Risk of criminal victimisation in outpatients with common mental health disorders

Crime victimisation is a serious problem in psychiatric patients. However, research has focused on patients with severe mental illness and few studies exist that address victimisation in other outpatient groups, such as patients with depression. Due to large differences in methodology of the studies that address crime victimisation, a comparison of prevalence between psychiatric diagnostic groups is hard to make. Objectives of this study were to determine and compare one-year prevalence of violent and non-violent criminal victimisation among outpatients from different diagnostic psychiatric groups and to examine prevalence differences with the general population.Criminal victimisation prevalence was measured in 300 outpatients living in Amsterdam, The Netherlands. Face-to-face interviews were conducted with outpatients with depressive disorder (n = 102), substance use disorder (SUD, n = 106) and severe mental illness (SMI, n = 92) using a National Crime Victimisation Survey, and compared with a matched general population sample (n = 10865).Of all outpatients, 61% reported experiencing some kind of victimisation over the past year; 33% reported violent victimisation (3.5 times more than the general population) and 36% reported property crimes (1.2 times more than the general population). Outpatients with depression (67%) and SUD (76%) were victimised more often than SMI outpatients (39%). Younger age and hostile behaviour were associated with violent victimisation, while being male and living alone were associated with non-violent victimisation. Moreover, SUD was associated with both violent and non-violent victimisation.Outpatients with depression, SUD, and SMI are at increased risk of victimisation compared to the general population. Furthermore, our results indicate that victimisation of violent and non-violent crimes is more common in outpatients with depression and SUD than in outpatients with SMI living independently in the community

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Crime victimisation is a serious problem in psychiatric patients. However, research has focused on patients with severe mental illness and few studies exist that address victimisation in other outpatient groups, such as patients with depression. Due to large differences in methodology of the studies that address crime victimisation, a comparison of prevalence between psychiatric diagnostic groups is hard to make. Objectives of this study were to determine and compare one-year prevalence of violent and non-violent criminal victimisation among outpatients from different diagnostic psychiatric groups and to examine prevalence differences with the general population.Criminal victimisation prevalence was measured in 300 outpatients living in Amsterdam, The Netherlands. Face-to-face interviews were conducted with outpatients with depressive disorder (n = 102), substance use disorder (SUD, n = 106) and severe mental illness (SMI, n = 92) using a National Crime Victimisation Survey, and compared with a matched general population sample (n = 10865).Of all outpatients, 61% reported experiencing some kind of victimisation over the past year; 33% reported violent victimisation (3.5 times more than the general population) and 36% reported property crimes (1.2 times more than the general population). Outpatients with depression (67%) and SUD (76%) were victimised more often than SMI outpatients (39%). Younger age and hostile behaviour were associated with violent victimisation, while being male and living alone were associated with non-violent victimisation. Moreover, SUD was associated with both violent and non-violent victimisation.Outpatients with depression, SUD, and SMI are at increased risk of victimisation compared to the general population. Furthermore, our results indicate that victimisation of violent and non-violent crimes is more common in outpatients with depression and SUD than in outpatients with SMI living independently in the community

Investigating the structure of craving using structural equation modeling in analysis of the obsessive-compulsive drinking scale: a multinational study

BACKGROUND: Currently, there is no agreement among researchers on the definition of craving and its underlying theoretical model. The Obsessive-Compulsive Drinking Scale (OCDS) seems to measure certain aspects of craving, but its theoretical basis remains unclear. The aim of this study was to investigate the structure of alcohol craving, using OCDS data. METHODS: OCDS data from four studies were pooled to obtain a large and heterogeneous sample of 505 participants. All participants were treatment-seeking alcoholics meeting DSM-IV criteria for alcohol dependence. The factor structures of the OCDS previously found were evaluated using confirmatory factor analyses. The goodness of fit of these solutions was compared with those of alternative causal models: an obsessive-compulsive disorder model, an inhibition model, and a cognitive-behavioral model. These alternative models were based on modern theories about craving and were tested in the OCDS data, using structural equation modeling. In this way, the current study replaced simple correlational analysis by a more sophisticated causal way of analyzing the underlying structure of the OCDS items. The best fitting model was selected by comparing the mean discrepancy between the implied and observed matrices of the models. RESULTS: The data showed that the previously reported factor structures had to be rejected. Also, the inhibition model and obsessive-compulsive disorder model did not fit the data. The cognitive-behavioral model showed encouraging fit. Optimizing strategies were applied to further improve the fit of this model, which resulted in a model with close fit to the data. CONCLUSIONS: The causal cognitive-behavioral model proved to be superior. It showed that the OCDS contains many items that do not represent the core concept of craving but instead are indicators for the consequences of craving. From this model, it seems that craving, in a narrow sense, can be reliably assessed with only five items of the OCD

Socio-demographics and substance use characteristics

<p>* p is a result of ANOVA for BPRS items and χ² test for categorical variables for differences between Depression, SUD & SMI.</p><p>^a Statistical analysis indicates a significant difference between the depression and the SUD group (asymptotic (2-sided) < 0.05).</p><p>^b Statistical analysis indicates a significant difference between the depression and the SMI group (asymptotic (2-sided) < 0.05).</p><p>^c Statistical analysis indicates a significant difference between the SUD and the SMI group (asymptotic (2-sided) < 0.05).</p><p>^d Cramer’s V</p><p>^e Eta squared (η²)</p><p>Socio-demographics and substance use characteristics</p

Results of univariate and multivariate hierarchical logistic regression analyses (method ENTER) for predictors of violent victimisation and victimisation of property crimes in psychiatric patients (n = 300).

<p>Step 1 Violent crimes: Omnibus test; Step P = 0.025, Model P = 0.025. Hosmer en Lemeshow; P = 0.901. Nagelkerke; R2 = 0.066.</p><p>Step 2 Violent crimes: Omnibus test; Step P = 0.265, Model P = 0.029. Hosmer en Lemeshow; P = 0.860. Nagelkerke; R2 = 0.078.</p><p>Step 1 Property crimes: Omnibus test; Step P = 0.002, Model P = 0.002. Hosmer en Lemeshow; P = 0.995. Nagelkerke; R2 = 0.090.</p><p>Step 2 Property crimes: Omnibus test; Step P = 0.014, Model P = 0.000. Hosmer en Lemeshow; P = 0.324. Nagelkerke; R2 = 0.181.</p><p>Results of univariate and multivariate hierarchical logistic regression analyses (method ENTER) for predictors of violent victimisation and victimisation of property crimes in psychiatric patients (n = 300).</p

Location and perpetrator of most recent violent victimisation incident (sexual offences, threats and assaults) for patients with depression, substance use disorder and severe mental illness.

<p>^‡ Public space includes: victimisation in streets, public transport, parks, parking lots and beaches.</p><p>* 3 missing values</p><p>Location and perpetrator of most recent violent victimisation incident (sexual offences, threats and assaults) for patients with depression, substance use disorder and severe mental illness.</p

Twelve month prevalence rates of victimisation of patients with depression, substance use disorder and severe mental illness, psychiatric patients overall and the general population.

<p>^a Pearson Chi-square indicates a significant difference between the depressive and the SUD group (asymptotic (2-sided) < 0.05).</p><p>^b Pearson Chi-square indicates a significant difference between the depression and the SMI group (asymptotic (2-sided) < 0.05).</p><p>^c Pearson Chi-square indicates a significant difference between the SUD and the SMI group (asymptotic (2-sided) < 0.05).</p><p>^d IVM data was weighed for gender, age, ethnicity, level of education and living area.</p><p>‡ Ratio of overall reported prevalence in psychiatric patients to prevalence reported by general population</p><p># The sample rate is 0; confidence bounds are not reported.</p><p>Twelve month prevalence rates of victimisation of patients with depression, substance use disorder and severe mental illness, psychiatric patients overall and the general population.</p