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Psychiatric symptoms and risk of victimisation: a population-based study from Southeast London

Published online by Cambridge University Press:  10 September 2018

V. Bhavsar*
Affiliation:
Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 8AF, UK South London and Maudsley NHS Foundation Trust, Maudsley Hospital, London SE5 8AZ, UK
K. Dean
Affiliation:
School of Psychiatry, University of New South Wales, Australia Justice Health & Forensic Mental Health Network, New South Wales, Australia
S. L. Hatch
Affiliation:
Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 8AF, UK
J. H. MacCabe
Affiliation:
Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 8AF, UK South London and Maudsley NHS Foundation Trust, Maudsley Hospital, London SE5 8AZ, UK
M. Hotopf
Affiliation:
South London and Maudsley NHS Foundation Trust, Maudsley Hospital, London SE5 8AZ, UK Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 8AF, UK
*
Author for correspondence: Vishal Bhavsar, E-mail: vishal.2.bhavsar@kcl.ac.uk
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Abstract

Aims

Although violence is a vital public health problem, no prospective studies have tested for subsequent vulnerability to violence, as a victim or witness, in members of the general population with a range of psychiatric symptoms, or evaluated the importance of higher symptom burden on this vulnerability.

Methods

We used successive waves of a household survey of Southeast London, taken 2 years apart, to test if association exists between psychiatric symptoms (symptoms of psychosis, common mental disorders, post-traumatic stress disorder and personality disorder) and later victimisation, in the form of either witnessing violence or being physically victimised, in weighted logistic regression models. Statistical adjustment was made for prior violence exposure, sociodemographic confounders, substance/alcohol use and violence perpetration. Sensitivity analyses were stratified by violence perpetration, sex and history of mental health service use.

Results

After adjustments, psychiatric symptoms were prospectively associated with reporting any subsequent victimisation (odds ratio (OR) 1.88, 95% confidence interval (CI) 1.25–2.83), a two times greater odds of reporting witnessed violence (OR 2.24, 95% CI 1.33–3.76) and reporting physical victimisation (OR 1.76, 95% CI 1.01–3.06). One more symptom endorsed was accompanied by 47% greater odds of subsequent victimisation (OR 1.47, 95% CI 1.16–1.86). In stratified analyses, statistical associations remained evident in non-perpetrators, and among those without a history of using mental health services, and were similar in magnitude in both men and women.

Conclusions

Psychiatric symptoms increase liability to victimisation compared with those without psychiatric symptoms, independently of a prior history of violence exposure and irrespective of whether they themselves are perpetrators of violence. Clinicians should be mindful of the impact of psychiatric symptoms on vulnerability to victimisation, including among those with common psychiatric symptoms and among those who are not considered at risk of perpetrating violence.

Type
Special Articles
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2018

Introduction

Violence towards people with psychiatric disorders remains a pressing public health and human rights issue (Krug et al., Reference Krug, Mercy, Dahlberg and Zwi2002), and negatively impacts symptoms in those with psychotic (Goodman et al., Reference Goodman, Rosenberg, Mueser and Drake1997) and bipolar disorders (Neria et al., Reference Neria, Bromet, Carlson and Naz2005). Victimisation is also associated with greater service utilisation, greater substance misuse and poorer functional status in the community (Hodgins et al., Reference Hodgins, Lincoln and Mak2009). The correlation between treated psychiatric disorders and suffering violence (as a witness and/or victim), particularly for physically violent victimisation, is supported by much observational evidence from large samples (Lehman and Linn, Reference Lehman and Linn1984; Hiday et al., Reference Hiday, Swartz, Swanson, Borum and Wagner1999; Walsh et al., Reference Walsh, Moran, Scott, McKenzie, Burns, Creed, Tyrer, Murray and Fahy2003; McDonald and Richmond, Reference McDonald and Richmond2008; Maniglio, Reference Maniglio2009), particularly among those with severe disorders such as schizophrenia. Various candidate explanations might contribute to this association. Victimisation could result in psychiatric disorder (Resnick et al., Reference Resnick, Acierno and Kilpatrick1997; Acierno et al., Reference Acierno, Brady, Gray, Kilpatrick, Resnick and Best2002). Alternatively, the association could be influenced by risk factors for both victimisation and psychiatric disorder, for example, socioeconomic position (Wohlfarth et al., Reference Wohlfarth, Winkel, Ybema and van den Brink2001) or substance misuse (Dansky et al., Reference Dansky, Saladin, Brady, Kilpatrick and Resnick1995; Hedtke et al., Reference Hedtke, Ruggiero, Fitzgerald, Zinzow, Saunders, Resnick and Kilpatrick2008). Thirdly, the association between psychiatric disorders and violence might be an artefact of selection bias, resulting from studying only people using services or who are being treated (Pearce and Richiardi, Reference Pearce and Richiardi2014). A further, less researched, possibility is that mental disorders themselves increase vulnerability to victimisation (Silver et al., Reference Silver, Arseneault, Langley, Caspi and Moffitt2005; Hart et al., Reference Hart, de Vet, Moran, Hatch and Dean2012). In terms of these candidate explanations, there is now reasonable evidence for an effect of victimisation on mental disorder, particularly for disorders such as psychosis (in relation to childhood victimisation (Varese et al., Reference Varese, Smeets, Drukker, Lieverse, Lataster, Viechtbauer, Read, Van Os and Bentall2012)) and post-traumatic stress disorder (PTSD) (Kessler et al., Reference Kessler, Sonnega, Bromet, Hughes and Nelson1995; Kessler et al., Reference Kessler, Sonnega, Bromet, Hughes, Nelson and Breslau1999; Frissa et al., Reference Frissa, Hatch, Gazard, Fear and Hotopf2013). Recently, studies in general population cross-sectional samples have confirmed associations between victimisation and mental health (Kadra et al., Reference Kadra, Dean, Hotopf and Hatch2014; Khalifeh et al., Reference Khalifeh, Johnson, Howard, Borschmann, Osborn, Dean, Hart, Hogg and Moran2015), suggesting the association is not fully accounted for by selection biases affecting studies on clinical populations.

Prospective evidence on the relationship between mental disorders and later victimisation is needed. Whether increased vulnerability to victimisation applies only to more severe disorders such as psychosis, or also pertains to commoner psychiatric symptoms, is also unknown. Furthermore, violence perpetration and victimisation are known to overlap (Johnson et al., Reference Johnson, Desmarais, Dorn and Grimm2015, Reference Johnson, Desmarais, Tueller, Grimm, Swartz and Van Dorn2016); however, few studies of mental health and victimisation have accounted for violence perpetration (Silver et al., Reference Silver, Arseneault, Langley, Caspi and Moffitt2005; Choe et al., Reference Choe, Teplin and Abram2008).

