Evidence map›Paper›PMID 29106281›Full record

ArticleJournal of abnormal psychology2017

Evidence that psychopathology symptom networks have limited replicability.

Miriam K Forbes, Aidan G C Wright, Kristian E Markon, Robert F Krueger

Open access · hybridAbstract read
In one paragraph

Article in Journal of abnormal psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 1 pooled it
36.3field-weighted citation impact, top 1% 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

137 citing papers in PubMed, 1 synthesis or guideline pooled it, 363 citations in OpenAlex.

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  10. Comparison of depressive symptoms between heterosexual and sexual minority university students: network analysis.Psicologia, reflexao e critica : revista semestral do Departamento de Psicologia da UFRGS · 2026
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77 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Miriam K ForbesDepartment of Psychiatry, University of Minnesota.
Aidan G C WrightDepartment of Psychology, University of Pittsburgh.
Kristian E MarkonDepartment of Psychological and Brain Sciences, University of Iowa.
Robert F KruegerDepartment of Psychology, University of Minnesota.
University of Minnesota · USUniversity of Iowa · USUniversity of Pittsburgh · US

Funding

EPIDEMIOLOGY-- NATIONAL COMORBIDITY SURVEY REPLICATIONU01MH060220 · NIMH · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI KESSLER, RONALD C · 1999 to 2010
$18.7M
Comorbidity: Substance Use Disorders and Other Psychiatric ConditionsT32DA037183 · NIDA · UNIVERSITY OF MINNESOTA · PI Anna Zilverstand · 2014 to 2026
$3.2M
National Institute of Drug AbuseNational Institute of Mental HealthNIDA NIH HHS T32 DA037183NIMH NIH HHS L30 MH101760NIMH NIH HHS U01 MH060220
6 · The paper itself

Abstract

Network analysis is quickly gaining popularity in psychopathology research as a method that aims to reveal causal relationships among individual symptoms. To date, 4 main types of psychopathology networks have been proposed: (a) association networks, (b) regularized concentration networks, (c) relative importance networks, and (d) directed acyclic graphs. The authors examined the replicability of these analyses based on symptoms of major depression and generalized anxiety between and within 2 highly similar epidemiological samples (i.e., the National Comorbidity Survey-Replication [n = 9282] and the National Survey of Mental Health and Wellbeing [n = 8841]). Although association networks were stable, the 3 other types of network analysis (i.e., the conditional independence networks) had poor replicability between and within methods and samples. The detailed aspects of the models-such as the estimation of specific edges and the centrality of individual nodes-were particularly unstable. For example, 44% of the symptoms were estimated as the "most influential" on at least 1 centrality index across the 6 conditional independence networks in the full samples, and only 13-21% of the edges were consistently estimated across these networks. One of the likely reasons for the instability of the networks is the predominance of measurement error in the assessment of individual symptoms. The authors discuss the implications of these findings for the growing field of psychopathology network research, and conclude that novel results originating from psychopathology networks should be held to higher standards of evidence before they are ready for dissemination or implementation in the field. (PsycINFO Database Record

Indexed as

Models, PsychologicalAdultAntisocial Personality DisorderAnxiety DisordersData Interpretation, StatisticalFemaleHumansMajor Depressive DisorderMaleMiddle AgedReproducibility of Results

Identifiers

PMID29106281
PMCPMC5749927
OpenAlexW2767417220

What OpenQuestion holds

Textmetadata
LicenceTDM
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.