Characteristics of people attending psychiatric clinics in inner Sydney homeless hostels.

OBJECTIVE: To describe the characteristics of people attending mental health clinics at shelters for the homeless in inner city Sydney. DESIGN: Retrospective review of medical records of homeless hostel clinic attenders. SETTING: Mental health clinics located in three inner city homeless hostels. PARTICIPANTS: Consecutive series of clinic attenders, 21 July 2008 - 31 December 2016. MAIN OUTCOME MEASURES: Demographic characteristics; social, medical and mental health histories of homeless people. RESULTS: 2388 individual patients were seen at the clinics during the 8.5-year study period. Their mean age was 42 years (standard deviation, 13 years), 93% were men, and 56% were receiving disability support pensions. 59% of attenders had been homeless for more than a year, and 34% of all attenders reported sleeping in the open. The most common diagnoses were substance use disorder (66%), psychotic illness (51%), acquired brain injury (14%), and intellectual disability (5%). Most patients had more than one diagnosis. Early life and recent trauma was reported by 42% of patients. Pathways to homelessness included release from prison (28% of the homeless), discharge from a psychiatric hospital (21%), loss of public housing tenancy (21%), and inability to pay rent because of problem gambling. CONCLUSIONS: The high rates of substance use and mental disorder among homeless people in inner Sydney confirms the need for increased access to treatment for these conditions in this setting. Homelessness among those with mental illness might be reduced by developing alternative housing models, and supporting people with multiple problems to retain tenancy.

Stimulant use disorders in people with psychosis: a meta-analysis of rate and factors affecting variation.

OBJECTIVE: Stimulant abuse and dependence often complicate the care of people with psychotic disorders. This study systematically reviews the prevalence estimates reported for stimulant abuse and dependence in people with psychotic disorders, and examines personal, clinical, regional and methodological factors which explain variation in these rates. METHODS: PsychINFO, EMBASE and MEDLINE (1946-2013) were searched systematically for studies reporting on stimulant drug use disorders in representative samples of people with psychotic disorders. Random effects models estimated the pooled rate of a stimulant use disorder, defined to include stimulant abuse and stimulant dependence. Study characteristics associated with heterogeneity in rates of stimulant use disorder were examined by subgroup analyses for categorical variables, by meta-regression for continuous independent variables and by multiple meta-regression. RESULTS: Sixty-four studies provided 68 estimates of lifetime or recent stimulant use disorders in 22,500 people with psychosis. The pooled rate of stimulant use disorder was 8.9% (95% CI 7.4%, 10.5%). Higher rates of stimulant use disorders were reported in studies of affective psychosis, studies from inpatient settings, studies from the USA and Australia, and studies with higher rates of cannabis disorder; in multiple meta-regression analysis these factors explained 68% of between-study variance. Rates of stimulant use disorder were stable over time, and unrelated to age, sex, stage of psychosis, type of stimulant drug or study methodology factors. CONCLUSIONS: Reported rates of stimulant use disorder in people with psychosis are much higher than in the general population but vary widely and are associated with regional, service setting and clinical differences between studies. It is likely that stimulants contribute to the overall burden of psychosis, and that social and environmental factors combine with drug and illness-related factors to influence stimulant use in psychosis.

A 21-year retrospective outcome study of New South Wales forensic patients granted conditional and unconditional release.

AIM: To retrospectively examine the outcomes of forensic patients found not guilty by reason of mental illness (NGMI) in New South Wales (NSW) and subsequently released into the community, as measured by reoffending, conditional release revocation and psychiatric hospital readmission. METHOD: Data were collected from the NSW Mental Health Review Tribunal (MHRT) files for all patients who received an NGMI verdict between January 1990 and December 2010, and who were released into the community during this period. The outcome measures of conditional release revocation and psychiatric hospital readmission were extracted from these files. Information about subsequent criminal charges, convictions and penalties were obtained from the Bureau of Crime Statistics and Research's reoffending database. RESULTS: During the 21-year period studied, 364 offenders received an NGMI verdict and were placed under the supervision of the MHRT. Of these, 197 were released into the community, including 85 who were granted unconditional release. Over a follow-up period averaging 8.4 years, 18% of conditionally released patients reoffended, 11.8% were convicted of a further offence, 8.7% were charged with a violent offence, 3.1% were convicted of a violent offence and 3.7% were sentenced to a term of imprisonment. Five (3.1%) conditionally released forensic patients received a further NGMI verdict. One-quarter of the conditionally released patients had their conditional release revoked and half were readmitted to hospital. Of the forensic patients granted unconditional release, 12.5% were charged with an offence, 9.4% received convictions for an offence, 6.3% were charged with a violent offence and 4.7% were convicted of a violent offence, in a mean follow-up period of 7.6 years. None committed a further serious offence resulting in a term of imprisonment, nor a second NGMI verdict. CONCLUSIONS: The results of this study suggest that the treatment and rehabilitation of forensic patients in NSW, together with the decision-making procedures of the MHRT, is effective in protecting the community from further offending by forensic patients.