Residents of Southeast London have high levels of psychiatric morbidity and mental health service use (Hatch et al., Reference Hatch, Harvey and Maughan2010, Reference Hatch, Frissa, Verdecchia, Stewart, Fear, Reichenberg, Morgan, Kankulu, Clark and Gazard2011). We have previously reported cross-sectional associations between victimisation and psychiatric symptoms (in particular, symptoms of depression/anxiety, psychotic symptoms, symptoms of post-traumatic stress (PTS) and personality symptoms). We found considerable overlap between the different forms of victimisation, and presented evidence that the distinction between proximal (i.e. in the last year) and distal (lifetime) violence exposure types revealed different patterns of sociodemographic and mental health associations (Kadra et al., Reference Kadra, Dean, Hotopf and Hatch2014). In this previous study, the 1-year prevalence of witnessed violence was 7.4%, and of violent victimisation, 6.3%. This is substantially higher than the 1-year prevalence of physical violence reported by respondents to the 2007 British Crime Survey, a UK general population-based study of violence and crime, in which the proportion of respondents (aged 16 and over) reporting physical victimisation in the previous year was 2.4% (Kershaw et al., Reference Kershaw, Nicholas and Walker2008). The relatively high levels of reported violence, and of psychiatric symptoms, in Southeast London, make it an appropriate setting to study the longitudinal association between psychiatric symptoms and violence.

Therefore, in this paper, we investigate the association between psychiatric symptoms and later victimisation (either by being physically victimised, or witnessing violence, and overall) in a representative sample of household residents in Southeast London. We hypothesise that the presence of psychiatric symptoms, and increasing number of symptom domains present, will be associated with later victimisation.

Methods

Sample details

The South East London Community Health study (SELCoH-1, 2008–2010) (Hatch et al., Reference Hatch, Frissa, Verdecchia, Stewart, Fear, Reichenberg, Morgan, Kankulu, Clark and Gazard2011) is a UK psychiatric and physical morbidity survey of 1698 adults aged 16 years and over, residing in 1075 randomly selected households in the boroughs of Southwark and Lambeth. Following SELCoH-1 (2008–2010), 1596 (94%) agreed to be re-contacted for a follow-up interview, of which 544 later declined consent for data collection or were ineligible due to death/poor health/relocation, The remaining 1052 participants (62%) were interviewed during 2011–2013, for SELCoH-2 (Hatch et al., Reference Hatch, Gazard, Williams, Frissa, Goodwin, Hotopf and Team2016). Sampling was clustered by household, with all adults living in selected households invited to participate. Full details of the study, its sampling methods, and representativeness are published (Hatch et al., Reference Hatch, Frissa, Verdecchia, Stewart, Fear, Reichenberg, Morgan, Kankulu, Clark and Gazard2011). Data for this analysis on psychiatric symptoms were taken from SELCoH-1, and information on victimisation was drawn from SELCoH-2, and weights used to account for within-household non-response, clustering of responses within households and attrition between SELCoH-1 and SELCoH-2. Data on covariates for multivariable modelling were all taken from SELCoH-1.

Measures

Psychiatric symptoms and service use at SELCoH-1

Psychiatric symptoms were measured in SELCoH-1 using a combination of community screening tools for separate domains of symptoms. The Psychosis Screening Questionnaire (PSQ) (Bebbington and Nayani, Reference Bebbington and Nayani1995) was used to assess non-affective psychotic symptoms, including strange experiences, paranoia, hallucinations and thought disorder. Individuals were considered to have psychotic symptoms if they endorsed one or more secondary items in these four areas. This approach is consistent with a previous analysis of psychotic symptoms originating from these data (Morgan et al., Reference Morgan, Reininghaus, Reichenberg, Frissa, Hotopf and Hatch2014). PTS symptoms were assessed using the PC-PTSD, a screening tool for PTSD designed for primary care use, which is based on the diagnostic criteria for PTSD in DSM-V. The PC-PTSD contains four items, of which three were necessary for the ascertainment of probable PTS symptoms – this cut-off identifies PTSD with a sensitivity of 0.76 and a specificity of 0.88 (Prins et al., Reference Prins, Ouimette, Kimerling, Camerond, Hugelshofer, Shaw-Hegwer, Thrailkill, Gusman and Sheikh2003). The Clinical Interview Schedule (Revised, CIS-R (Lewis and Pelosi, Reference Lewis and Pelosi1990)), was used to measure symptoms of depression and anxiety, applying a cut-off score of 12 to identify those with depressive/anxiety symptoms, in line with the original receiver operating curve analysis and subsequent studies using this tool. The Standardised Assessment of Personality – Abbreviated Scale (SAPAS (Moran et al., Reference Moran, Leese, Lee, Thornicroft and Mann2003)) was used to identify people with probably personality dysfunction. This tool contains eight binary items assessing domains of personality function, of which four positive items were necessary to be coded as screening positive for personality dysfunction. The scale demonstrates good psychometric properties, and using a cut-off of 3, identifies the presence of personality disorder in clinical populations with a sensitivity of 0.94 and a specificity of 0.85. In accordance with previous research on non-clinical populations, a cut-off of 4 was used, which has a better positive predictive value in populations where the prevalence of clinically significant personality symptoms is lower (Fok et al., Reference Fok, Hotopf, Stewart, Hatch, Hayes and Moran2014).

Participants endorsing at least one of the domains: psychotic symptoms, depressive/anxiety symptoms, PTS symptoms or personality dysfunction, as defined above, were classed as having psychiatric symptoms in one or more domains. Participants were also classified based on the number of psychiatric symptom domains they endorsed, grouped into 0, 1–2 and 3–4 domains. Finally, a binary item was created for mental health service use, based on items assessing whether or not the respondent had seen a GP, mental health specialist or a psychological therapist for mental health reasons in the previous year.

SELCoH-1 covariates

Age was categorised in the following intervals: 16–24, 25–34, 35–54 and 55 years or older. Ethnicity information was available based on self-reported UK Census categories, which were collapsed into two categories reflecting white participants and those of black and minority ethnicity (BME). Employment status was categorised into employed, student, unemployed and other (Kadra et al., Reference Kadra, Dean, Hotopf and Hatch2014). Recent use of illicit drugs was indicated by reports of the use of amphetamines, cocaine, crack cocaine, heroin, LSD or ecstasy in the previous year. A cut-off score of 8 out of 40 on the Alcohol Use Disorders Identification Test (Saunders et al., Reference Saunders, Aasland, Babor, de la Fuente and Grant1993) was used to identify hazardous alcohol consumption. Perpetration of violence was assessed by asking respondents whether they had ever (1) attacked or robbed someone; (2) injured someone with a weapon; or (3) hit, bit or slapped another person. This information was not available in SELCoH-2. Lifetime victimisation was assessed in SELCoH-1 by items inquiring whether the respondent had ever experienced (a) physical attack, (b) injury with a weapon, (c) witnessed violence or (d) either physical or sexual abuse in childhood. These were combined into a binary category reflecting any violence exposure at baseline.

Recent victimisation and witnessed violence

Respondents to SELCoH-2 were asked whether they had, in the previous 12 months, been exposed to physical violence in the form of having been attacked, robbed, mugged or been the victim of a serious crime; having been injured with a weapon, such as a gun, knife or stick; or been hit, bitten, slapped, kicked or sexually assaulted. Witnessed violence was determined by asking participants whether they had seen something violent happen to someone (e.g. someone being attacked or beaten or killed) in the last 12 months. Finally, a binary ‘overall victimisation’ variable was created, reflecting endorsement of either being physically victimised or witnessing violence.

