Evidence map›Paper›PMID 34231122›Full record

ArticleJournal of gambling studies2022

Testing the Validity of the Pathways Model: A Latent Class Analysis of Potential Pathological Gambling Subtypes in a Non-Treatment Sample.

Donald W Black, Jeff Allen

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In one paragraph

Article in Journal of gambling studies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

Donald W BlackDepartment of Psychiatry, 2-126b MEB/Psychiatry Research, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA. donald-black@uiowa.edu.
Jeff AllenDepartment of Psychiatry, 2-126b MEB/Psychiatry Research, University of Iowa Carver College of Medicine, Iowa City, IA, 52242, USA.

Funding

Family-Genetic Study of Pathological GamblingR01DA021361 · NIDA · UNIVERSITY OF IOWA · PI BLACK, DONALD W. · 2005 to 2009
$2.3M
A Follow-up Study of Addictions and Co-Occurring Disorders in Older AdultsR01AG037132 · NIA · UNIVERSITY OF IOWA · PI BLACK, DONALD W. · 2011 to 2015
$1.6M
NIH HHS RO1AG037132NIH HHS RO1DA021361
6 · The paper itself

Abstract

Latent class analysis (LCA) was used to test the validity of the Pathways Model in 285 subjects with DSM-IV pathological gambling (PG). In addition to identifying three subtypes that roughly correspond with those described in the model (Behaviorally Conditioned, or BC, Emotionally Vulnerable, or EV, Antisocial-Impulsivist, or AI), LCA identified a fourth class, termed the Antisocial Drinker, or AD, characterized by high rates of antisociality, conduct disorder, and alcohol use disorder. BC gamblers comprised 45% of the sample, followed by EV (24%), AD (22%), and AI (9%) gamblers. Women were more likely to be EV gamblers (OR = 1.89) and less likely to be AD gamblers (OR = 0.46). Those who had attempted suicide were more likely to be EV (OR = 3.06) or AI (OR = 3.05) gamblers and less likely to be BC (OR = 0.37) or AD gamblers (OR = 0.50). Greater childhood maltreatment was associated with AD (standardized OR = 1.81) and AI (standardized OR = 1.43) gamblers. Individuals with later PG onset were less likely to be AI gamblers (standardized OR = 0.48). Individuals who preferred slots were more likely to be EV gamblers (OR = 1.83) and less likely to be AD gamblers (OR = 0.33). The BC subtype was associated with better health outcomes, better social functioning, less childhood maltreatment, and less severe PG. The AI subtype was associated with worse health outcomes, worse social functioning, and higher PG severity. The findings provide a better understanding PG heterogeneity that could be relevant to clinical management.

Indexed as

GamblingAntisocial Personality DisorderDiagnostic and Statistical Manual of Mental DisordersFemaleHumansLatent Class AnalysisSurveys and QuestionnairesGamblingLatent class analysisPathways modelSubtypes

Identifiers

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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.