Suicide risk categorisation of psychiatric inpatients: what it might mean and why it is of no use.

OBJECTIVE: Existing suicide risk assessment policies and guidelines do not specify whether the risk to be assessed is absolute, relative to other patients or relative to the same patient at an earlier time. METHODS: We utilised the results of a recent study of inpatient suicide to explore the implications of each of the above types of risk. RESULTS: No interpretation of the current requirements for suicide risk categorisation of psychiatric inpatients can lead to information that might usefully guide clinical decision-making. CONCLUSIONS: Policies and guidelines requiring suicide risk categorisation of inpatients should be withdrawn. The College should delete the mandatory entrustable professional activity requiring risk assessment.

Delusions in postpartum psychosis: Implications for cognitive theories.

Postpartum psychosis is a rare but serious condition that can affect women after childbirth. We present a case study of an individual with no comorbidities or psychiatric history who developed postpartum psychosis characterised by prominent misidentification delusions whilst admitted to hospital. The woman recovered quickly with medication and showed no evidence of relapse over the following three years. Whilst still symptomatic and after recovery, the patient was able to provide a detailed description of her experiences. Contemporaneous interviews and observations during her hospital admission and a subsequent detailed retrospective account provide a unique, comprehensive window into her experience of these time-limited delusions. Her case reveals important insights including the triggers for her misidentification delusions, the role of social and contextual influences on delusional beliefs, and her recall of active involvement in evaluating and discarding delusional hypotheses. These insights highlight the complexity of delusional beliefs, challenge existing theories of delusions, and help inform broader theories of belief formation.

The predictive validity and temporal characteristics of the HCR-20v3 for inpatient violence in forensic inpatient settings. An international study.

Aggression and violence are common day to day problems in psychiatric settings. However, the optimal means of assessing that risk remains unclear. In the context of that uncertainty many tools have evolved, among which the HCR-20 is one of the most globally accepted, though many questions remain about its performance, how and when it should be deployed and how it can be most effectively used. In this 12 month follow up study of 210 forensic psychiatric inpatients with a diagnosis of a schizophrenia spectrum disorder we explored these issues. We found that the performance of the HCR-20v3, especially its Total score, performed well up to 6 months after it was rated but its performance deteriorated after that. Repeating the HCR-20v3 at 6 months stabilised the risk assessment and led to improved performance in the second months over and above the first rating. The HCR-20v3 was good at identifying those subjects at low risk of violence over 6 months of follow up in a forensic inpatient setting. The real-world implications of this study are that the HCR-20v3 is an effective means of identifying patient at low risk of violence, but it should be reassessed every 6 months.

Calibrating violence risk assessments for uncertainty.

Psychiatrists and other mental health clinicians are often tasked with assessing patients' risk of violence. Approaches to this vary and include both unstructured (based on individual clinicians' judgement) and structured methods (based on formalised scoring and algorithms with varying scope for clinicians' judgement). The end result is usually a categorisation of risk, which may, in turn, reference a probability estimate of violence over a certain time period. Research over recent decades has made considerable improvements in refining structured approaches and categorising patients' risk classifications at a group level. The ability, however, to apply these findings clinically to predict the outcomes of individual patients remains contested. In this article, we review methods of assessing violence risk and empirical findings on their predictive validity. We note, in particular, limitations in calibration (accuracy at predicting absolute risk) as distinct from discrimination (accuracy at separating patients by outcome). We also consider clinical applications of these findings, including challenges applying statistics to individual patients, and broader conceptual issues in distinguishing risk and uncertainty. Based on this, we argue that there remain significant limits to assessing violence risk for individuals and that this requires careful consideration in clinical and legal contexts.

Mania, homicide and severe violence.

BACKGROUND: Mania has been reported to be a risk factor for aggression and violence in psychiatric hospitals, but the extent of any association between mania and severe interpersonal violence in community settings is not known. AIM: To examine the association between mania and severe violence in a series of patients found not guilty by reason of mental illness (NGMI). METHODS: A review of the court documents of those found NGMI of offences involving severe violence, including homicide, attempted homicide and assault causing wounding or serious injury, in New South Wales between 1992 and 2008. RESULTS: Twelve of 272 people found NGMI were in a manic state when they committed a severe violence offence. Ten were diagnosed with schizo-affective disorder and two with bipolar disorder. Three patients were in the depressed phase of schizo-affective disorder and there were no patients in the depressed phase of bipolar disorder. CONCLUSION: Mania, in particular the manic phase of bipolar disorder, is not strongly associated with severe violence.

Severe non-lethal violence during psychotic illness.

BACKGROUND: Research about violence in psychosis has mainly considered homicide by people with mental disorder, especially schizophrenia, and violence in groups of psychiatric patients. In this study we examine the characteristics of a sample of offenders with psychotic illness who committed severe non-lethal violent offences. METHOD: A review of court documents from a consecutive series of cases involving violence resulting in significant injury concluded in the District Court of New South Wales, Australia, in the years 2006 and 2007. RESULTS: Of 661 people found to have committed a severe violent offence, 74 (11%, 95% confidence interval (CI) 9-14%) had a diagnosed psychotic illness. Of these, 16 (22%, 95% CI 12-31%) had never received treatment with antipsychotic medication and could be regarded as being in the first episode of psychosis. Offenders with psychosis were typically non-adherent to treatment, had co-morbid substance use and prior criminal convictions. Positive symptoms of psychotic illness such as hallucinations and delusional beliefs were reported to be present at the time of the offence in most of the cases. Seven of 74 (10%) psychotic offenders were found not guilty on the grounds of mental illness. CONCLUSIONS: People with psychotic illness are over-represented among those who commit violent offences resulting in significant injury, confirming the presence of an association between psychosis and severe non-lethal violence. Earlier treatment of first episode psychosis, improving the adherence to treatment of known patients and treatment of co-morbid substance abuse could reduce the incidence of severe violence committed by patients with psychosis.

Clinical and cognitive associations with aggression in the first episode of psychosis.

OBJECTIVE: Although there may be an increased risk of aggression in first-episode psychosis, little is known about the clinical and cognitive associations of serious and less serious aggression during this phase of psychotic illness. METHODS: Eighty-five patients in the first episode of psychosis under the age of 26 underwent comprehensive clinical assessment and cognitive testing. Aggression was assessed using a purpose-designed rating scale based on corroborative interviews to record 10 types of aggressive behaviour in the 3 months before presenting for treatment. RESULTS: Thirty-seven of 85 patients (43.5%) exhibited physically aggressive behaviour and 23 patients (27.1%) had assaulted another person or used a weapon. Young age and elevated scores in the mania rating scale were associated with a history of any type of aggression. Serious aggression was associated with regular cannabis use and more errors of commission on a continuous performance task. CONCLUSIONS: The clinical features associated with less serious aggression were different to those associated with more serious forms of aggression. Serious aggression is associated with regular cannabis use and also reduced behavioural inhibition. Awareness of substance use and neurocognitive deficits may assist in the identification of potentially violent patients.

Suicide attempts by jumping and psychotic illness.

BACKGROUND: Several recent studies have reported that serious violence towards self and others is more common in the first episode of psychosis than after treatment. AIM: To estimate the proportion of survivors of suicide attempts during psychotic illness by jumping from a height who had not previously received treatment with antipsychotic medication. METHODS: An audit of the medical records of patients admitted to nine designated trauma centres in New South Wales, Australia, after surviving a jump of more than 3 m. Jumping was defined using routine hospital ascribed International Classification of Diseases (ICD) codes. The height of the jump and all clinical data were extracted from case notes. RESULTS: The files of 160 survivors of jumps of more than 3 m were examined, which included 70 who were diagnosed with a psychotic illness (44%). Thirty-one of the 70 diagnosed with a psychotic illness (44%, 95% confidence interval [CI] 32-56%) had never received treatment for psychosis and hence were in the first episode of psychosis. One in five (19.4%) of all survivors of a suicide attempt by jumping had an undiagnosed and untreated psychosis that was often characterized by frightening delusional beliefs. CONCLUSION: A large proportion of the survivors of suicide attempts by jumping were diagnosed with a psychotic illness, which confirms an association between psychosis and suicide by jumping. Some suicides might not have been linked to psychosis had the patient not survived the suicide attempt, suggesting that the contribution of schizophrenia to suicide mortality might have been underestimated in psychological autopsy studies. The finding that nearly half of the survivors diagnosed to have a psychotic illness had never received treatment with antipsychotic medication indicates a greatly increased risk of suicide by jumping in the first episode of psychosis when compared to the annual risk after treatment.

Can machine-learning methods really help predict suicide?

PURPOSE OF REVIEW: In recent years there has been interest in the use of machine learning in suicide research in reaction to the failure of traditional statistical methods to produce clinically useful models of future suicide. The current review summarizes recent prediction studies in the suicide literature including those using machine learning approaches to understand what value these novel approaches add. RECENT FINDINGS: Studies using machine learning to predict suicide deaths report area under the curve that are only modestly greater than, and sensitivities that are equal to, those reported in studies using more conventional predictive methods. Positive predictive value remains around 1% among the cohort studies with a base rate that was not inflated by case-control methodology. SUMMARY: Machine learning or artificial intelligence may afford opportunities in mental health research and in the clinical care of suicidal patients. However, application of such techniques should be carefully considered to avoid repeating the mistakes of existing methodologies. Prediction studies using machine-learning methods have yet to make a major contribution to our understanding of the field and are unproven as clinically useful tools.