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Department of Forensic Mental Health Science, Institute of Psychiatry, London
Division of Psychological Medicine, Institute of Psychiatry, London
Department of Health Services Research, Institute of Psychiatry, London
Division of Neuroscience and Psychological Medicine, Imperial College, London
School of Psychiatry and Behavioural Sciences, University of Manchester
Centre for the Economics of Mental Health, Institute of Psychiatry, London
Department of Psychiatry, University of Oxford
Division of Psychological Medicine, Institute of Psychiatry, London
Department of Forensic Mental Health Science, Institute of Psychiatry, London, UK
Correspondence: Dr Kimberlie Dean, PO 23, Department of Forensic Mental Health Science, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK. Tel: +44 (0)20 7848 0771; fax +44 (0)20 7701 9044; e-mail: k.dean{at}iop.kcl.ac.uk
Declaration of interest None. Funding detailed in Acknowledgement. P.T. is Editor of the British Journal of Psychiatry but had no partinthe evaluation of this paper for publication.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Aims To identify predictors of violence in a community sample of women with chronic psychosis.
Method The 2-year prevalence of physical assault was estimated for a sample of 304 women with psychosis. Baseline socio-demographic and clinical factors were used to identify predictors of assault.
Results The 2-year prevalence of assault in the sample was 17%. Assaultive behaviour was associated with previous violence (OR=5.87,95% CI 2.42–14.25), non-violentconvictions (OR=2.63,95% CI 1.17–5.93), victimisation (OR=2.46, 95% CI1.02–5.93), African–Caribbean ethnicity (OR=2.24,95% CI1.02–4.77), cluster B personality disorder (OR=2.66, 95% CI1.11–6.38) and high levels of unmet need (OR=1.17,95% CI1.01–1.35). An interaction between African–Caribbean ethnicity and cluster B personality disorder was identified in relation to violent outcome. Violent women were found to be more costly to services.
Conclusions Nearly a fifth of community-dwelling women with chronic psychosis committed assault over a period of 2 years. Six independent risk factors were found to predict violence.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Little is known about the gender-specific factors associated with risk of violence among individuals with psychosis. Clearly, women with psychosis are a vulnerable group, and the effect of mental illness on the risk of violence in this group requires further investigation. Our aim was to undertake this prospectively in a sample of women with psychosis who were living in the community in urban settings.
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METHOD |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Baseline measures
A number of socio-demographic and clinical variables were assessed at
baseline on the basis of interview and review of case notes. Clinical history
and life circumstances, including self-reported information on assaultive
behaviour, during the 2 years before baseline were assessed using the World
Health Organization Life Chart (World
Health Organization, 1992). The Comprehensive Psychopathological
Rating Scale (CPRS; Åsberg et
al, 1978) was used to assess current psychopathology. Two
items from the CPRS, namely ‘feeling controlled’ and ‘ideas
of persecution’, were taken together as a proxy measure for
threat/control override symptoms. The presence of comorbid personality
disorder was assessed using a rapid version of the Personality Assessment
Schedule (PAS–R; Tyrer et
al, 1979), a semi-structured interview schedule. Each
category of personality disorder was scored on a 3-point scale (0=absence of
dysfunction, 1=personality difficulty, 2=personality disorder). In the present
study, a dichotomous variable was created (personality disorder and no
personality disorder), with a score of 2 defining the presence of personality
disorder. Other baseline measures included the Scale for Assessment of
Negative Symptoms (SANS; Andreason,
1984), the National Adult Reading Test (NART;
Nelson, 1982), the Lancashire
Quality of Life Profile (Oliver,
1991), the Camberwell Assessment of Need (CAN;
Phelan et al, 1995);
the Mental Needs Index (MINI; Glover et
al, 1998) and the World Health Organization Disability
Assessment Schedule (DAS; Jablensky et
al, 1980). Participants were asked about their alcohol and
drug use by means of a questionnaire designed specifically for this study. A
demographic schedule was also devised to gather information about ethnicity,
level of education, history of medical illnesses and employment status, among
other variables. In addition to obtaining information from interviews and case
notes, an application was made to the British Home Office for the full
criminal records for each participant, categorised into violent and
non-violent convictions. Ethical approval for the study was obtained from the
four local ethics committees.
Outcome measures
The main outcome of interest was violence during the 2 years of follow-up.
This was defined as actual physical contact regardless of severity or
resulting injury of the victim. Three data sources were combined to produce a
binary result for each patient, namely self-report, case-note review and case
manager’s report. Data on costs associated with healthcare, social and
non-statutory sector services and prison/police custody were also collected. A
full description of the economic methodology employed has been published
previously (UK700 Group,
2000).
