Intensive case management for high-risk patients with first-episode psychosis: service model and outcomes

Background : The first episode of psychosis is a crucial period when early intervention can alter the trajectory of the young person's ongoing mental health and general functioning. After an investigation into completed suicides in the Early Psychosis Prevention and Intervention Centre (EPPIC) programme, the intensive case management subprogramme was developed in 2003 to provide assertive outreach to young people having a first episode of psychosis who are at high risk owing to risk to self or others, disengagement, or suboptimal recovery. We report intensive case management model development, characterise the target cohort, and report on outcomes compared with EPPIC treatment as usual.

Methods : Inclusion criteria, staff support, referral pathways, clinical review processes, models of engagement and care, and risk management protocols are described. We compared 120 consecutive referrals with 50 EPPIC treatment as usual patients (age 15–24 years) in a naturalistic stratified quasi-experimental real-world design. Key performance indicators of service use plus engagement and suicide attempts were compared between EPPIC treatment as usual and intensive case management, and psychosocial and clinical measures were compared between intensive case management referral and discharge.

Findings : Referrals were predominately unemployed males with low levels of functioning and educational attainment. They were characterised by a family history of mental illness, migration and early separation, with substantial trauma, history of violence, and forensic attention. Intensive case management improved psychopathology and psychosocial outcomes in high-risk patients and reduced risk ratings, admissions, bed days, and crisis contacts.

Interpretation : Characterisation of intensive case management patients validated the clinical research focus and identified a first episode of psychosis high-risk subgroup. In a real-world study, implementation of an intensive case management stream within a well-established first episode of psychosis service showed significant improvement in key service outcomes. Further analysis is needed to determine cost savings and effects on psychosocial outcomes. Targeting intensive case management services to high-risk patients with unmet needs should reduce the distress associated with pathways to care for patients, their families, and the community.

Incidence and course of adolescent deliberate self-harm in Victoria, Australia, and Washington State

PURPOSE: There have been few longitudinal studies of deliberate self-harm (DSH) in adolescents. This cross-national longitudinal study outlines risk and protective factors for DSH incidence and persistence. METHODS: Seventh and ninth grade students (average ages 13 and 15 years) were recruited as state-representative cohorts, surveyed, and then followed up 12 months later (N = 3,876), using the same methods in Washington State and Victoria, Australia. The retention rate was 99% in both states at follow-up. A range of risk and protective factors for DSH were examined using multivariate analyses. RESULTS: The prevalence of DSH in the past year was 1.53% in Grade 7 and .91% in Grade 9 for males and 4.12% and 1.34% for Grade 7 and Grade 9 females, respectively, with similar rates across states. In multivariate analyses, incident DSH was lower in Washington State (odds ratio [OR] = .67; 95% confidence interval [CI] = .45-1.00) relative to Victoria 12 months later. Risk factors for incident DSH included being female (OR = 1.93; CI = 1.35-2.76), high depressive symptoms (OR = 3.52; CI = 2.37-5.21), antisocial behavior (OR = 2.42; CI = 1.46-4.00), and lifetime (OR = 1.85; CI = 1.11-3.08) and past month (OR = 2.70; CI = 1.57-4.64) alcohol use relative to never using alcohol. CONCLUSIONS: Much self-harm in adolescents resolves over the course of 12 months. Young people who self-harm have high rates of other health risk behaviors associated with family and peer risks that may all be targets for preventive intervention.

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Electronic medical record (EMR) offers promises for novel analytics. However, manual feature engineering from EMR is labor intensive because EMR is complex - it contains temporal, mixed-type and multimodal data packed in irregular episodes. We present a computational framework to harness EMR with minimal human supervision via restricted Boltzmann machine (RBM). The framework derives a new representation of medical objects by embedding them in a low-dimensional vector space. This new representation facilitates algebraic and statistical manipulations such as projection onto 2D plane (thereby offering intuitive visualization), object grouping (hence enabling automated phenotyping), and risk stratification. To enhance model interpretability, we introduced two constraints into model parameters: (a) nonnegative coefficients, and (b) structural smoothness. These result in a novel model called eNRBM (EMR-driven nonnegative RBM). We demonstrate the capability of the eNRBM on a cohort of 7578 mental health patients under suicide risk assessment. The derived representation not only shows clinically meaningful feature grouping but also facilitates short-term risk stratification. The F-scores, 0.21 for moderate-risk and 0.36 for high-risk, are significantly higher than those obtained by clinicians and competitive with the results obtained by support vector machines.

