Literature DB >> 35304235

Predictors of nonfatal suicide attempts within 30 days of discharge from psychiatric hospitalization: Sex-specific models developed using population-based registries.

Rachel L Zelkowitz1, Tammy Jiang2, Erzsébet Horváth-Puhó3, Amy E Street4, Timothy L Lash5, Henrik T Sørensen3, Anthony J Rosellini6, Jaimie L Gradus7.   

Abstract

BACKGROUND: Risk for nonfatal suicide attempts is heightened in the month after psychiatric hospitalization discharge. Investigations of factors associated with such attempts are limited.
METHODS: We conducted a case-subcohort study using data from Danish medical, administrative, and social registries to develop sex-specific risk models using two machine learning methods: classification trees and random forests. Cases included individuals who received a diagnostic code for a nonfatal suicide attempt within 30 days of discharge following a psychiatric hospitalization between January 1, 1995 and December 31, 2015 (n = 3166, 56.5% female). The comparison subcohort consisted of a 5% random sample of individuals living in Denmark (n = 24,559, 51.3% female) on January 1, 1995 who had a psychiatric hospitalization during the study period.
RESULTS: Histories of self-poisoning, substance-related disorders, and eating disorders were important predictors of nonfatal suicide attempt among women, with notable interactions observed between age, self-poisoning history, and other characteristics (e.g., medication use). Self-poisoning, substance-related disorders, and severe stress reactions were among the most important variables for men, with key interactions noted between self-poisoning history, age, major depressive disorder diagnosis, and prescription classes. LIMITATIONS: Findings are based on Danish administrative data, which may be subject to inaccuracies, missingness, etc. It is unclear whether results would generalize to other populations.
CONCLUSIONS: Markers of behavioral dysregulation were important predictors of nonfatal suicide attempts in the 30 days after psychiatric hospitalization discharge for both sexes. Examining risk markers for nonfatal suicide attempt following discharge is important to enhance support for this vulnerable population. Published by Elsevier B.V.

Entities:  

Keywords:  Administrative health records; Case-cohort study; Machine learning; Psychiatric hospitalization; Suicide attempt

Mesh:

Year:  2022        PMID: 35304235      PMCID: PMC9062818          DOI: 10.1016/j.jad.2022.03.034

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   6.533


  40 in total

1.  Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).

Authors:  Ronald C Kessler; Christopher H Warner; Christopher Ivany; Maria V Petukhova; Sherri Rose; Evelyn J Bromet; Millard Brown; Tianxi Cai; Lisa J Colpe; Kenneth L Cox; Carol S Fullerton; Stephen E Gilman; Michael J Gruber; Steven G Heeringa; Lisa Lewandowski-Romps; Junlong Li; Amy M Millikan-Bell; James A Naifeh; Matthew K Nock; Anthony J Rosellini; Nancy A Sampson; Michael Schoenbaum; Murray B Stein; Simon Wessely; Alan M Zaslavsky; Robert J Ursano
Journal:  JAMA Psychiatry       Date:  2015-01       Impact factor: 21.596

Review 2.  Family psychology and the psychology of men and masculinities.

Authors:  Ronald F Levant
Journal:  J Fam Psychol       Date:  2017-02

Review 3.  Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research.

Authors:  Joseph C Franklin; Jessica D Ribeiro; Kathryn R Fox; Kate H Bentley; Evan M Kleiman; Xieyining Huang; Katherine M Musacchio; Adam C Jaroszewski; Bernard P Chang; Matthew K Nock
Journal:  Psychol Bull       Date:  2016-11-14       Impact factor: 17.737

Review 4.  Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning.

Authors:  Tal Yarkoni; Jacob Westfall
Journal:  Perspect Psychol Sci       Date:  2017-08-25

5.  Predicting psychiatric readmission: sex-specific models to predict 30-day readmission following acute psychiatric hospitalization.

Authors:  Lucy Church Barker; Andrea Gruneir; Kinwah Fung; Nathan Herrmann; Paul Kurdyak; Elizabeth Lin; Paula A Rochon; Dallas Seitz; Valerie H Taylor; Simone N Vigod
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2017-11-09       Impact factor: 4.328

6.  Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

Authors:  Jaimie L Gradus; Anthony J Rosellini; Erzsébet Horváth-Puhó; Amy E Street; Isaac Galatzer-Levy; Tammy Jiang; Timothy L Lash; Henrik T Sørensen
Journal:  JAMA Psychiatry       Date:  2020-01-01       Impact factor: 21.596

7.  Perceived Coercion During Admission Into Psychiatric Hospitalization Increases Risk of Suicide Attempts After Discharge.

Authors:  Joshua T Jordan; Dale E McNiel
Journal:  Suicide Life Threat Behav       Date:  2019-06-04

8.  Data Resource Profile: The Danish National Prescription Registry.

Authors:  Anton Pottegård; Sigrun Alba Johannesdottir Schmidt; Helle Wallach-Kildemoes; Henrik Toft Sørensen; Jesper Hallas; Morten Schmidt
Journal:  Int J Epidemiol       Date:  2017-06-01       Impact factor: 7.196

9.  Danish registers on personal labour market affiliation.

Authors:  Flemming Petersson; Mikkel Baadsgaard; Lau Caspar Thygesen
Journal:  Scand J Public Health       Date:  2011-07       Impact factor: 3.021

Review 10.  Supervised Machine Learning: A Brief Primer.

Authors:  Tammy Jiang; Jaimie L Gradus; Anthony J Rosellini
Journal:  Behav Ther       Date:  2020-05-16
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