Journal article
Screening to Identify Groups of Pediatric Emergency Department Patients Using Latent Class Analysis of Reported Suicidal Ideation and Behavior and Non-Suicidal Self-Injury
Archives of suicide research, v 22(1)
01 Jan 2018
PMID: 28121237
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Latent class analysis of medical records data from 3,523 emergency department (ED) patients (ages 14-24; 31% Caucasian; 67% female) distinguished 6 groups with varying histories of suicidal ideation and behavior based on items endorsed on the Behavioral Health Screen, a web based, nurse-initiated screening tool. As expected, the more severe suicidality groups reported higher levels of depressive symptoms, traumatic distress, and substance abuse symptoms. Findings support the validity of the BHS and its utility as a medical decision tool to help ED staff evaluate the severity of patients' suicidality.
Metrics
Details
- Title
- Screening to Identify Groups of Pediatric Emergency Department Patients Using Latent Class Analysis of Reported Suicidal Ideation and Behavior and Non-Suicidal Self-Injury
- Creators
- Joanna Herres - Coll New Jersey, Dept Psychol, Ewing, NJ USATamar Kodish - Univ Calif Los Angeles, Dept Psychol, Los Angeles, CA USAJoel Fein - Childrens Hosp Philadelphia, Dept Psychiat, Philadelphia, PA 19104 USAGuy Diamond - Drexel University
- Publication Details
- Archives of suicide research, v 22(1)
- Publisher
- Taylor & Francis
- Number of pages
- 12
- Grant note
- 5U79SM058386; 1U79SM060387; 1U79SM061750 / SAMHSA's, Garrett Lee Smith Suicide Prevention Programs
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Center for Family Intervention Science
- Web of Science ID
- WOS:000425672700003
- Scopus ID
- 2-s2.0-85013413859
- Other Identifier
- 991019168808804721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Psychiatry
- Psychology
- Psychology, Multidisciplinary