skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Developing a risk prediction model for death at first suicide attempt-Identifying risk factors from Thailand's national suicide surveillance system data

PloS one, 2024, Vol.19 (4), p.e0297904-e0297904 [Peer Reviewed Journal]

Copyright: © 2024 Arunpongpaisal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;2024 Arunpongpaisal et al 2024 Arunpongpaisal et al ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0297904 ;PMID: 38598456

Full text available

Citations Cited by
  • Title:
    Developing a risk prediction model for death at first suicide attempt-Identifying risk factors from Thailand's national suicide surveillance system data
  • Author: Arunpongpaisal, Suwanna ; Assanangkornchai, Sawitri ; Chongsuvivatwong, Virasakdi
  • Subjects: Humans ; Logistic Models ; Male ; Medicine and Health Sciences ; Middle Aged ; People and Places ; Physical Sciences ; Research and Analysis Methods ; Risk Factors ; Suicidal Ideation ; Suicide, Attempted ; Thailand - epidemiology
  • Is Part Of: PloS one, 2024, Vol.19 (4), p.e0297904-e0297904
  • Description: More than 60% of suicides globally are estimated to take place in low- and middle-income nations. Prior research on suicide has indicated that over 50% of those who die by suicide do so on their first attempt. Nevertheless, there is a dearth of knowledge on the attributes of individuals who die on their first attempt and the factors that can predict mortality on the first attempt in these regions. The objective of this study was to create an individual-level risk-prediction model for mortality on the first suicide attempt. We analyzed records of individuals' first suicide attempts that occurred between May 1, 2017, and April 30, 2018, from the national suicide surveillance system, which includes all of the provinces of Thailand. Subsequently, a risk-prediction model for mortality on the first suicide attempt was constructed utilizing multivariable logistic regression and presented through a web-based application. The model's performance was assessed by calculating the area under the receiver operating curve (AUC), as well as measuring its sensitivity, specificity, and accuracy. Out of the 3,324 individuals who made their first suicide attempt, 50.5% of them died as a result of that effort. Nine out of the 21 potential predictors demonstrated the greatest predictive capability. These included male sex, age over 50 years old, unemployment, having a depressive disorder, having a psychotic illness, experiencing interpersonal problems such as being aggressively criticized or desiring plentiful attention, having suicidal intent, and displaying suicidal warning signals. The model demonstrated a good predictive capability, with an AUC of 0.902, a sensitivity of 84.65%, a specificity of 82.66%, and an accuracy of 83.63%. The implementation of this predictive model can assist physicians in conducting comprehensive evaluations of suicide risk in clinical settings and devising treatment plans for preventive intervention.
  • Publisher: United States: Public Library of Science
  • Language: English
  • Identifier: EISSN: 1932-6203
    DOI: 10.1371/journal.pone.0297904
    PMID: 38598456
  • Source: PLoS (Open access)
    Geneva Foundation Free Medical Journals at publisher websites
    MEDLINE
    PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait