cautioning.pdf · Fitzwilliam College Supervisor: Dr Katrin Müller-Johnson

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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

7

List of tables

8

Introduction

9

Literature Review

13

What we know

13

Reporting and under-reporting

14

Prediction of domestic violence

17

Risk assessment

21

Personal characteristics of offenders

25

Present research aims

28

Methods

31

Specific research questions

31

Data source

31

Data analysis plan

35

Preparation of data/selection of cases

35

First 5000 crimes – creating the final data set

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Results

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Description of sample

40

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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Q2 Is there a relationship between offenders’ background variables and prevalence of further domestic violence offending?

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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

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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:



Risk assessment


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.


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.


“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

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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).


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.

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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?




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.


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


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



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.


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.


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



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


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


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.


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


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


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.

89

Appendices

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).



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).



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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Documents

POL116 Nikki Leaper Fitzwilliam College Supervisor: Dr ...library.college.police.uk/docs/repeat-offending-after-cautioning.pdf · Fitzwilliam College Supervisor: Dr Katrin Müller-Johnson