Vishal Bhavsar reports on the development and validation of a new clinical prediction rule (the OxMIS tool), which has been developed by the Forensic Psychiatry and Psychology group at the University of Oxford to help predict the risk of suicide in people with severe mental illness.
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Alex Langford appraises a systematic review that looks at high-risk categories for suicide risk assessment among psychiatric inpatients.
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Dean Connolly looks at an international study which asks: Is there consensus across evidence-based guidelines for the psychotropic drug management of bipolar disorder during the perinatal period?
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Katie Finning writes her debut elf blog on a recent systematic review which looks at adult mental health outcomes of adolescent depression; including depression, anxiety and suicidality in adults.
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Karen Wetherall summarises the new NatCen report on suicide and self-harm in Britain: researching risk and resilience using UK surveys.
Follow #SelfHarmData on Twitter for all the discussions from the ‘Using data to inform suicide and self-harm prevention’ event in London.
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Maria Loades writes her debut elf blog on a recent systematic review and meta-analysis on the long-term psychosocial outcomes of teenage depression, which finds that depression as a youth is linked to poor academic outcomes, unemployment and problems with relationships in adult life.
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Joe Barnby considers the findings of a recent meta-analysis of cross-sectional observational data, which explores the association of cannabis with cognitive functioning in adolescents and young adults.
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Megan Skelton explores a study that uses polygenic scores in the context of longitudinal developmental data, to characterise developmental trajectories and the role of neuropsychiatric genetic risk variants in early-onset depression.
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A group of UCL Mental Health Masters students summarise a recent cohort study of the individual and area-based socioeconomic factors associated with dementia incidence in England.
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Douglas Levinson on a genome-wide meta-analysis of depression in 807,553 individuals, which identifies 102 independent variants relating to the genetics of depression.
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