Analysis

All statistical analyses were performed in STATA 14 (StataCorp, 2014), and took account of weights for non-response within households, household clustering and attrition between SELCoH-1 and SELCoH-2. Participants successfully interviewed at SELCoH-2 were compared with those not interviewed (for reasons of ineligibility or loss to follow-up). Univariate associations were estimated between the endorsement of each psychiatric symptom domain and each violence type, using logistic regression models, estimating odds ratios. For multivariable logistic regression modelling, potential confounders selected from the literature were included as covariates if the difference between the adjusted and unadjusted estimates was >10% (Greenland et al., Reference Greenland, Daniel and Pearce2016). Having identified potential confounders for inclusion in the final model, these were grouped into baseline victimisation (model I), then adding sociodemographic confounders (model II) and then substance-related confounders (model III). Finally, we additionally adjusted for perpetration to arrive at a fully adjusted estimate (model IV).

Linear associations between the number of psychiatric symptom domains endorsed, and odds of victimisation, were assessed with likelihood ratio tests. To further assess the influence of gender, perpetration history and evaluate whether associations were limited to those with previous mental health service use, further analyses were stratified by perpetration history in S1, history of mental health service use and sex.

Results

Description of sampling

Of 1698 individuals participating in SELCoH-1, 1052 (62%) participated in SELCoH-2 (Hatch et al., Reference Hatch, Gazard, Williams, Frissa, Goodwin, Hotopf and Team2016). Respondents in the first wave of data collection who were lost to follow-up tended to be younger, male, unemployed and of BME ethnicity. The time elapsed between baseline and follow-up data collection was 3 years. Interval between the baseline and follow-up interview ranged between 14.8 and 51.8 months, with a median of 29.9 months; this did not vary statistically by victimisation/witness status.

Included participants

After excluding 54 records with missing data on any modelled variables in both waves of data collection, 998 participants remained, with an age range of 16–88, of whom 59% were female and 35% were of BME ethnicity. Three hundred and sixty-nine participants (37%, Table 1) endorsed any psychiatric symptom domain at baseline interview. Meeting thresholds for one or more of the symptom domains was commoner in women than men, and among the unemployed compared with the employed. Endorsing one or more symptom domain was around twice as common among those with a history of service use (62%), compared with those without (34%). In baseline data, PTS symptoms were least prevalent and depressive/anxiety symptoms most common. Nearly three-fifths had been exposed to violence during their lifetime in the baseline interview. At follow-up, 5.9% of participants reported recent (past 12 months) physical victimisation, 6.8% reported recent witnessed violence and 11.2% reported any victimisation (Table 2).

Table 1. Descriptive data on included participants classified by presence of any psychiatric symptom domain (n = 998)

BME, black and minority ethnic status.

Raw counts are presented, with survey-weighted proportions in parentheses.

Table 2. Descriptive data on overall sample, and included participants

BME, black and minority ethnic status.

Raw counts are presented, with survey-weighted proportions in parentheses.

a Percentages based on proportion of baseline sample (n = 1698).

b Percentages based on proportion of participants included in the analysis (n = 998).

χ2 p-value for the association with inclusion in analysis: bp = 0.001, cp = 0.045, dp = 0.004, ep < 0.001, fp = 0.229, gp = 0.416, hp = 0.084, ip = 0.524, jp = 0.854, kp = 0.129, lp = 0.911, mp = 0.273, np = 0.142, op = 0.055.

Univariate associations

Victimisation reduced with age, and was more common among males, those of BME ethnicity, those reporting recent substance use and those meeting thresholds for any psychiatric symptom domains (Table 3). Overall victimisation was statistically associated with psychotic symptoms, but not with personality dysfunction, PTS symptoms or depressive/anxiety symptoms, after adjusting for prior violence exposure. Psychotic symptoms and hazardous alcohol use were associated with subsequent witnessed violence, after adjustment for prior violence exposure.

Table 3. Univariate prospective associations (odds ratios with 95% confidence intervals) with each type of violence exposure in the final sample (n = 998)

All estimates are based on 998 cases with complete records on modelled variables, take account of household non-response, household clustering of responses and attrition between baseline and follow-up interviews.

a Adjusted for lifetime violence exposure at baseline.

b Reference group is 16–24, the youngest age group.

Multivariable modelling

After adjustment, endorsing any psychiatric symptom domain was associated with a greater than twofold increase in the odds of later witnessed violence, a 1.75-fold increase in the odds of being physically victimised and a close to twofold increase in the odds of overall victimisation (see Table 4). Statistical evidence (p < 0.001) was found for a linear trend between the number of symptom domains endorsed and overall victimisation. Compared with those not endorsing any symptom domain, those reporting 3–4 symptom domains had more than three times the odds of reporting recently witnessed violence, and twice the odds of reporting physical victimisation, in adjusted models. For each further symptom domain endorsed, there was a 1.55-fold increase in the odds of later witnessed violence, a 1.3-fold increase in the odds of later physical victimisation, and a 1.47-fold increase in the odds of overall victimisation.

Table 4. Partial and fully adjusted logistic regression models for the association (odds ratios with 95% confidence intervals) between psychiatric symptom domains in S1 interview and recent exposure to violence at follow-up

All estimates take account of clustering of responses within households and household non-response, and are based on 998 cases with complete data on all modelled variables. For each outcome, we present three specifications of psychiatric symptom domain – a binary outcome (any psychiatric symptom domain endorsed, compared with no psychiatric symptom domain endorsed), categorisations into 0, 1–2 and 3–4 symptom domains endorsed, and a linear model based on number of symptom domains endorsed.

a Model I is adjusted only for lifetime violence exposure at baseline.

b Model II is further adjusted for age (continuous), gender, ethnicity and unemployment.

c Model III is further adjusted for hazardous alcohol use and recent drug use.

d Model IV is further adjusted for perpetration.

e Reference group for these comparisons is the group with no psychiatric symptom domains.

f Likelihood ratio tests for significance of linear trend in number of symptom domains was <0.001 in all fully adjusted models for witnessed violence, victimisation and any violence exposure.

In order to examine the influence of important potential confounders in more depth, we repeated the analyses shown in Table 3 stratifying by perpetration status, sex and history of service use (Table 4). Table 5 presents estimates for the association between any psychiatric symptom domain and any subsequent victimisation, stratified by perpetration history, gender and mental health service use. Endorsing any psychiatric symptom domain remained prospectively associated with overall victimisation both in those with and without a history of perpetration, and among women and men, however the association among women was greater in magnitude, and the confidence interval for the final estimate in men crossed null. The association between any psychiatric symptom domain and later victimisation was greater among those with a history of service use than those without, where it remained, but was statistically significant in both groups. Statistical evidence for a linear relationship between number of psychiatric symptom domains and odds of later victimisation was evident both in those with and without a history of service use, and among non-perpetrators, in men and in women. However, fully adjusted estimates for perpetrators no longer produced statistical evidence of an association.

