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      Association between suicidal symptoms and repeat suicidal behaviour within a sample of hospital-treated suicide attempters

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          Abstract

          Background

          Suicidal behaviour is the end result of the complex relation between many factors which are biological, psychological and environmental in nature. Network analysis is a novel method that may help us better understand the complex association between different factors.

          Aims

          To examine the relationship between suicidal symptoms as assessed by the Beck Scale for Suicide Ideation and future suicidal behaviour in patients admitted to hospital following a suicide attempt, using network analysis.

          Method

          Secondary analysis was conducted on previously collected data from a sample of 366 patients who were admitted to a Scottish hospital following a suicide attempt. Network models were estimated to visualise and test the association between baseline symptom network structure and suicidal behaviour at 15-month follow-up.

          Results

          Network analysis showed that the desire for an active attempt was found to be the most central, strongly related suicide symptom. Of the 19 suicide symptoms that were assessed at baseline, 10 symptoms were directly related to repeat suicidal behaviour. When comparing baseline network structure of repeaters ( n=94) with the network of non-repeaters ( n=272), no significant differences were found.

          Conclusions

          Network analysis can help us better understand suicidal behaviour by visualising the complex relation between relevant symptoms and by indicating which symptoms are most central within the network. These insights have theoretical implications as well as informing the assessment and treatment of suicidal behaviour.

          Declaration of interest

          None.

          Copyright and usage

          © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

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          Most cited references19

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          Sparse inverse covariance estimation with the graphical lasso.

          We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics.
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            • Record: found
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            • Article: not found

            Assessment of suicidal intention: the Scale for Suicide Ideation.

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              Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential

              Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method – and research results based on it – are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and suicidal ideation are distinct phenomena that differ from each other in important dimensions such as underlying biology, impact on impairment, and risk factors. Furthermore, specific life events predict increases in particular depression symptoms, and there is evidence for direct causal links among symptoms. We suggest that the pervasive use of sum-scores to estimate depression severity has obfuscated crucial insights and contributed to the lack of progress in key research areas such as identifying biomarkers and more efficacious antidepressants. The analysis of individual symptoms and their causal associations offers a way forward. We offer specific suggestions with practical implications for future research. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0325-4) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                BJPsych Open
                BJPsych Open
                bjporcpsych
                bjporcpsych
                BJPsych Open
                The Royal College of Psychiatrists
                2056-4724
                4 May 2017
                May 2017
                : 3
                : 3
                : 120-126
                Affiliations
                [1] Derek P. de Beurs, PhD, Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands
                [2] Claudia D. van Borkulo, PhD, Department of Psychology, Psychological Methods Group, University of Amsterdam, The Netherlands
                [3] Rory C. O’Connor, PhD, Suicidal Behaviour Research Laboratory, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
                Author notes
                Correspondence: Derek P. de Beurs, Netherlands Institute for Health Services Research (NIVEL), The Netherlands. Email: d.debeurs@ 123456nivel.nl
                Article
                bjporcpsych004275
                10.1192/bjpo.bp.116.004275
                5415676
                28507771
                5e0a79a5-c41b-4a14-8515-edacc40124a5
                © 2017 The Royal College of Psychiatrists

                This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 6 November 2016
                : 28 March 2017
                : 29 March 2017
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