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

The predictive ability of the 313 variant–based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant

Abstract: Purpose: To evaluate the association between a previously published 313 variant–based breast cancer (BC) polygenic risk score (PRS313) and contralateral breast cancer (CBC) risk, in BRCA1 and BRCA2 pathogenic variant heterozygotes. Methods: We included women of European ancestry with a prevalent first primary invasive BC (BRCA1 = 6,591 with 1,402 prevalent CBC cases; BRCA2 = 4,208 with 647 prevalent CBC cases) from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), a large international retrospective series. Cox regression analysis was performed to assess the association between overall and ER-specific PRS313 and CBC risk. Results: For BRCA1 heterozygotes the estrogen receptor (ER)-negative PRS313 showed the largest association with CBC risk, hazard ratio (HR) per SD = 1.12, 95% confidence interval (CI) (1.06–1.18), C-index = 0.53; for BRCA2 heterozygotes, this was the ER-positive PRS313, HR = 1.15, 95% CI (1.07–1.25), C-index = 0.57. Adjusting for family history, age at diagnosis, treatment, or pathological characteristics for the first BC did not change association effect sizes. For women developing first BC < age 40 years, the cumulative PRS313 5th and 95th percentile 10-year CBC risks were 22% and 32% for BRCA1 and 13% and 23% for BRCA2 heterozygotes, respectively. Conclusion: The PRS313 can be used to refine individual CBC risks for BRCA1/2 heterozygotes of European ancestry, however the PRS313 needs to be considered in the context of a multifactorial risk model to evaluate whether it might influence clinical decision-making

Social inclusion and relationship satisfaction of patients with a severe mental illness

Background: Research suggests that patients with a severe mental illness (SMI) are among the most social excluded in society. However, comparisons of social network composition and relationship satisfaction between SMI patients and a control group are rare. Aims: Our aim was to compare differences in size, satisfaction and composition of the social network between patients with SMI and a control group. Potential sociodemographic and clinical risk factors in relation to social network size in SMI patients were explored. Methods: The sample consisted of a control group (N = 949) and SMI patients (N = 211) who were under treatment in Dutch mental health care institutions. In these groups, network size, relationship satisfaction, sociodemographic and clinical (patients only) characteristics were assessed. Results: Social network size was 2.5 times lower in SMI patients, which was also reflected in a lower relationship satisfaction. The composition of the social network of SMI patients differs from that of controls: patients’ network seems to consist of a smaller part of friends. Different risk factors were associated with the impoverishment of the social network of family, friends and acquaintances of patients with SMI. Conclusion: SMI patients have very small networks compared to controls. This may be a problem, given the ongoing emphasis on outpatient treatment of SMI patients and self-dependence. This outcome advocates for more attention to social isolation of SMI patients and involvement of family in the treatment and aftercare of SMI patients

Dying Too Soon: Excess Mortality in Severe Mental Illness

Aims: We aimed to identify baseline predictors of mortality in patients with a severe mental illness (SMI) over a 6-year period and to describe mortality rates as standardised mortality ratios (SMRs). We hypothesised that cardiovascular diseases, older age, cigarette smoking, more severe psychiatric symptoms and more severe psychotropic side effects, and alcohol or drug use were independent risk factors for mortality. Method: Medical examinations were conducted at baseline in a cohort of 322 SMI patients. SMRs were estimated after 6 years and an evaluation was made of the impact of a wide range of variables on survival time. Results: Almost 11% of the SMI patients had died at the end of the study period. All-cause SMRs were 4.51 (95% CI 3.07–5.95) for all SMI patients (4.89, 95% CI 2.97–6.80 for men, and 3.94, 95% CI 1.78–6.10 for women). Natural causes accounted for 86% of excess mortality and unnatural causes for 14%. Cardiovascular disease was a major contributor to this excess mortality. Multivariate Cox regression analyses showed that premature death was associated with a longer history of tobacco use (HR: 1.03, 95% CI 1.02–1.03) and more severe symptoms of disorganisation (HR: 2.36, 95% CI 2.21–2.52). Conclusions: The high SMR and the incidence of cardiovascular disease-related death in SMI patients in our study justify concern. This study underscores the urgent need for interventions to reduce excess mortality in patients with SMI

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

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

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

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