There is uncertainty about factors associated with involuntary in-patient psychiatric care. Understanding these factors would help in reducing coercion in psychiatry.

To explore variables associated with involuntary care in the largest database of involuntary admissions published.

We identified 166 102 public mental health hospital admissions over 5 years in New South Wales, Australia. Demographic, clinical and episode-of-care variables were examined in an exploratory, multivariable logistic regression.

A total of 54% of eligible admissions included involuntary care. The strongest associations with involuntary care were referral from the legal system (odds ratio 4.98, 95% CI 4.61–5.38), and psychosis (odds ratio 4.48, 95% CI 4.31–4.64) or organic mental disorder (odds ratio 4.40, 95% CI 3.85–5.03). There were moderately strong associations between involuntary treatment and substance use disorder (odds ratio 2.68, 95% CI 2.56–2.81) or affective disorder (odds ratio 2.06, 95% CI 1.99–2.14); comorbid cannabis and amphetamine use disorders (odds ratio 1.65, 95% CI 1.57–1.74); unmarried status (odds ratio 1.62, 95% CI 1.49–1.76) and being born in Asia (odds ratio 1.42, 95% CI 1.35–1.50), Africa or the Middle East (odds ratio 1.32, 95% CI 1.24–1.40). Involuntary care was less likely for people aged >75 years (odds ratio 0.68, 95% CI 0.62–0.74), with comorbid personality disorder (odds ratio 0.90, 95% CI 0.87–0.94) or with private health insurance (odds ratio 0.89, 95% CI 0.86–0.93).

This research strengthens the evidence linking diagnostic, socioeconomic and cultural factors to involuntary treatment. Targeted interventions are needed to reduce involuntary admissions in disadvantaged groups.

The extent to which rates of homicide by people with or without schizophrenia vary over time has theoretical and practical implications in understanding homicide by people with mental illness.

The aim was to report on the rates of homicide by people diagnosed with schizophrenia over time in a region in which there were dramatic changes in the overall rates of homicide.

An examination of homicide by people diagnosed with schizophrenia in the course of judicial psychiatric examination, and the rate of other homicide in the Chuvash Republic of the Russian Federation between 1981 and 2020 was undertaken.

During the 40 years of the study a total of 5741 people faced legal proceedings for a homicide offence, of whom 179 (3.1%) were diagnosed with schizophrenia. During the study period the average annual total homicide rate rose from about 9 per 100 000 in the 1980s, peaked at 17 per 100 000 in the 1990s before falling to 13 per 100 000 in the 2000s and 6 per 100 000 in the 2010s. Rates of homicide by people with schizophrenia also rose and fell over this period and were significantly associated with the rates of other homicide (r = 0.503, d.f. = 38, P = 0.001).

The rise and fall in rates of homicide by people diagnosed with schizophrenia in parallel to total homicide suggests that homicidal behaviour might not be intrinsic to the clinical manifestations of the illness, and might instead reflect a heightened vulnerability to social factors that are associated with homicide by people without schizophrenia.

Suicide prediction models have been formulated in a variety of ways and are heterogeneous in the strength of their predictions. Machine learning has been a proposed as a way of improving suicide predictions by incorporating more suicide risk factors.

To determine whether machine learning and the number of suicide risk factors included in suicide prediction models are associated with the strength of the resulting predictions.

Random-effect meta-analysis of exploratory suicide prediction models constructed by combining two or more suicide risk factors or using clinical judgement (Prospero Registration CRD42017059665). Studies were located by searching for papers indexed in PubMed before 15 August 2020 with the term suicid* in the title.

In total, 86 papers reported 102 suicide prediction models and included 20 210 411 people and 106 902 suicides. The pooled odds ratio was 7.7 (95% CI 6.7–8.8) with high between-study heterogeneity (I2 = 99.5). Machine learning was associated with a non-significantly higher odds ratio of 11.6 (95% CI 6.0–22.3) and clinical judgement with a non-significantly lower odds ratio of 4.7 (95% CI 2.1–10.9). Models including a larger number of suicide risk factors had a higher odds ratio when machine-learning studies were included (P = 0.02). Among non-machine-learning studies, suicide prediction models including fewer risk factors performed just as well as those including more risk factors.