Differentially private multi-task learning

Privacy restrictions of sensitive data repositories imply that the data analysis is performed in isolation at each data source. A prime example is the isolated nature of building prognosis models from hospital data and the associated challenge of dealing with small number of samples in risk classes (e.g. suicide) while doing so. Pooling knowledge from other hospitals, through multi-task learning, can alleviate this problem. However, if knowledge is to be shared unrestricted, privacy is breached. Addressing this, we propose a novel multi-task learning method that preserves privacy of data under the strong guarantees of differential privacy. Further, we develop a novel attribute-wise noise addition scheme that significantly lifts the utility of the proposed method. We demonstrate the effectiveness of our method with a synthetic and two real datasets.

Differentiating sub-groups of online depression-related communities using textual cues

Depression is a highly prevalent mental illness and is a comorbidity of other mental and behavioural disorders. The Internet allows individuals who are depressed or caring for those who are depressed, to connect with others via online communities; however, the characteristics of these online conversations and the language styles of those interested in depression have not yet been fully explored. This work aims to explore the textual cues of online communities interested in depression. A random sample of 5,000 blog posts was crawled. Five groupings were identified: depression, bipolar, self-harm, grief, and suicide. Independent variables included psycholinguistic processes and content topics extracted from the posts. Machine learning techniques were used to discriminate messages posted in the depression sub-group from the others.Good predictive validity in depression classification using topics and psycholinguistic clues as features was found. Clear discrimination between writing styles and content, with good predictive power is an important step in understanding social media and its use in mental health.

A different kettle of fish : mental health strategies for Australian fishers, and farmers

Despite being typically represented and managed under the same policy umbrella, fishers face different challenges than do their farming counterparts. This paper unpacks the findings of research depicting poor levels of mental health and well-being among Australian commercial wild-catch fishers. The research is considered in the context of widespread acceptance that farmers tend to exhibit worse than average mental health outcomes due, at least in part, to the environmental uncertainties of climate change. In particular it is stressed that the insecurity of fishing concessions (quota and licenses), is a key driver of chronic livelihood insecurity, resulting in reports of stress, depression and suicide. A call is made for the separation of health research in the fishing and farming industries. Importantly, the role that tenure insecurity plays in the perpetuation of poor mental health among fishers should be acknowledged and addressed so that the fishing industry can maximize the strength of its human capital.

Social connections and suicidal behaviour in young Australian adults: Evidence from a case-control study of persons aged 18-34 years in NSW, Australia

Purpose: There is evidence that social isolation is a risk factor for suicide, and that social connections are protective. Only a limited number of studies have attempted to correlate the number of social connections a person has in their life and suicidal behaviour. Method: Two population-based case-control studies of young adults (18-34 years) were conducted in New South Wales, Australia. Cases included both suicides (n=84) and attempts (n=101). Living controls selected from the general population were matched to cases by age-group and sex. Social connections was the main exposure variable (representing the number of connections a person had in their life). Suicide and attempts as outcomes were modelled separately and in combination using conditional logistic regression modelling. The analysis was adjusted for marital status, socio-economic status, and diagnosis of an affective or anxiety disorder. Results: Following adjustment for other variables, those who had 3-4 social connections had 74% lower odds of suicide deaths or attempts (OR=0.26, 95% CI 0.08, 0.84, p=0.025), and those with 5-6 connections had 89% lower odds of suicide deaths or attempts (OR=0.11 95% CI 0.03, 0.35, p<0.001), compared to those with 0-2 social connections. With the number of social connection types specified as a continuous variable, the odds ratio was 0.39 per connection (95% CI 0.27, 0.56, p<0.001). Conclusions: A greater number of social connections was significantly associated with reduced odds of suicide or attempt. This suggests that suicide prevention initiatives that promote increased social connections at an individual, familial, and wider social levels might be effective.