Statistical methods
Analyses were performed using the Statistical Package for the Social
Sciences version 11.0 statistical software for Windows. The prevalence of
violence over the 2-year follow-up period was determined. Before the data were
inspected, a list of possible baseline predictor variables was drawn up from
the clinical and demographic measures available. Initially the data were used
to establish a baseline description of the study sample. Logistic regression
analysis was then used to compare individuals who were violent with those who
were not with regard to the putative predictor variables. Both categorical and
continuous variables were included in the analysis. If continuous variables
were found to be highly skewed, categorical variables were created by dividing
data according to the median. After a univariate analysis had been performed
(Tables 1 and
2), a multivariate analysis was
undertaken using a stepwise method (Table
3). All univariately significant factors were entered in the
model, and those that were no longer significant were then removed. After this
stage, each univariate factor tested was entered individually to establish a
final model that best predicted violence as the outcome. Tests were also
performed to examine the possibility of interactions between the independent
predictors identified and the univariately significant factors for violence as
the outcome.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Prevalence of violence
Information on violence was available from at least one data source for all
women (n=304), and no significant difference in the availability of
information was found between the two groups. Information on violence was
available for 95% of the women based on self-report, for 75% based on the case
manager’s interview and for 93% based on case-note review. Over the
2-year follow-up period, 53 women (17%) physically assaulted another
person.
Univariate analysis
The socio-demographic profile of women who committed assault during the
2-year follow-up period is shown in Table
1. Compared with non-violent women, violent women were more likely
to be younger and of African–Caribbean ethnic origin. They were also
more likely to have reported being victims of violence themselves in the year
before commencement of the study. Violent women more often had a history of
committing assault in the 2 years before baseline, and were more likely to
have a conviction for a non-violent offence than women who were not violent
during the study. No associations were found between violence and employment
status, educational achievement or measures of living circumstances (e.g.
homelessness). Importantly, there was no association between being randomised
to intensive v. standard case management and an outcome of violence
in this sample.
The clinical characteristics of the women who were violent during the study period are listed in Table 2. They were more likely to have an earlier age of onset of illness (under 30 years) and a diagnosis of cluster B personality disorder compared with non-violent women (impulsive personality disorder, n=9; dissocial personality disorder, n=4; histrionic personality disorder, n=4; borderline personality disorder, n=4 in the violent group). They also had higher levels of disability, psychopathology and unmet need. However, violent women were not more likely to report misuse of either alcohol or drugs.
The Lancashire Quality of Life Profile (Oliver, 1991) provided information about the way in which the participants perceived their circumstances when interviewed at baseline. Compared with non-violent women, those who were violent during the study were less satisfied with their personal safety (odds ratio (OR)=2.14, 95% CI 1.17–3.91), wanted to move but felt unable to do so (OR=2.02, 95% CI 1.03–3.98), and were dissatisfied with their financial status (OR=2.39, 95% CI 1.11–5.15). However, there were no significant differences in the way that they perceived the safety of their neighbourhood, the support provided by their family or the pleasure they derived from leisure activities.
We then examined the costs associated with healthcare, social and non-statutory sector services, and time spent in prison/police custody for each of the women. Those who were violent during the 2 years of the study were significantly more costly to services than non-violent women. Violent women were more than three times (OR=3.63, 95% CI 1.83–7.16) more likely to require overall care costing over £12 000 during the 2 years of the study than non-violent women (£12 000 was the median cost for the whole sample). Violent women accrued more costs associated with supported accommodation, social services involvement, prison service involvement and healthcare, although only the difference in the latter area of cost reached the level of statistical significance. We did not have access to detailed data that would allow comparison of service contacts between the two groups. However, we did find that violent women spent more time in hospital and were more likely to have spent time in prison during the study, although the differences were not significant (see Table 2). In the whole sample of women with psychosis, the following factors were found to independently predict high total cost: level of unmet need; absence of alcohol misuse; number of days in hospital; and conviction for a non-violent offence. When these factors were added to the unadjusted model, violence during follow-up remained significantly associated with high total costs, but the odds ratio decreased.
Multivariate analysis
Table 3 shows the final
multivariate model with each predictor adjusted for all of the others in the
univariate tables. The following six factors remained in the multivariate
model as significant predictors of violence in the sample: being of
African–Caribbean ethnic origin; having been a victim of violence;
admitting to a history of violence; having a conviction for a non-violent
offence; having comorbid cluster B personality disorder; and having a high
level of unmet need.
