Moderating the Influence of Current Intention to Improve Suicide Risk Prediction


When assessors evaluate a person's risk of completing suicide, the person's expressed current intention is one of the most influential factors. However, if people say they have no intention, this may not be true for a number of reasons. This paper explores the reliability of negative intention in data provided by mental-health services using the GRiST decision support system in England. It identifies features within a risk assessment record that can classify a negative statement regarding current intention of suicide as being reliable or unreliable. The algorithm is tested on previously conducted assessments, where outcomes found in later assessments do or do not match the initially stated intention. Test results show significant separation between the two classes. It means suicide predictions could be made more accurate by modifying the assessment process and associated risk judgement in accordance with a better understanding of the person's true intention.

Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
Additional Information: © 2018 American Medical Informatics Association. All Rights Reserved Funding: American Foundation for Suicide Prevention
Uncontrolled Keywords: Clinical Risk Judgment,Decision Support System,GRiST,Suicide Intention,Suicide Risk,Medicine(all)
Publication ISSN: 1942-597X
Full Text Link: https://www.ncb ... pubmed/28269925
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-02-10
Accepted Date: 2017-02-09
Authors: Zaher, Nawal A.
Buckingham, Christopher D. (ORCID Profile 0000-0002-3675-1215)



Version: Accepted Version

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