Table 5. Estimates for the association between psychiatric symptom domains endorsed and any later violence exposure, limited to those with and without a lifetime history of perpetration, to those with and without a history of mental health service use, and to men and women

All models are based on 998 participants with complete data for the modelled variables and weighted for household non-response at both waves. Models are numbered as in Table 3. aReference group is no symptom domain endorsed. bp = 0.006, cp = 0.105, dp = 0.018, ep = 0.035, fp = 0.064, gp = 0.028.

Discussion

Summary of findings

In a sample of Southeast London household residents, psychiatric symptoms, ascertained based on endorsement of epidemiological screening tools for different domains of psychopathology, were prospectively associated with later victimisation over a 3-year period, both overall, by being physically victimised, and as a witness, compared with those without symptoms at baseline. An increasing number of symptom domains predicted greater odds of victimisation over time. The association was not limited to perpetrators of violence, or to those without a history of mental health service use. Although associations between endorsing any psychiatric symptom domain and later victimisation were observed in both men and women, estimates for women were of greater magnitude.

What this study adds

We suggest that our study significantly strengthens a limited literature (Silver et al., Reference Silver, Arseneault, Langley, Caspi and Moffitt2005; Hart et al., Reference Hart, de Vet, Moran, Hatch and Dean2012) pointing to an association between a range of psychiatric symptoms and later victimisation, confirming this in a longitudinal population-based sample. In our study, recent (12-month) victimisation at follow-up was reported by 9.6% of people reporting any psychiatric symptom domain, and 4.7% in those without, comparing favourably with other estimates (Maniglio, Reference Maniglio2009). The study also contributes by using data drawn from a representative sample of household residents who were not using mental health services, and includes information on witnessed violence as well as violent victimisation. Our evidence that psychiatric symptoms were associated with later witnessed violence, together with evidence of the psychiatric sequelae of witnessed violence (Fitzpatrick and Boldizar, Reference Fitzpatrick and Boldizar1993), implies a bi-directional relationship between witnessed violence and psychiatric symptoms that warrants further examination. In addition to adjusting for gender in regression models in line with previous work (Silver et al., Reference Silver, Arseneault, Langley, Caspi and Moffitt2005; Hart et al., Reference Hart, de Vet, Moran, Hatch and Dean2012), we found evidence for a stronger association among women in stratified analyses, and evidence for association even in those not using mental healthcare, as well as perpetrators of violence.

Previous literature

The psychiatric consequences of victimisation are well known, and include psychosis (Varese et al., Reference Varese, Smeets, Drukker, Lieverse, Lataster, Viechtbauer, Read, Van Os and Bentall2012), depression (Dorrington et al., Reference Dorrington, Zavos, Ball, McGuffin, Rijsdijk, Siribaddana, Sumathipala and Hotopf2014) and PTSD (Liu et al., Reference Liu, Petukhova, Sampson, Aguilar-Gaxiola, Alonso, Andrade, Bromet, De Girolamo, Haro, Hinkov, Kawakami, Koenen, Kovess-Masfety, Lee, Medina-Mora, Navarro-Mateu, O'Neill, Piazza, Posada-Villa, Scott, Shahly, Stein, Ten Have, Torres, Gureje, Zaslavsky, Kessler, Al-Hamzawi, Al-Kaisy, Benjet, Borges, Bruffaerts, Bunting, De Almeida, Cardoso, Chatterji, Cia, Degenhardt, De Jonge, Demyttenaere, Fayyad, Florescu, He, Hu, Huang, Karam, Karam, Kiejna, Lepine, Levinson, McGrath, Moskalewicz, Pennell, Slade, Stagnaro, Viana, Whiteford, Williams and Wojtyniak2017). Previous evidence on increased victimisation in people with psychiatric disorders have been based on cross-sectional and case–control designs (Kamperman et al., Reference Kamperman, Henrichs, Bogaerts, Lesaffre, Wierdsma, Ghauharali, Swildens, Nijssen, van der Gaag, Theunissen, Delespaul, van Weeghel, van Busschbach, Kroon, Teplin, van de Mheen and Mulder2014; Rodway et al., Reference Rodway, Flynn, While, Rahman, Kapur, Appleby and Shaw2014; Tsigebrhan et al., Reference Tsigebrhan, Shibre, Medhin, Fekadu and Hanlon2014; Meijwaard et al., Reference Meijwaard, Kikkert, De Mooij, Lommerse, Peen, Schoevers, Van, De Wildt, Bockting and Dekker2015) – we demonstrate this association in prospective data. Moreover, previous studies have been confined to clinical populations with severe mental disorder (Bebbington et al., Reference Bebbington, Meltzer, Brugha, Farrell, Jenkins, Ceresa and Lewis2000; Alonso et al., Reference Alonso, Codony, Kovess, Angermeyer, Katz, Haro, De Girolamo, De Graaf, Demyttenaere and Vilagut2007; Howard et al., Reference Howard, Trevillion, Khalifeh, Woodall, Agnew-Davies and Feder2010), have not directly sampled the general population for controls (Brennan et al., Reference Brennan, Moore and Shepherd2010; Rodway et al., Reference Rodway, Flynn, While, Rahman, Kapur, Appleby and Shaw2014), have been cross-sectional in design (Sturup et al., Reference Sturup, Sorman, Lindqvist and Kristiansson2011; Desmarais et al., Reference Desmarais, Van Dorn, Johnson, Grimm, Douglas and Swartz2014; Kamperman et al., Reference Kamperman, Henrichs, Bogaerts, Lesaffre, Wierdsma, Ghauharali, Swildens, Nijssen, van der Gaag, Theunissen, Delespaul, van Weeghel, van Busschbach, Kroon, Teplin, van de Mheen and Mulder2014; Tsigebrhan et al., Reference Tsigebrhan, Shibre, Medhin, Fekadu and Hanlon2014; Meijwaard et al., Reference Meijwaard, Kikkert, De Mooij, Lommerse, Peen, Schoevers, Van, De Wildt, Bockting and Dekker2015), have not examined the association of psychiatric symptoms with witnessing violence and have not accounted for perpetration history (Stickley and Carlson, Reference Stickley and Carlson2010; Desmarais et al., Reference Desmarais, Van Dorn, Johnson, Grimm, Douglas and Swartz2014; Meijwaard et al., Reference Meijwaard, Kikkert, De Mooij, Lommerse, Peen, Schoevers, Van, De Wildt, Bockting and Dekker2015). Hart et al. found prospective association between a single scale reflecting psychiatric morbidity and violent experiences, but examined only individuals remaining in the study at age 46 (Hart et al., Reference Hart, de Vet, Moran, Hatch and Dean2012), which is not the peak age for victimisation experiences. They did not distinguish between different psychiatric disorders in their data, lacked information on perpetration and did not account for victimisation occurring prior to the development of psychiatric disorder. Honings et al. (Reference Honings, Drukker, ten Have, de Graaf, van Dorsselaer and van Os2017) reported evidence of bi-directional associations between psychiatric symptoms and victimisation based on prospective data from the Netherlands, however their analysis was limited to psychotic symptoms, and did not directly assess perpetration of violence (instead adjusting for history of overall arrest).

