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

De Beurs, D. P., Van Borkulo, C. D. & O'Connor, R. C., 1-May-2017, In : BJPsych Open. 3, 3, p. 120-126 7 p.

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)120-126
Number of pages7
JournalBJPsych Open
Issue number3
Publication statusPublished - 1-May-2017
Externally publishedYes

Download statistics

No data available

ID: 92705694