Citation

Modai I, Kuperman J, Goldberg I, Goldish M, Mendel S. Med. Inform. Internet Med. 2004; 29(1): 65-74.

Affiliation

Sha'ar Menashe Mental Health Center, Institute of Psychiatric Studies, Hadera, Israel. modai@shaar-menashe.org.il

Copyright

(Copyright © 2004, Society for the Internet in Medicine, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/14639230410001662651

PMID

15204611

Abstract

PRIMARY OBJECTIVES: There are many known suicide risk factors (SRF) common to major psychiatric disorders, but their impact on suicide vulnerability remains unclear. We used FALCON (Fuzzy Adaptive Learning Control Network) to evaluate those impacts. METHODS: Staff psychiatrists completed computerized suicide risk scales (CSRS-III) including 21 SRF for 612 patients. Diagnoses were: schizophrenia, schizoaffective, major depression, anxiety disorder, bipolar affective disorder, personality disorder, organic brain syndromes, delusional disorder and other diagnoses. An optimal trained FALCON was obtained by running the network 10 times with 552 CSRS-III, validating with the balance. Medically serious suicide attempts (the vulnerability factor) served as the target variable. The significance of each variable in the trained network was determined by the magnitude of the change in output as affected by the consecutive change in all points of the variable input, then calculating the mean variance of all cases. The direction of influence was determined by the input on the entire scale of each variable, point by point, across all cases, then calculating the mean of all outputs. RESULTS: The impact and direction of influence of the various SRF differed for each diagnosis. CONCLUSION: Evaluation of the individual patient with his/her specific impact profile, determination of direction of influence of the corresponding SRF's may assist in increasing the accuracy of individual suicide risk assessment.

Language: en