We tested for interactions using logistic regression analysis by entering an interaction term for ethnicity and factors which were found to be univariately significant in the initial analysis. Cluster B personality disorder was the only factor that was found to contribute any significant interaction to the association between ethnicity and violence. African–Caribbean women with cluster B personality disorder were more likely to be violent than African–Caribbean women without this disorder. We also subsequently adjusted the final model for age, which in itself did not remain significant in the model, but eliminated the significance of being a victim of violence as a predictor.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Methodological issues
This study has a number of strengths. Predictors of violence were
investigated in a prospective manner in a large sample of women, thus avoiding
the problems inherent in retrospective analyses. Importantly, multiple sources
of data were used to identify with greater accuracy those women who were
violent during the period of follow-up. Different methods of assessing
violence can produce very different results, particularly among patients
living in the community, so the use of a multiple source design has important
advantages (Mulvey et al,
1994). The inclusion of self-reported violence is also important,
as this method has been shown to produce higher prevalence figures for
violence than the use of other sources
(Lidz et al,
1993).
Operational definitions of psychosis were used in the study, in addition to well-validated instruments that were predominantly based on interview rather than on records. The large size and community-based nature of the sample also offer a number of advantages. The participants were typical of individuals with chronic and severe psychosis managed by mental health services in the community. The urban settings of the four centres may limit the extent to which our results can be generalised to more rural populations. Finally, the completion rate for measurement of outcome over 2 years was high, and information about violence was collected from at least one source for each woman.
One limitation of our study is the lack of information on the frequency, severity and context of the violent episodes recorded, and on the perpetrator’s relationship to the victim. Previous research indicates that such factors differ between men and women in populations with and without mental illness (Hiday et al, 1998). The MacArthur Violence Risk Assessment Study found that men were more likely to commit violence that resulted in serious injury, whereas women were more likely to target family members and to be violent in the home (Robbins et al, 2003). Clearly this is an area that requires further investigation. We also lacked any information about compliance with treatment provided by mental health services, a factor which has been found to predict violence in individuals with mental disorder (Swartz et al, 1998).
Prevalence of violence
It is difficult to compare the prevalence of violence found in the present
study with that reported from previous investigations, as there is little
consistency in the way that violence is either measured or defined. In
addition, the selection of samples and the populations from which they are
derived vary widely. During a 1-year follow-up after discharge from hospital,
24.6% of the women in the MacArthur Violence Risk Assessment Study committed
an act of violence, but that study included women with a range of primary
mental disorders in addition to psychosis
(Robbins et al,
2003). During the first 20 weeks, 7.14% of women who had a
diagnosis of schizophrenia, bipolar disorder or other psychosis were violent
in the MacArthur study.
Risk factors for violence
After adjustment for potential confounders, six factors were found to
predict assault during the follow-up period
(Table 3). A past history of
violence has consistently been found to predict subsequent violence in a
number of populations (Tardiff et
al, 1997; Steinert,
2002). It is one of the most robust of the static risk factors
that are used to predict future violence. In our study, we also found that a
history of conviction for a non-violent offence predicted assault during the
follow-up period. This may indicate that women with psychosis who commit
assault do so in the context of a criminal lifestyle.
Women of African–Caribbean ethnic origin were more likely to commit assault, and this association persisted after adjustment. This is consistent with previous findings from a study of a similar population of individuals with schizophrenia, which reported that belonging to an ethnic minority (predominantly African–Caribbean) independently increased the risk of criminal conviction for both men and women (Wessely, 1998). In our study, an interaction between ethnicity and cluster B personality disorder was found to be an important explanatory factor in the association with assault. Among the African–Caribbean women, those with comorbid cluster B personality disorder (n=13) were more likely to be violent. However, no association was found between comorbid diagnosis of any personality disorder and ethnic origin in the larger sample of men and women from which our study sample was drawn (Moran et al, 2003). Little is known about the prevalence and correlates of personality disorder in Black and minority ethnic groups. Personality disorder has in fact been found to be less common among African–Caribbean patients than among White patients presenting to psychiatric services in the UK (Tyrer et al, 1994), but the rates in the general population are as yet unknown. Rather than reflecting a genuinely lower prevalence, the rarity of personality disorder among Black patients in treatment may be due to diagnostic or selection bias (Ndegwa, 2004). Another potential interacting factor that we considered, namely substance misuse, was not found to be associated with either ethnicity or violence in our sample, but the limitations of the measure available may have impaired our ability to detect such associations. However, our finding that rates of substance misuse did not differ between ethnic groups is supported by recent evidence in this area (Hutchinson & Haasen, 2004).