Strengths and limitations

This study was longitudinal and based on a randomly selected baseline sample. Detailed measurements of psychopathology were gathered, and we used conservative cut-offs to identify individuals in whom we could be reasonably confident there were clinically relevant symptoms in the various domains. On the other hand, there was attrition, which reduced the precision of estimates and limited study power to estimate associations with specific symptom domains in detail, as planned. People with psychiatric symptoms might have been more or less liable to report victimisation compared with people without psychiatric symptoms, leading to misclassification and resulting over or underestimation of the main association. However, studies indicate that the recall of victimisation events is generally reliable (Schneider, Reference Schneider1981; Goodman et al., Reference Goodman, Thompson, Weinfurt, Corl, Acker, Mueser and Rosenberg1999), and our investigation of victimisation events focused on events in the previous year. Information on perpetration was only available at one time point. We did not have information on the number and intensity of violent experiences, which is a pressing need in public health research (Krieger, Reference Krieger2012; Walby et al., Reference Walby, Towers, Balderston, Corradi, Francis, Heiskanen, Helweg-Larsen, Mergaert, Olive and Palmer2017). Because our two waves of data collection took place within 3 years of each other, we were unable to assess longer term consequences of psychiatric symptoms in these data, in contrast to some previous studies (Silver et al., Reference Silver, Arseneault, Langley, Caspi and Moffitt2005; Hart et al., Reference Hart, de Vet, Moran, Hatch and Dean2012). Although we adjusted estimates for prior victimisation in order to limit confounding, it is also possible that we overadjusted our estimates in this study (Glymour et al., Reference Glymour, Weuve, Berkman, Kawachi and Robins2005). Finally, baseline survey respondents lost to follow-up tended to be younger, male, unemployed and more commonly of BME ethnicity compared with those whose were successfully followed up, leaving open the possibility of selection bias. Given that younger age, male gender and BME ethnicity were associated with victimisation in this study, consistent with other evidence (Brennan et al., Reference Brennan, Moore and Shepherd2010), it is likely that bias introduced into our estimates through biased attrition deviated our estimates towards, rather than away from the null. Although we were able to examine a wider range of psychiatric symptoms than previous studies, it was not possible to include all psychiatric symptoms; in principle, other symptom categories, not measured in this study, could display opposite associations with later victimisation. We would caution against generalizing these results to psychiatric symptoms not measured in this study. This analysis was based on two waves of a household survey, with some loss to follow-up attrition between the waves. We did not have information on the precise timing of offences, or time of loss to follow-up, and our analysis is therefore based only on individuals on whom data were collected in the second wave.

Although our results suggest that psychiatric symptoms may increase liability to subsequent victimisation, the exact explanations remain unclear. Our findings may, for example, be consistent with a ‘routine activities’ model of victimisation where violent experiences arise from the convergence of motive, opportunity and lack of adequate safeguards against violence (Miethe et al., Reference Miethe, Stafford and Long1987). Psychiatric disorders are socially and culturally stigmatising, which might lead to increasing conflict in daily life (Cohen and Felson, Reference Cohen and Felson1979; Link et al., Reference Link, Phelan, Bresnahan, Stueve and Pescosolido1999), however our study had no information on the perpetrators of violence experienced by survey respondents. Psychiatric symptoms not measured in this study, such as irritability, social withdrawal or disorganised behaviour, could increase risk of attack from other people (Brekke et al., Reference Brekke, Prindle, Bae and Long2001; Walsh et al., Reference Walsh, Moran, Scott, McKenzie, Burns, Creed, Tyrer, Murray and Fahy2003; Fortugno et al., Reference Fortugno, Katsakou, Bremner, Kiejna, Kjellin, Nawka, Raboch, Kallert and Priebe2013; de Mooij et al., Reference de Mooij, Kikkert, Lommerse, Peen, Meijwaard, Theunissen, Duurkoop, Goudriaan, Van and Beekman2015). One study has suggested that victimisation risk in people with psychiatric disorder is related to the experience of financial stress (Honkonen et al., Reference Honkonen, Henriksson, Koivisto, Stengard and Salokangas2004), on which information was also unavailable. Hazardous use of substances and alcohol are other potential mediators (Schomerus et al., Reference Schomerus, Heider, Angermeyer, Bebbington, Azorin, Brugha and Toumi2008; Dolan et al., Reference Dolan, Castle and McGregor2012), which is consistent with the attenuation of estimates seen upon adjustment in the present study. Finally, there is strong evidence that repeated victimisation experiences tend to cluster in individuals over time (Goodman et al., Reference Goodman, Salyers, Mueser, Rosenberg, Swartz, Essock, Osher, Butterfield and Swanson2001; Cotter et al., Reference Cotter, Drake and Yung2016; Pridemore and Berg, Reference Pridemore and Berg2017); in a prospective study of people with psychosis, reporting assault was associated with prior victimisation, early illness onset, infrequent family contact and personality difficulties, implying that early life adversity might play a role in patterning social interactions over the life course, and result in the emergence of victimisation, enduring dysfunctional personality traits, and psychosis (Dean et al., Reference Dean, Moran, Fahy, Tyrer, Leese, Creed, Burns, Murray and Walsh2007). This evidence implies the presence of underlying factors driving victimisation in particular individuals, for whom diagnosis and treatment may have a limited impact. We adjusted estimates for prior instances of violence exposure as a way of accounting not only for the direct effects of prior violence exposure on later violence (through aberrant coping, e.g.), but also for sociodemographic and other risk factors for the earlier exposure to violence. The suggestion from our results that the association between psychiatric symptoms and later victimisation is greater among women requires further investigation.

Conclusions

We present the first prospective evidence that people with common psychiatric symptoms, and higher number of symptoms, have greater vulnerability to victimisation than those without symptoms, not limited to those with a history of perpetrating violence, those using services or those with prior exposure to violence. Lifestyle factors such as hazardous alcohol use and drug use, as well as perpetration history, appear to account for some of this association. There is already evidence that people with psychiatric disorders are systematically excluded from the benefits of public health interventions addressing, for example, smoking (Szatkowski and McNeill, Reference Szatkowski and McNeill2014) and healthy eating (Cabassa et al., Reference Cabassa, Ezell and Lewis-Fernández2010). We tentatively suggest that this might also be true for violence prevention programmes, safer neighbourhood interventions and policing. Clinicians and health services have a role in maintaining the personal safety of people with mental illness (Manthorpe and Martineau, Reference Manthorpe and Martineau2010). Clinicians should be mindful of the impact of psychiatric symptoms on vulnerability to victimisation, including among those with common psychiatric symptoms, such as depression, and among those who are not considered at risk of perpetrating violence.

Acknowledgements

The authors acknowledge the assistance of David Pernet, Shirlee MacCrimmon and the SELCoH team in the completion of this research work.

