Evidence map›Paper›PMID 25576367›Full record

ArticlePsychiatry research2015

Comorbid substance use disorders in schizophrenia: a latent class approach.

Berit Kerner

Abstract read
In one paragraph

Article in Psychiatry research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

6 citing papers in PubMed, 26 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Berit KernerSemel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, USA. Electronic address: bkerner@mednet.ucla.edu.
University of California, Los Angeles · US

Funding

Symptom Dimensions in PsychosisK08MH074057 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KERNER, BERIT · 2005 to 2009
$872k
Parsing of Bipolar Disorders and Schizophrenia: A Latent Class ApproachR01MH085744 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KERNER, BERIT · 2010 to 2012
$723k
NIMH NIH HHS 3K08MH074057-05S1NIMH NIH HHS K08 MH074057NIMH NIH HHS R01 MH085744NIMH NIH HHS R01MH085744
6 · The paper itself

Abstract

Schizophrenia is a complex psychiatric disorder with a characteristic disease course and heterogeneous etiology. While substance use disorders and a family history of psychosis have individually been identified as risk factors for schizophrenia, it is less well understood if and how these factors are related. To address this deficiency, we examined the relationship between substance use disorders and family history of psychosis in a sample of 1219 unrelated patients with schizophrenia. The lifetime rate of substance use disorders in this sample was 50%, and 30% had a family history of psychosis. Latent class mixture modeling identified three distinct patient subgroups: (1) individuals with low probability of substance use disorders; (2) patients with drug and alcohol abuse, but no symptoms of dependence; and (3) patients with substance dependence. Substance use was related to being male, to a more severe disease course, and more acute symptoms at assessment, but not to an earlier age of onset of schizophrenia or a specific pattern of positive and negative symptoms. Furthermore, substance use in schizophrenia was not related to a family history of psychosis. The results suggest that substance use in schizophrenia is an independent risk factor for disease severity and onset.

Indexed as

AdultComorbidityDiagnosis, Dual (Psychiatry)FemaleHumansMaleMiddle AgedSchizophreniaSubstance-Related DisordersUnited StatesDependenceDisease courseFamily history of psychosisMajor depressive disorderSchizophreniaSubstance use disorders

Identifiers

PMID25576367
PMCPMC4378564
OpenAlexW2003919441

What OpenQuestion holds

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Registered trials

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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.