Suicidality in childhood and adolescence is of increasing concern. The aim of this paper was to review the published literature identifying key psychosocial risk factors for suicidality in the paediatric population. A systematic two-step search was carried out following the PRISMA statement guidelines, using the terms 'suicidality, suicide, and self-harm' combined with terms 'infant, child, adolescent' according to the US National Library of Medicine and the National Institutes of Health classification of ages. Forty-four studies were included in the qualitative synthesis. The review identified three main factors that appear to increase the risk of suicidality: psychological factors (depression, anxiety, previous suicide attempt, drug and alcohol use, and other comorbid psychiatric disorders); stressful life events (family problems and peer conflicts); and personality traits (such as neuroticism and impulsivity). The evidence highlights the complexity of suicidality and points towards an interaction of factors contributing to suicidal behaviour. More information is needed to understand the complex relationship between risk factors for suicidality. Prospective studies with adequate sample sizes are needed to investigate these multiple variables of risk concurrently and over time.

In this data set of bipolar patients we noted an intriguing picture of two clusters of suicide attempts. Hostility was the strongest risk factor. These findings may have implications in both the identification of at-risk patients and the timing of clinical interventions including aggressive pharmacotherapeutic prophylaxis to prevent relapse or recurrence of depressive symptomatology.

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Background-Bipolar Disorder (BD) is associated with a high prevalence of suicide attempt and completion. Family history of suicidal behavior and personal history of childhood abuse are reported risk factors for suicide among BD subjects.

We concluded that being the middle child and living with both biological parents appear to be protective factors against the development of ED or ADHD. Living in large families appears to increase the risk of receiving a CD, MR, or PDD diagnosis. Further research is warranted.

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Suicide is among the top ten leading causes of death in individuals of all ages. An explanatory model for suicidal behavior that links clinical and psychological risk factors or endophenotypes, to the underlying neurobiological abnormalities associated with suicidal behavior may enhance prediction, help identify treatment options and have heuristic value. Our explanatory model proposes that developmental factors that are biological (genetics) and psychological or clinical (early childhood adversity) may have causal relevance to the disturbances found in subjects with suicidal behavior. In this way, our model integrates findings from several perspectives in suicidology and attempts to explain the relationship between various neurobiological, genetic, and clinical observations in suicide research, offering a comprehensive hypothesis to facilitate understanding of this complex outcome.

Ecological momentary assessment (EMA) is gaining importance in psychiatry. This article assesses the characteristics of patients who used a new electronic EMA tool: the MEmind Wellness Tracker. Over one year, 13811 adult outpatients in our Psychiatry Department were asked to use MEmind. We collected information about socio-demographic data, psychiatric diagnoses, illness severity, stressful life events and suicidal thoughts/behavior. We compared active users (N = 2838) and non-active users (N = 10,973) of MEmind and performed a Random Forest analysis to assess which variables could predict its use. Univariate analyses revealed that MEmind-users were younger (42.2 ± 13.5 years versus 48.5 ± 16.3 years; χ = 18.85; P < 0.001) and more frequently diagnosed with anxiety related disorders (57.9% versus 46.7%; χ = 105.92; P = 0.000) than non-active users. They were more likely to report thoughts about death and suicide (up to 24% of active users expressed wish for death) and had experienced more stressful life events than non-active users (57% versus 48.5%; χ = 64.65; P < 0.001). In the Random Forest analysis, 31 variables showed mean decrease accuracy values higher than zero with a 95% confidence interval (CI), including sex, age, suicidal thoughts, life threatening events and several diagnoses. In the light of these results, strategies to improve EMA and e-Mental Health adherence are discussed.