Machine learning might have the potential to improve the performance of suicide prediction models by increasing the number of included suicide risk factors but its superiority over other methods is unproven.

The expression of suicidal ideation is considered to be an important warning sign for suicide. However, the predictive properties of suicidal ideation as a test of later suicide are unclear.

To assess the strength of the association between suicidal ideation and later suicide measured by odds ratio (OR), sensitivity, specificity and positive predictive value (PPV).

We located English-language studies indexed in PubMed that reported the expression or non-expression of suicidal ideation among people who later died by suicide or did not. A random effects meta-analysis was used to assess the pooled OR, sensitivity, specificity and PPV of suicidal ideation for later suicide among groups of people from psychiatric and non-psychiatric settings.

There was a moderately strong but highly heterogeneous association between suicidal ideation and later suicide (n = 71, OR = 3.41, 95% CI 2.59–4.49, 95% prediction interval 0.42–28.1, I2 = 89.4, Q-value = 661, d.f.(Q) = 70, P ≤0.001). Studies conducted in primary care and other non-psychiatric settings had similar pooled odds to studies of current and former psychiatric patients (OR = 3.86 v. OR = 3.23, P = 0.7). The pooled sensitivity of suicidal ideation for later suicide was 41% (95% CI 35–48) and the pooled specificity was 86% (95% CI 76–92), with high between-study heterogeneity. Studies of suicidal ideation expressed by current and former psychiatric patients had a significantly higher pooled sensitivity (46% v. 22%) and lower pooled specificity (81% v. 96%) than studies conducted in non-psychiatric settings. The PPV among non-psychiatric cohorts (0.3%, 95% CI 0.1%–0.5%) was significantly lower (Q-value = 35.6, P < 0.001) than among psychiatric samples (3.9%, 95% CI 2.2–6.6).

Estimates of the extent of the association between suicidal ideation and later suicide are limited by unexplained between-study heterogeneity. The utility of suicidal ideation as a test for later suicide is limited by a modest sensitivity and low PPV.

M.M.L. and C.J.R. have provided expert evidence in civil, criminal and coronial matters. I.B.H. has been a Commissioner in Australia's National Mental Health Commission since 2012. He is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney. The BMC operates an early-intervention youth services at Camperdown under contract to Headspace. I.B.H. has previously led community-based and pharmaceutical industry-supported (Wyeth, Eli Lily, Servier, Pfizer, AstraZeneca) projects focused on the identification and better management of anxiety and depression. He is a Board Member of Psychosis Australia Trust and a member of Veterans Mental Health Clinical Reference group. He was a member of the Medical Advisory Panel for Medibank Private until October 2017. He is the Chief Scientific Advisor to, and an equity shareholder in, InnoWell. InnoWell has been formed by the University of Sydney and PricewaterhouseCoopers to administer the $30 M Australian Government Funded Project Synergy. Project Synergy is a 3-year programme for the transformation of mental health services through the use of innovative technologies.

M.M.L. has provided expert testimony in legal proceedings following in-patient suicide. N.K. sits on the Department of Health (England) National Suicide Prevention Strategy Advisory group.

Being a current psychiatric in-patient is one of the strongest statistical risk factors for suicide. It is usually assumed that this strong association is not causal but is a result of the combination of the selection of high-risk patients for admission and the imperfect protection from suicide afforded by psychiatric wards. Logically, a third factor, which is causal, might play a role in the association. It has recently been suggested that adverse experiences in psychiatric units such as trauma, stigma and loss of social role might precipitate some in-patient suicides.

To consider whether there is a causal association between psychiatric hospitalisation and suicide.

We used the framework of Austin Bradford Hill's criteria for assessing causality in epidemiology to consider the possibility that psychiatric hospitalisation might causally contribute to the extent and variation in in-patient suicide rates.

The association between psychiatric hospitalisation and suicide clearly meets five of the nine Hill's criteria (strength of association, consistency, plausibility, coherence and analogy) and partially meets three of the remaining four criteria (gradient of exposure, temporality and experimental evidence).

Admission to hospital itself might play a causal role in a proportion of in-patient suicides. The safety of being in hospital with respect to suicide could be examined with a large-scale randomised controlled trial (RCT). In the absence of an RCT, the possibility of a causal role provides further impetus to calls to make care in the community more available and psychiatric hospitals more acceptable to patients.