ArticleAddictive behaviors2022
Cross-sectional and longitudinal AUD symptom networks: They tell different stories.
Article in Addictive behaviors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of symptom-level networks of alcohol use disorder.Addiction (Abingdon, England) · 2025Pooled it
- Common cause versus dynamic mutualism: Insights into ADHD's common comorbidities.JCPP advances · 2026Article
- A systematic review of operational research modelling for alcohol consumption and its consequences.Health systems (Basingstoke, England) · 2026Review
- The interplay of alcohol use symptoms and sociodemographic factors in the HELIUS study: A network perspective.Social psychiatry and psychiatric epidemiology · 2025Article
- Longitudinal Association Between Posttraumatic Stress Symptoms and Depression Symptoms Among Chinese Adolescents During COVID-19: Evidence from Network Perspective.Child psychiatry and human development · 2025Article
- Core Symptoms and Dynamic Interactions of Depressive Symptoms in Older Chinese Adults: A Longitudinal Network Analysis.Depression and anxiety · 2025Article
- Longitudinal relationship between oppositional defiant disorder symptoms and attention-deficit/hyperactivity disorder symptoms in Chinese children: insights from cross-lagged panel network analyses.European child & adolescent psychiatry · 2024Article
- Network analysis of DSM-5 criteria for gambling disorder: considering sex differences in a large clinical sample.European psychiatry : the journal of the Association of European Psychiatrists · 2024Article
- Age Differences in the Associations Between Interpersonal Relationships and Short-Form Video Addiction Symptoms: A Network Analysis.Psychology research and behavior management · 2024Article
- Predictors of symptom course in alcohol use disorder.Alcohol, clinical & experimental research · 2023Article
- The Predictive Role of Tolerance and Health Problems in Problem Gambling: A Cross-Sectional and Cross-Lagged Network Analyses.Journal of gambling studies · 2023Article
- A Longitudinal Network Analysis of the Interactions of Risk and Protective Factors for Suicidal Potential in Early Adolescents.Journal of youth and adolescence · 2023Article
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4 authors.
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Abstract
Modern theoretical models of Alcohol Use Disorder (AUD) highlight the different functional roles played by various mechanisms associated with different symptoms. Symptom network models (SNMs) offer one approach to modeling AUD symptomatology in a way that could reflect these processes and provide important information on the progression and persistence of disorder. However, much of the research conducted using SNMs relies on cross-sectional data, which has raised questions regarding the extent they reflect dynamic processes. The current study aimed to (a) examine symptom networks of AUD and (b) compare the extent to which cross-sectional network models had similar structures and interpretations as longitudinal network models. 17,360 participants from Wave 1 (2001-2002) and Wave 2 (2003-2004) of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC) were used to model cross-sectional and longitudinal AUD symptom networks. The cross-sectional analyses demonstrate high replicability across waves and central symptoms consistent with other cross-sectional studies on addiction networks. The longitudinal network shared much less similarity than the cross-sectional networks and had a substantially different structure. Given the increasing attention given to the network perspective in psychopathology research, the results of this study raise concerns about interpreting cross-sectional symptom networks as representative of temporal changes occurring within a psychological disorder. We conclude that the psychological symptom network literature should be bolstered with additional research on longitudinal network models.
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