Authors’ contributions

MH, SLH and members of the SELCoH team were responsible for data acquisition. VB was responsible for analysis and interpretation, and for writing up data and drafting the paper, under supervision from SLH, MH and JHM. VB was responsible for study conception and design, and KD provided advice about interpretation and preparation of the paper. MH and SLH provided overall guidance and leadership to the study. All authors read and approved the final submitted version. MH and JM are joint guarantors for the study.

Financial support

This work was funded by a Wellcome Trust Clinical Research Training Fellowship (101681/Z/13/Z) awarded to Dr Bhavsar. This work was also supported by the Economic and Social Research Council (grant number RES-177-25-0015). This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The funder of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. The corresponding author had full access to all the data and final responsibility for the decision to submit for publication.

Conflict of interest

All authors declare that they have no competing interests in relation to this study.

Ethical standards

Ethical approval for SELCoH-1 was received from the King's College London Research Ethics Committee for non-clinical research populations (reference CREC/07/08-152) and for SELCoH-2 was received from the King's College London Psychiatry, Nursing and Midwifery Research Ethics Committee (PNM/10/11-106).

Availability of data and materials

The data that support the findings of this study are available from Professor Matthew Hotopf but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Professor Matthew Hotopf.

Footnotes

*

Joint senior authors

References

Acierno, R, Brady, K, Gray, M, Kilpatrick, DG, Resnick, H and Best, CL (2002) Psychopathology following interpersonal violence: a comparison of risk factors in older and younger adults. Journal of Clinical Geropsychology 8, 1323.Google Scholar
Alonso, J, Codony, M, Kovess, V, Angermeyer, MC, Katz, SJ, Haro, JM, De Girolamo, G, De Graaf, R, Demyttenaere, K and Vilagut, G (2007) Population level of unmet need for mental healthcare in Europe. The British Journal of Psychiatry 190, 299306.Google Scholar
Bebbington, P and Nayani, T (1995) The psychosis screening questionnaire. International Journal of Methods in Psychiatric Research 5, 1119.Google Scholar
Bebbington, P, Meltzer, H, Brugha, T, Farrell, M, Jenkins, R, Ceresa, C and Lewis, G (2000) Unequal access and unmet need: neurotic disorders and the use of primary care services. Psychological Medicine 30, 13591367.Google Scholar
Brekke, JS, Prindle, C, Bae, SW and Long, JD (2001) Risks for individuals with schizophrenia who are living in the community. Psychiatric Services 52, 13581366.Google Scholar
Brennan, IR, Moore, SC and Shepherd, JP (2010) Risk factors for violent victimisation and injury from six years of the British Crime Survey. International Review of Victimology 17, 209229.Google Scholar
Cabassa, LJ, Ezell, JM and Lewis-Fernández, R (2010) Lifestyle interventions for adults with serious mental illness: a systematic literature review. Psychiatric Services 61, 774782.Google Scholar
Choe, JY, Teplin, LA and Abram, KM (2008) Perpetration of violence, violent victimization, and severe mental illness: balancing public health concerns. Psychiatric Services 59, 153164.Google Scholar
Cohen, LE and Felson, M (1979) Social change and crime rate trends: a routine activity approach. American Sociological Review 44, 588608.Google Scholar
Cotter, J, Drake, RJ and Yung, AR (2016) Adulthood revictimization: looking beyond childhood trauma. Acta Psychiatrica Scandinavica 134, 368.Google Scholar
Dansky, BS, Saladin, ME, Brady, KT, Kilpatrick, DG and Resnick, HS (1995) Prevalence of victimization and posttraumatic stress disorder among women with substance use disorders: comparison of telephone and in-person assessment samples. International Journal of the Addictions 30, 10791099.Google Scholar
de Mooij, LD, Kikkert, M, Lommerse, NM, Peen, J, Meijwaard, SC, Theunissen, J, Duurkoop, PW, Goudriaan, AE, Van, HL and Beekman, AT (2015) Victimisation in adults with severe mental illness: prevalence and risk factors. The British Journal of Psychiatry 207, 515522.Google Scholar
Dean, K, Moran, P, Fahy, T, Tyrer, P, Leese, M, Creed, F, Burns, T, Murray, R and Walsh, E (2007) Predictors of violent victimization amongst those with psychosis. Acta Psychiatrica Scandinavica 116, 345353.Google Scholar
Desmarais, SL, Van Dorn, RA, Johnson, KL, Grimm, KJ, Douglas, KS and Swartz, MS (2014) Community violence perpetration and victimization among adults with mental illnesses. American Journal of Public Health 104, 23422349.Google Scholar
Dolan, MC, Castle, D and McGregor, K (2012) Criminally violent victimisation in schizophrenia spectrum disorders: the relationship to symptoms and substance abuse. BMC Public Health 12, 445.Google Scholar
Dorrington, S, Zavos, H, Ball, H, McGuffin, P, Rijsdijk, F, Siribaddana, S, Sumathipala, A and Hotopf, M (2014) Trauma, post-traumatic stress disorder and psychiatric disorders in a middle-income setting: prevalence and comorbidity. The British Journal of Psychiatry 205, 383.Google Scholar
Fitzpatrick, KM and Boldizar, JP (1993) The prevalence and consequences of exposure to violence among African-American youth. Journal of the American Academy of Child & Adolescent Psychiatry 32, 424430.Google Scholar
Fok, M, Hotopf, M, Stewart, R, Hatch, S, Hayes, R and Moran, P (2014) Personality disorder and self-rated health: a population-based cross-sectional survey. Journal of Personality Disorders 28, 319333.Google Scholar
Fortugno, F, Katsakou, C, Bremner, S, Kiejna, A, Kjellin, L, Nawka, P, Raboch, J, Kallert, T and Priebe, S (2013) Symptoms associated with victimization in patients with schizophrenia and related disorders. PLoS ONE [Electronic Resource] 8, e58142.Google Scholar
Frissa, S, Hatch, SL, Gazard, B, Fear, NT and Hotopf, M and team, S. s. (2013). Trauma and current symptoms of PTSD in a South East London community. Social Psychiatry and Psychiatric Epidemiology 48, 11991209.Google Scholar
Glymour, MM, Weuve, J, Berkman, LF, Kawachi, I and Robins, JM (2005) When is baseline adjustment useful in analyses of change? An example with education and cognitive change. American Journal of Epidemiology 162, 267278.Google Scholar
Goodman, LA, Rosenberg, SD, Mueser, KT and Drake, RE (1997) Physical and sexual assault history in women with serious mental illness: prevalence, correlates, treatment, and future research directions. Schizophrenia Bulletin 23, 685696.Google Scholar
Goodman, LA, Thompson, KM, Weinfurt, K, Corl, S, Acker, P, Mueser, KT and Rosenberg, SD (1999) Reliability of reports of violent victimization and posttraumatic stress disorder among men and women with serious mental illness. Journal of Traumatic Stress 12, 587599.Google Scholar
Goodman, LA, Salyers, MP, Mueser, KT, Rosenberg, SD, Swartz, M, Essock, SM, Osher, FC, Butterfield, MI and Swanson, J (2001) Recent victimization in women and men with severe mental illness: prevalence and correlates. Journal of Traumatic Stress 14, 615632.Google Scholar
Greenland, S, Daniel, R and Pearce, N (2016) Outcome modelling strategies in epidemiology: traditional methods and basic alternatives. International Journal of Epidemiology 45, 565575.Google Scholar
Hart, C, de Vet, R, Moran, P, Hatch, SL and Dean, K (2012) A UK population-based study of the relationship between mental disorder and victimisation. Social Psychiatry and Psychiatric Epidemiology 47, 15811590.Google Scholar
Hatch, SL, Harvey, SB and Maughan, B (2010) A developmental-contextual approach to understanding mental health and well-being in early adulthood. Social Science & Medicine 70, 261268.Google Scholar
Hatch, SL, Frissa, S, Verdecchia, M, Stewart, R, Fear, NT, Reichenberg, A, Morgan, C, Kankulu, B, Clark, J and Gazard, B (2011) Identifying socio-demographic and socioeconomic determinants of health inequalities in a diverse London community: the South East London Community Health (SELCoH) study. BMC Public Health 11, 861.Google Scholar
Hatch, S, Gazard, B, Williams, D, Frissa, S, Goodwin, L, Hotopf, M and Team, SS (2016) Discrimination and common mental disorder among migrant and ethnic groups: findings from a South East London Community sample. Social Psychiatry and Psychiatric Epidemiology 51, 689701.Google Scholar
Hedtke, KA, Ruggiero, KJ, Fitzgerald, MM, Zinzow, HM, Saunders, BE, Resnick, HS and Kilpatrick, DG (2008) A longitudinal investigation of interpersonal violence in relation to mental health and substance use. Journal of Consulting and Clinical Psychology 76, 633.Google Scholar
Hiday, VA, Swartz, MS, Swanson, JW, Borum, R and Wagner, HR (1999) Criminal victimization of persons with severe mental illness. Psychiatric Services 50, 6268.Google Scholar
Hodgins, S, Lincoln, T and Mak, T (2009) Experiences of victimisation and depression are associated with community functioning among men with schizophrenia. Social Psychiatry and Psychiatric Epidemiology 44, 448457.Google Scholar
Honings, S, Drukker, M, ten Have, M, de Graaf, R, van Dorsselaer, S and van Os, J (2017) The interplay of psychosis and victimisation across the life course: a prospective study in the general population. Social Psychiatry and Psychiatric Epidemiology 52, 13631374.Google Scholar
Honkonen, T, Henriksson, M, Koivisto, A-M, Stengard, E and Salokangas, RK (2004) Violent victimization in schizophrenia. Social Psychiatry and Psychiatric Epidemiology 39, 606612.Google Scholar
Howard, L, Trevillion, K, Khalifeh, H, Woodall, A, Agnew-Davies, R and Feder, G (2010) Domestic violence and severe psychiatric disorders: prevalence and interventions. Psychological Medicine 40, 881893.Google Scholar
Johnson, KL, Desmarais, SL, Dorn, RAV and Grimm, KJ (2015) A typology of community violence perpetration and victimization among adults with mental illnesses. Journal of Interpersonal Violence 30, 522540.Google Scholar
Johnson, KL, Desmarais, SL, Tueller, SJ, Grimm, KJ, Swartz, MS and Van Dorn, RA (2016) A longitudinal analysis of the overlap between violence and victimization among adults with mental illnesses. Psychiatry Research 246, 203210.Google Scholar
Kadra, G, Dean, K, Hotopf, M and Hatch, SL (2014) Investigating exposure to violence and mental health in a diverse urban community sample: data from the South East London Community Health (SELCoH) survey. PLoS ONE 9, e93660.Google Scholar
Kamperman, AM, Henrichs, J, Bogaerts, S, Lesaffre, EM, Wierdsma, AI, Ghauharali, RR, Swildens, W, Nijssen, Y, van der Gaag, M, Theunissen, JR, Delespaul, PA, van Weeghel, J, van Busschbach, JT, Kroon, H, Teplin, LA, van de Mheen, D and Mulder, CL (2014) Criminal victimisation in people with severe mental illness: a multi-site prevalence and incidence survey in the Netherlands. PLoS ONE [Electronic Resource] 9, e91029.Google Scholar
Kershaw, C, Nicholas, S and Walker, A (2008) Crime in England and Wales 2007/08: findings from the British Crime Survey and police recorded crime. Home Office Statistical Bulletin 7, 4445.Google Scholar
Kessler, RC, Sonnega, A, Bromet, E, Hughes, M and Nelson, CB (1995) Posttraumatic stress disorder in the national comorbidity survey. Archives of General Psychiatry 52, 10481060.Google Scholar
Kessler, RC, Sonnega, A, Bromet, E, Hughes, M, Nelson, CB and Breslau, N (1999) Epidemiological risk factors for trauma and PTSD. In (Rachel Yehuda, ed.) Risk Factors for Posttraumatic Stress Disorder. Arlington, VA, USA: American Psychiatric Association, pp. 2359.Google Scholar
Khalifeh, H, Johnson, S, Howard, LM, Borschmann, R, Osborn, D, Dean, K, Hart, C, Hogg, J and Moran, P (2015) Violent and non-violent crime against adults with severe mental illness. British Journal of Psychiatry 206, 275282.Google Scholar
Krieger, N (2012) Methods for the scientific study of discrimination and health: an ecosocial approach. American Journal of Public Health 102, 936944.Google Scholar
Krug, EG, Mercy, JA, Dahlberg, LL and Zwi, AB (2002) The world report on violence and health. The Lancet 360, 10831088.Google Scholar
Lehman, AF and Linn, LS (1984) Crimes against discharged mental patients. American Journal of Psychiatry 141, 271274.Google Scholar
Lewis, G and Pelosi, A (1990). Manual of the Revised Clinical Interview Schedule (CIS-R). London: Institute of Psychiatry.Google Scholar
Link, BG, Phelan, JC, Bresnahan, M, Stueve, A and Pescosolido, BA (1999) Public conceptions of mental illness: labels, causes, dangerousness, and social distance. American Journal of Public Health 89, 13281333.Google Scholar
Liu, H, Petukhova, MV, Sampson, NA, Aguilar-Gaxiola, S, Alonso, J, Andrade, LH, Bromet, EJ, De Girolamo, G, Haro, JM, Hinkov, H, Kawakami, N, Koenen, KC, Kovess-Masfety, V, Lee, S, Medina-Mora, ME, Navarro-Mateu, F, O'Neill, S, Piazza, M, Posada-Villa, J, Scott, KM, Shahly, V, Stein, DJ, Ten Have, M, Torres, Y, Gureje, O, Zaslavsky, AM, Kessler, RC, Al-Hamzawi, A, Al-Kaisy, MS, Benjet, C, Borges, G, Bruffaerts, R, Bunting, B, De Almeida, JMC, Cardoso, G, Chatterji, S, Cia, AH, Degenhardt, L, De Jonge, P, Demyttenaere, K, Fayyad, J, Florescu, S, He, Y, Hu, CY, Huang, Y, Karam, AN, Karam, EG, Kiejna, A, Lepine, JP, Levinson, D, McGrath, J, Moskalewicz, J, Pennell, BE, Slade, T, Stagnaro, JC, Viana, MC, Whiteford, H, Williams, DR and Wojtyniak, B (2017) Association of DSM-IV posttraumatic stress disorder with traumatic experience type and history in the World Health Organization World Mental Health surveys. JAMA Psychiatry 74, 270281.Google Scholar
