Literature DB >> 28471534

Predicting suicide with the SAD PERSONS scale.

Cara Katz1, Jason R Randall2, Jitender Sareen1,2,3, Dan Chateau3,4, Randy Walld4, William D Leslie4,5, JianLi Wang6,7, James M Bolton1,2,3,4.   

Abstract

BACKGROUND: Suicide is a major public health issue, and a priority requirement is accurately identifying high-risk individuals. The SAD PERSONS suicide risk assessment scale is widely implemented in clinical settings despite limited supporting evidence. This article aims to determine the ability of the SAD PERSONS scale (SPS) to predict future suicide in the emergency department.
METHODS: Five thousand four hundred sixty-two consecutive adults were seen by psychiatry consultation teams in two tertiary emergency departments with linkage to population-based administrative data to determine suicide deaths within 6 months, 1, and 5 years.
RESULTS: Seventy-seven (1.4%) individuals died by suicide during the study period. When predicting suicide at 12 months, medium- and high-risk scores on SPS had a sensitivity of 49% and a specificity of 60%; the positive and negative predictive values were 0.9 and 99%, respectively. Half of the suicides at both 6- and 12-month intervals were classified as low risk by SPS at index visit. The area under the curve at 12 months for the Modified SPS was 0.59 (95% confidence interval [CI] range 0.51-0.67). High-risk scores (compared to low risk) were significantly associated with death by suicide over the 5-year study period using the SPS (hazard ratio 2.49; 95% CI 1.34-4.61) and modified version (hazard ratio 2.29; 95% CI 1.24-2.29).
CONCLUSIONS: Although widely used in educational and clinical settings, these findings do not support the use of the SPS and Modified SPS to predict suicide in adults seen by psychiatric services in the emergency department.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  emergency psychiatry; epidemiology; suicide risk assessment

Mesh:

Year:  2017        PMID: 28471534     DOI: 10.1002/da.22632

Source DB:  PubMed          Journal:  Depress Anxiety        ISSN: 1091-4269            Impact factor:   6.505


  6 in total

Review 1.  Suicide prediction models: a critical review of recent research with recommendations for the way forward.

Authors:  Ronald C Kessler; Robert M Bossarte; Alex Luedtke; Alan M Zaslavsky; Jose R Zubizarreta
Journal:  Mol Psychiatry       Date:  2019-09-30       Impact factor: 15.992

2.  Predicting death by suicide following an emergency department visit for parasuicide with administrative health care system data and machine learning.

Authors:  Michael Sanderson; Andrew Gm Bulloch; JianLi Wang; Kimberly G Williams; Tyler Williamson; Scott B Patten
Journal:  EClinicalMedicine       Date:  2020-02-18

3.  Resampling to address inequities in predictive modeling of suicide deaths.

Authors:  Majerle Reeves; Harish S Bhat; Sidra Goldman-Mellor
Journal:  BMJ Health Care Inform       Date:  2022-04

4.  Development of a Checklist for Predicting Suicidality Based on Risk and Protective Factors: The Gwangju Checklist for Evaluation of Suicidality.

Authors:  Sung-Wan Kim; Woo-Young Park; Honey Kim; Min Jhon; Ju-Wan Kim; Hee-Ju Kang; Seon-Young Kim; Seunghyoung Ryu; Ju-Yeon Lee; Il-Seon Shin; Jae-Min Kim
Journal:  Psychiatry Investig       Date:  2022-06-15       Impact factor: 3.202

5.  Accuracy of risk scales for predicting repeat self-harm and suicide: a multicentre, population-level cohort study using routine clinical data.

Authors:  Sarah Steeg; Leah Quinlivan; Rebecca Nowland; Robert Carroll; Deborah Casey; Caroline Clements; Jayne Cooper; Linda Davies; Duleeka Knipe; Jennifer Ness; Rory C O'Connor; Keith Hawton; David Gunnell; Nav Kapur
Journal:  BMC Psychiatry       Date:  2018-04-25       Impact factor: 3.630

6.  Root causes of deaths by suicide among patients under the care of a mental health trust: thematic analysis.

Authors:  Opeyemi Odejimi; Kerry Webb; Dhruba Bagchi; George Tadros
Journal:  BJPsych Bull       Date:  2021-06
  6 in total

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