Cluster analysis reveals risk factors for repeated suicide attempts in a multi-ethnic Asian population

Choo, Carol, Diederich, Joachim, Song, Insu, and Ho, Roger (2014) Cluster analysis reveals risk factors for repeated suicide attempts in a multi-ethnic Asian population. Asian Journal of Psychiatry, 8. pp. 38-42.

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DOI: 10.1016/j.ajp.2013.10.001

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Abstract

This study explores underlying patterns in suicide risk factors using data mining techniques. Medical records of suicide attempters who were admitted to a teaching hospital in January 2004 – December 2006 were studied. Cluster analysis revealed hidden patterns for repeated and single attempters (n = 418). Repeated attempters had a more complex clinical picture. Symptoms of psychotic illness, borderline personality disorder, and psychosomatic complaints of insomnia and headaches, reports of adverse life events such as unemployment, divorce and quarrels, experience of negative feelings, and usage of alcohol were associated with risk of repeated overdoses with benzodiazepines and paracetamol. The findings have implications for suicide assessments and interventions.


Item ID:	31006
Item Type:	Article (Research - C1)
ISSN:	1876-2026
Keywords:	repeated suicide attempts; risk factors; data mining; cluster analysis; psychotic illness; borderline personality disorder
Date Deposited:	06 May 2014 23:04
FoR Codes:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 40% 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing @ 30% 17 PSYCHOLOGY AND COGNITIVE SCIENCES > 1701 Psychology > 170110 Psychological Methodology, Design and Analysis @ 30%
SEO Codes:	89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890201 Application Software Packages (excl. Computer Games) @ 50% 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920199 Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classified @ 50%
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