Maniglio, R (2009) Severe mental illness and criminal victimization: a systematic review. Acta Psychiatrica Scandinavica 119, 180191.Google Scholar
Manthorpe, J and Martineau, S (2010) Serious case reviews in adult safeguarding in England: an analysis of a sample of reports. British Journal of Social Work 41, 224241.Google Scholar
McDonald, CC and Richmond, TR (2008) The relationship between community violence exposure and mental health symptoms in urban adolescents. Journal of Psychiatric and Mental Health Nursing 15, 833849.Google Scholar
Meijwaard, SC, Kikkert, M, De Mooij, LD, Lommerse, NM, Peen, J, Schoevers, RA, Van, R, De Wildt, W, Bockting, CL and Dekker, JJ (2015). Risk of criminal victimisation in outpatients with common mental health disorders. PLoS ONE 10, e0128508.Google Scholar
Miethe, TD, Stafford, MC and Long, JS (1987) Social differentiation in criminal victimization: a test of routine activities/lifestyle theories. American Sociological Review 184194.Google Scholar
Moran, P, Leese, M, Lee, T, Thornicroft, G and Mann, A (2003) Standardised Assessment of Personality – Abbreviated Scale (SAPAS): preliminary validation of a brief screen for personality disorder. The British Journal of Psychiatry 183, 228232.Google Scholar
Morgan, C, Reininghaus, U, Reichenberg, A, Frissa, S, Hotopf, M and Hatch, SL (2014) Adversity, cannabis use and psychotic experiences: evidence of cumulative and synergistic effects. The British Journal of Psychiatry 204, 346353.Google Scholar
Neria, Y, Bromet, EJ, Carlson, GA and Naz, B (2005) Assaultive trauma and illness course in psychotic bipolar disorder: findings from the Suffolk county mental health project. Acta Psychiatrica Scandinavica 111, 380383.Google Scholar
Pearce, N and Richiardi, L (2014) Commentary: three worlds collide: Berkson's bias, selection bias and collider bias. International Journal of Epidemiology 43, 521524.Google Scholar
Pridemore, WA and Berg, MT (2017) What is past is prologue: a population-based case-control study of repeat victimization, premature mortality, and homicide. Aggressive Behavior 43, 176189.Google Scholar
Prins, A, Ouimette, P, Kimerling, R, Camerond, RP, Hugelshofer, DS, Shaw-Hegwer, J, Thrailkill, A, Gusman, FD and Sheikh, JI (2003) The primary care PTSD screen (PC PTSD): development and operating characteristics. Primary Care Psychiatry 9, 914.Google Scholar
Resnick, HS, Acierno, R and Kilpatrick, DG (1997) Health impact of interpersonal violence. 2: medical and mental health outcomes. Behavioral Medicine 23, 6578.Google Scholar
Rodway, C, Flynn, S, While, D, Rahman, MS, Kapur, N, Appleby, L and Shaw, J (2014) Patients with mental illness as victims of homicide: a national consecutive case series. The Lancet Psychiatry 1, 129134.Google Scholar
Saunders, JB, Aasland, OG, Babor, TF, de la Fuente, JR and Grant, M (1993) Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction 88, 791804.Google Scholar
Schneider, AL (1981) Methodological problems in victim surveys and their implications for research in victimology. The Journal of Criminal Law and Criminology (1973-) 72, 818838.Google Scholar
Schomerus, G, Heider, D, Angermeyer, MC, Bebbington, PE, Azorin, JM, Brugha, T and Toumi, M (2008) Urban residence, victimhood and the appraisal of personal safety in people with schizophrenia: results from the European Schizophrenia Cohort (EuroSC). Psychological Medicine 38, 591597.Google Scholar
Silver, E, Arseneault, L, Langley, J, Caspi, A and Moffitt, TE (2005) Mental disorder and violent victimization in a total birth cohort. American Journal of Public Health 95, 20152021.Google Scholar
StataCorp (2014) Stata Statistical Software: Release 14. Special Edition.Google Scholar
Stickley, A and Carlson, P (2010) Factors associated with non-lethal violent victimization in Sweden in 2004-2007. Scandinavian Journal of Public Health 38, 404410.Google Scholar
Sturup, J, Sorman, K, Lindqvist, P and Kristiansson, M (2011) Violent victimisation of psychiatric patients: a Swedish case–control study. Social Psychiatry and Psychiatric Epidemiology 46, 2934.Google Scholar
Szatkowski, L and McNeill, A (2014) Diverging trends in smoking behaviors according to mental health Status. Nicotine & Tobacco Research 17, 356360.Google Scholar
Tsigebrhan, R, Shibre, T, Medhin, G, Fekadu, A and Hanlon, C (2014) Violence and violent victimization in people with severe mental illness in a rural low-income country setting: a comparative cross-sectional community study. Schizophrenia Research 152, 275282.Google Scholar
Varese, F, Smeets, F, Drukker, M, Lieverse, R, Lataster, T, Viechtbauer, W, Read, J, Van Os, J and Bentall, RP (2012) Childhood adversities increase the risk of psychosis: a meta-analysis of patient-control, prospective-and cross-sectional cohort studies. Schizophrenia Bulletin 38, 661671.Google Scholar
Walby, S, Towers, J, Balderston, S, Corradi, C, Francis, B, Heiskanen, M, Helweg-Larsen, K, Mergaert, L, Olive, P and Palmer, E (2017). The Concept and Measurement of Violence Against Women and Men. London: Policy Press.Google Scholar
Walsh, E, Moran, P, Scott, C, McKenzie, K, Burns, T, Creed, F, Tyrer, P, Murray, RM and Fahy, T (2003) Prevalence of violent victimisation in severe mental illness. British Journal of Psychiatry 183, 233238.Google Scholar
Wohlfarth, T, Winkel, FW, Ybema, JF and van den Brink, W (2001) The relationship between socio-economic inequality and criminal victimisation: a prospective study. Social Psychiatry and Psychiatric Epidemiology 36, 361370.Google Scholar
Figure 0

Table 1. Descriptive data on included participants classified by presence of any psychiatric symptom domain (n = 998)

Figure 1

Table 2. Descriptive data on overall sample, and included participants

Figure 2

Table 3. Univariate prospective associations (odds ratios with 95% confidence intervals) with each type of violence exposure in the final sample (n = 998)

Figure 3

Table 4. Partial and fully adjusted logistic regression models for the association (odds ratios with 95% confidence intervals) between psychiatric symptom domains in S1 interview and recent exposure to violence at follow-up

Figure 4

Table 5. Estimates for the association between psychiatric symptom domains endorsed and any later violence exposure, limited to those with and without a lifetime history of perpetration, to those with and without a history of mental health service use, and to men and women