The presence of comorbid personality disorder is known to increase the risk of violence among people with a psychotic disorder, and this has been confirmed by analysis of the entire sample from which our study sample of women was drawn (Moran et al, 2003). Personality disorder has also been shown to be prevalent among women without psychosis who commit serious assault (Putkonen et al, 2003). In our sample of women with psychosis we found that the presence of cluster B (borderline, dissocial, histrionic and impulsive) personality disorder in particular predicted violence, and this association persisted after adjustment. We also found that the presence of cluster C personality disorder (obsessive–compulsive, dependent and avoidant) protected against violent behaviour during the follow-up period, but this association did not remain after adjustment, when the impact of the small number of individuals with the disorder is likely to have been significant. One problem that arises when considering the role of comorbid personality disorder in relation to risk of violence is the fact that one of the diagnostic criteria for a diagnosis of antisocial personality disorder is a history of aggression, although in our sample impulsive rather than dissocial personality disorder was more common in the violent group. Other difficulties associated with the assessment of personality in individuals with psychosis have been highlighted previously (Moran et al, 2003), but it is not known whether these are gender-dependent. As was noted previously, little is known about personality disorder in Black and minority ethnic groups, and since most research on antisocial personality disorder has focused on men, very little is known about women with this disorder (Mulder et al, 1994). The present study therefore provides valuable descriptive epidemiological data in both of these respects.
In addition to the above predictors, we found two factors which have not been reported frequently in other studies, and which may reflect risk factors that are particularly relevant to women. Victimisation was found to independently predict violence during the follow-up period, but this did not remain significant after adjustment for age. An analysis of the UK700 data was recently undertaken to establish the prevalence of violent victimisation in the entire sample (Walsh et al, 2003). In total, 16% of patients (men and women) with psychosis reported being the victim of violence in the year before baseline, and associations were found with severity of symptoms, homelessness, substance misuse, comorbid personality disorder and previous violent behaviour. Victimisation may again reflect the criminal nature of the lifestyle and social milieu of women with psychosis who go on to commit assault. However, only 35% of the women who were victimised committed assault during the follow-up period, so clearly other factors are operating to alter the role of being a victim in predicting later violence. Perceptions of safety may mediate the link between victimisation and violence. We found that women who committed assault were less satisfied with their personal safety than those who did not, but we found no differences when we enquired about their perceptions of the safety of their neighbourhood.
The final independent predictor that was identified in this study was the association between higher levels of unmet need at baseline and later violence. This may reflect problems both with the provision of services and with the engagement of women with psychosis with such services. Current service provision may be inadequate, inappropriate, or both, and may well be rejected by women with psychosis, who themselves are likely to have certain personality characteristics which contribute to the development of dysfunctional relationships with others. In addition, the high level of unmet need may reflect a lack of informal support which is caused by poor social networks. In a post-hoc analysis, women who committed assault were found to have significantly more serious problems with regard to unmet need in the areas of daily activity, childcare, basic education and finances.
Economic considerations
In addition to establishing predictors of violence, we found that women
with psychosis who committed assault during follow-up were more costly to
services. This clearly has implications for the planning of service provision.
These women incurred more costs to public services in several areas, including
health, criminal justice and social services. Interestingly, in addition to
finding that unmet need predicted violence, we also found an association
between unmet need and total costs in the total sample. Our analysis also
suggests that some of the high costs are likely to be due to time spent in
hospital and in contact with the criminal justice system, perhaps for
non-violent offences in particular. Thus not only are these women more costly
to public services, but also their needs are still not being met by those very
services.
Implications and further research
Our findings with regard to predictors of violence are similar to previous
findings, highlightling history of previous violence, comorbid personality
disorder, previous conviction and specific minority ethnicity. Predictors such
as victimisation and higher levels of unmet need may represent factors that
are particularly relevant to women with a psychotic disorder. In contrast to
other studies, we did not find an association with substance misuse. This may
reflect a lower prevalence of substance misuse among women with psychosis (12%
of the women in our study misused drugs). We also considered the possibility
that our measure of substance misuse may well have had limitations that
rendered it inadequate for demonstrating a link with violence. In addition, no
data were available on compliance with treatment, and we did not find an
association with the presence of threat/control override symptoms, which has
been reported previously (Link et
al, 1998).
The high prevalence of violence during follow-up in our sample, as well as the finding of the high costs to services incurred by this group, both highlight the importance of considering the risk of violence in women with chronic psychosis. Clinicians have been shown to consistently underestimate the potential risk of violence posed by female patients with psychosis (Lidz et al, 1993; Coontz et al, 1994), and consequently this risk may be less likely to be considered when management plans are devised. It has been argued that the inability of clinicians to recognise the potential risk of violence among female patients may contribute substantially to the poor results that are often obtained when risk prediction by clinicians is evaluated (Robbins et al, 2003). Violence is regarded as a male phenomenon by clinicians and the lay public alike.
Our findings support the need to raise awareness of the risk of violence in women with psychosis, and they provide some indication of the factors that should be the focus of risk assessment and management. Further research is needed to explore the important predictors of violence in women with mental illness from a range of populations, and also to evaluate the benefits of addressing such factors with a view to reducing the risk of violence.
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Clinical Implications and Limitations |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONClinical Implications and...ACKNOWLEDGMENTSREFERENCES |
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Received for publication December 21, 2004. Revision received May 31, 2005. Accepted for publication June 1, 2005.
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