Bipolar disorder

Bipolar disorder is a recurrent chronic disorder characterised by fluctuations in mood state and energy. It affects more than 1% of the world's population irrespective of nationality, ethnic origin, or socioeconomic status. Bipolar disorder is one of the main causes of disability among young people, leading to cognitive and functional impairment and raised mortality, particularly death by suicide. A high prevalence of psychiatric and medical comorbidities is typical in affected individuals. Accurate diagnosis of bipolar disorder is difficult in clinical practice because onset is most commonly a depressive episode and looks similar to unipolar depression. Moreover, there are currently no valid biomarkers for the disorder. Therefore, the role of clinical assessment remains key. Detection of hypomanic periods and longitudinal assessment are crucial to differentiate bipolar disorder from other conditions. Current knowledge of the evolving pharmacological and psychological strategies in bipolar disorder is of utmost importance.

The treatment of suicidality in adolescents by psychosocial interventions for depression: a systematic literature review

OBJECTIVE: Given depression is a significant risk factor for suicidal behaviour, it is possible that interventions for depression may also reduce the risk of suicide in adolescents. The purpose of this literature review is to determine whether psychological interventions aimed to prevent and/or treat depression in adolescents can also reduce suicidality. METHODS: We conducted a systematic review of psychological interventions aimed to prevent and/or treat depression in adolescents in which outcomes for suicidality were reported, using five databases: PsycINFO, Embase, Medline, CINAHL and Scopus. Study quality was assessed using the Cochrane Collaboration's tool for assessing risk of bias. RESULTS: A total of 35 articles pertaining to 12 treatment trials, two selective prevention trials and two universal prevention trials met inclusion criteria. No studies were identified that used a no-treatment control. In both intervention and active control groups, suicidality decreased over time; however, most structured psychological depression treatment interventions did not outperform pharmaceutical or treatment as usual control groups. Depression prevention studies demonstrated small but statistically significant reductions in suicidality. LIMITATIONS: Analysis of study quality suggested that at least 10 of the 16 studies have a high risk of bias. Conclusive comparisons across studies are problematic due to differences in measures, interventions, population differences and control groups used. CONCLUSIONS: It is unclear whether psychological treatments are more effective than no treatment since no study has used a no-treatment control group. There is evidence to suggest that Cognitive Behavioural Therapy interventions produce pre-post reductions in suicidality with moderate effect sizes and are at least as efficacious as pharmacotherapy in reducing suicidality; however, it is unclear whether these effects are sustained. There are several trials showing promising evidence for family-based and interpersonal therapies, with large pre-post effect sizes, and further evaluation with improved methodology is required. Depression prevention interventions show promising short-term effects.

Staying healthy: industry organisations’ influence on behaviours and services used by fishers

This study emerged in response to a previous report that used a strength-based approach to identify best-practice good-health behaviours in a number of farming and fishing communities, titled Staying Healthy: Behaviours and services used by farmers and fishers. This earlier report found there was a need for specific attention to the physical and particularly the mental health of those in the Australian commercial fishing industry. This included a better understanding of the issues, logistical and social barriers to good-health practices, and avenues of health communication and treatment. The 2013 Staying Healthy study echoed the Rural Industries Research and Development Corporation (RIRDC) research and development Plan for 2008-2012, Collaborative Partnership for Farming and Fishing Health and Safety, which advocated research into health, well-being and resilience in rural primary industries. These reports are coupled with widespread anecdotal accounts describing very poor physical and mental health within the fishing industry, including accounts of suicide and attempted suicide. As a contributor to a body of scholarly research, this study is supported by other literature, which is addressed, below. In this short section we introduce research that is most relevant to appreciating the findings of this study on fisher health and well-being.