Evidence map›Paper›PMID 37261240›Full record

ArticleFrontiers in public health2023

High suicidality predicts overdose events among people with substance use disorder: A latent class analysis.

Renae D Schmidt, Viviana E Horigian, Dikla Shmueli-Blumberg, Kathryn Hefner, Judith Feinberg, Radhika Kondapaka, Daniel J Feaster, Rui Duan, Sophia Gonzalez, Carly Davis and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Comorbidities of substance use: Opportunities realized and future needs.Journal of substance use and addiction treatment · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Renae D SchmidtDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Viviana E HorigianDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Dikla Shmueli-BlumbergThe Emmes Company, LLC, Rockville, MD, United States.
Kathryn HefnerThe Emmes Company, LLC, Rockville, MD, United States.
Judith FeinbergDepartments of Behavioral Medicine and Psychiatry and Medicine/Infectious Diseases, West Virginia University School of Medicine, Morgantown, WV, United States.
Radhika KondapakaThe Emmes Company, LLC, Rockville, MD, United States.
Daniel J FeasterDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Rui DuanDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Sophia GonzalezDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Carly DavisDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Ashley VenaThe Emmes Company, LLC, Rockville, MD, United States.
Rodrigo Marín-NavarreteDivision of Research and Translational Education, Centros de Integración Juvenil A.C, Mexico City, Mexico.
Susan TrossDepartment of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States.
University of Miami · USEmmes (United States) · USColumbia University Irving Medical Center · USWest Virginia University · US

Funding

Project-003UG1DA013035 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Aimee N Campbell, Jennifer McNeely · 2015 to 2026
$130.3M
West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Reagan Curtis · 2012 to 2026
$81.0M
The Florida Node Alliance of the National Drug Abuse Treatment Clinical Trials NetworkUG1DA013720 · NIDA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Daniel J Feaster, Viviana Elizabeth Horigian · 2015 to 2026
$50.6M
Project-008UG1DA049436 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Jane M. Liebschutz, Erin L Winstanley · 2019 to 2026
$10.5M
Training Program on HIV and Substance Use in the Criminal Justice SystemT32DA037801 · NIDA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Nabila El-Bassel, Lisa R Metsch · 2014 to 2026
$5.7M
NIDA NIH HHS T32 DA037801NIDA NIH HHS UG1 DA013035NIDA NIH HHS UG1 DA013720NIDA NIH HHS UG1 DA049436NIGMS NIH HHS U54 GM104942
6 · The paper itself

Abstract

Introduction: Suicide is the tenth leading cause of death in the United States and continues to be a major public health concern. Suicide risk is highly prevalent among individuals with co-occurring substance use disorders (SUD) and mental health disorders, making them more prone to adverse substance use related outcomes including overdose. Identifying individuals with SUD who are suicidal, and therefore potentially most at risk of overdose, is an important step to address the synergistic epidemics of suicides and overdose fatalities in the United States. The current study assesses whether patterns of suicidality endorsement can indicate risk for substance use and overdose. Methods: Latent class analysis (LCA) was used to assess patterns of item level responses to the Concise Health Risk Tracking Self-Report (CHRT-SR), which measures thoughts and feelings associated with suicidal propensity. We used data from 2,541 participants with SUD who were enrolled across 8 randomized clinical trials in the National Drug Abuse Treatment Clinical Trials Network from 2012 to 2021. Characteristics of individuals in each class were assessed, and multivariable logistic regression was performed to examine class membership as a predictor of overdose. LCA was also used to analyze predictors of substance use days. Results: Three classes were identified and discussed: Class (1) Minimal Suicidality, with low probabilities of endorsing each CHRT-SR construct; Class (2) Moderate Suicidality, with high probabilities of endorsing pessimism, helplessness, and lack of social support, but minimal endorsement of despair or suicidal thoughts; and Class (3) High Suicidality with high probabilities of endorsing all constructs. Individuals in the High Suicidality class comprise the highest proportions of males, Black/African American individuals, and those with a psychiatric history and baseline depression, as compared with the other two classes. Regression analysis revealed that those in the High Suicidality class are more likely to overdose as compared to those in the Minimal Suicidality class ( Conclusion: Suicidality is an essential factor to consider when building strategies to screen, identify, and address individuals at risk for overdose. The integration of detailed suicide assessment and suicide risk reduction is a potential solution to help prevent suicide and overdose among people with SUD.

Indexed as

Substance-Related DisordersSuicideDepressionHumansLatent Class AnalysisMaleSuicidal IdeationUnited Statesco-occurring disordersoverdosesubstance usesubstance use disordersuicidalitysuicide risk

Identifiers

PMID37261240
PMCPMC10228506
OpenAlexW4376956171

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.