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

Формування світогляду О. Кониського

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 effects of intensive home treatment on self-efficacy in patients recovering from a psychiatric crisis

Background: This study evaluated whether providing intensive home treatment (IHT) to patients experiencing a psychiatric crisis has more effect on self-efficacy when compared to care as usual (CAU). Self-efficacy is a psychological concept closely related to one of the aims of IHT. Additionally, differential effects on self-efficacy among patients with different mental disorders and associations between self-efficacy and symptomatic recovery or quality of life were examined. Methods: Data stem from a Zelen double consent randomised controlled trial (RCT), which assesses the effects of IHT compared to CAU on patients who experienced a psychiatric crisis. Data were collected at baseline, 6 and 26 weeks follow-up. Self-efficacy was measured using the Mental Health Confidence Scale. The 5-dimensional EuroQol instrument and the Brief Psychiatric Rating Scale (BPRS) were used to measure quality of life and symptomatic recovery, respectively. We used linear mixed modelling to estimate the associations with self-efficacy. Results: Data of 142 participants were used. Overall, no difference between IHT and CAU was found with respect to self-efficacy (B = − 0.08, SE = 0.15, p = 0.57), and self-efficacy did not change over the period of 26 weeks (B = − 0.01, SE = 0.12, t (103.95) = − 0.06, p = 0.95). However, differential effects on self-efficacy over time were found for patients with different mental disorders (F(8, 219.33) = 3.75, p < 0.001). Additionally, self-efficacy was strongly associated with symptomatic recovery (total BPRS B = − 0.10, SE = 0.02, p < 0.00) and quality of life (B = 0.14, SE = 0.01, p < 0.001). Conclusions: Although self-efficacy was associated with symptomatic recovery and quality of life, IHT does not have a supplementary effect on self-efficacy when compared to CAU. This result raises the question whether, and how, crisis care could be adapted to enhance self-efficacy, keeping in mind the development of self-efficacy in depressive, bipolar, personality, and schizophrenia spectrum and other psychotic disorders. The findings should be considered with some caution. This study lacked sufficient power to test small changes in self-efficacy and some mental disorders had a small sample size. Trial registration This trial is registered at Trialregister.nl, number NL6020

Factors associated with victimization in dual diagnosis patients

Background: Patients with a substance use disorder and co-occurring mental disorder are prone to victimization. There is a lack of research identifying variables related to violent and property victimization in this high risk group. The aim of this study was to identify factors associated with violent and property victimization in male and female dual diagnosis patients in order to identify targets for prevention. Methods: In a cross-sectional study, victimization and demographic, clinical and psychological characteristics were assessed in 243 treatment-seeking patients with dual diagnosis. Patients were recruited in an addiction psychiatry clinic and an allied outpatient care facility in Amsterdam, The Netherlands. Results: In a multiple logistic regression analysis, violent victimization was independently associated with younger age, female gender, violent offending and a self-sacrificing and overly accommodating interpersonal style (p <0.001; chi(2) = 108.83, d.f. = 8, R-2 = 0.49) in dual diagnosis patients. In male patients, violent victimization was independently associated with younger age, violent offending and a self-sacrificing and overly accommodating interpersonal style (p <0.001; chi(2) = 91.90, d.f. = 7, R-2 = 0.56). In female patients, violent victimization was independently positively associated with homelessness, violent offending, a domineering/controlling interpersonal style, and negatively associated with being socially inhibited and cold/distant (p <0.001; chi(2) = 34.08, d.f. = 4, R2 = 0.53). Property victimization was independently associated with theft offending (p <0.001, chi(2) = 26.99, d.f. = 5, R-2 = 0.14). Conclusions: Given the high prevalence of victimization in dual diagnosis patients and its related problems, preventive interventions should be developed. Interventions should target interpersonal skills to decrease vulnerability to victimization, address the overlap between victimization and offending and incorporate gender-specific elements. (C) 2017 Elsevier Inc. All rights reserve

Factors associated with victimization in dual diagnosis patients

Background Patients with a substance use disorder and co-occurring mental disorder are prone to victimization. There is a lack of research identifying variables related to violent and property victimization in this high risk group. The aim of this study was to identify factors associated with violent and property victimization in male and female dual diagnosis patients in order to identify targets for prevention. Methods In a cross-sectional study, victimization and demographic, clinical and psychological characteristics were assessed in 243 treatment-seeking patients with dual diagnosis. Patients were recruited in an addiction-psychiatry clinic and an allied outpatient care facility in Amsterdam, The Netherlands. Results In a multiple logistic regression analysis, violent victimization was independently associated with younger age, female gender, violent offending and a self-sacrificing and overly accommodating interpersonal style (p < 0.001; χ2 = 108.83, d.f. = 8, R2 = 0.49) in dual diagnosis patients. In male patients, violent victimization was independently associated with younger age, violent offending and a self-sacrificing and overly accommodating interpersonal style (p < 0.001; χ2 = 91.90, d.f. = 7, R2 = 0.56). In female patients, violent victimization was independently positively associated with homelessness, violent offending, a domineering/controlling interpersonal style, and negatively associated with being socially inhibited and cold/distant (p < 0.001; χ2 = 34.08, d.f. = 4, R2 = 0.53). Property victimization was independently associated with theft offending (p < 0.001, χ2 = 26.99, d.f. = 5, R2 = 0.14). Conclusions Given the high prevalence of victimization in dual diagnosis patients and its related problems, preventive interventions should be developed. Interventions should target interpersonal skills to decrease vulnerability to victimization, address the overlap between victimization and offending and incorporate gender-specific elements

Police Encounters, Agitation, Diagnosis, and Employment Predict Psychiatric Hospitalisation of Intensive Home Treatment Patients During a Psychiatric Crisis

Objective: This study aims to determine factors associated with psychiatric hospitalisation of patients treated for an acute psychiatric crisis who had access to intensive home treatment (IHT). Methods: This study was performed using data from a randomised controlled trial. Interviews, digital health records and eight internationally validated questionnaires were used to collect data from patients on the verge of an acute psychiatric crisis enrolled from two mental health organisations. Thirty-eight factors were assigned to seven risk domains. The seven domains are “sociodemographic”, “social engagement”, “diagnosis and psychopathology”, “aggression”, “substance use”, “mental health services” and “quality of life”. Multiple logistic regression analysis (MLRA) was conducted to assess how much pseudo variance in hospitalisation these seven domains explained. Forward MLRA was used to identify individual risk factors associated with hospitalisation. Risks were expressed in terms of relative risk (RR) and absolute risk difference (ARD). Results: Data from 183 participants were used. The mean age of the participants was 40.03 (SD 12.71), 57.4% was female, 78.9% was born in the Netherlands and 51.4% was employed. The range of explained variance for the domains related to “psychopathology and care” was between 0.34 and 0.08. The “aggression” domain explained the highest proportion (R2 = 0.34) of the variance in hospitalisation. “Quality of life” had the lowest explained proportion of variance (R2 = 0.05). The forward MLRA identified four predictive factors for hospitalisation: previous contact with the police or judiciary (OR = 7.55, 95% CI = 1.10–51.63; ARD = 0.24; RR = 1.47), agitation (OR = 2.80, 95% CI = 1.02–7.72; ARD = 0.22; RR = 1.36), schizophrenia spectrum and other psychotic disorders (OR = 22.22, 95% CI = 1.74–284.54; ARD = 0.31; RR = 1.50) and employment status (OR = 0.10, 95% CI = 0.01–0.63; ARD = −0.28; RR = 0.66). Conclusion: IHT teams should be aware of patients who have histories of encounters with the police/judiciary or were agitated at outset of treatment. As those patients benefit less from IHT due to the higher risk of hospitalisation. Moreover, type of diagnoses and employment status play an important role in predicting hospitalisation

Victimisation in adults with severe mental illness: prevalence and risk factors

Patients with a severe mental illness (SMI) are more likely to experience victimisation than the general population. To examine the prevalence of victimisation in people with SMI, and the relationship between symptoms, treatment facility and indices of substance use/misuse and perpetration, in comparison with the general population. Victimisation was assessed among both randomly selected patients with SMI (n = 216) and the general population (n = 10 865). Compared with the general population, a high prevalence of violent victimisation was found among the SMI group (22.7% v. 8.5%). Compared with out-patients and patients in a sheltered housing facility, in-patients were most often victimised (violent crimes: 35.3%; property crimes: 47.1%). Risk factors among the SMI group for violent victimisation included young age and disorganisation, and risk factors for property crimes included being an in-patient, disorganisation and cannabis use. The SMI group were most often assaulted by someone they knew. Caregivers should be aware that patients with SMI are at risk of violent victimisation. Interventions need to be developed to reduce this vulnerabilit

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