Co-occurrence of Common Biological and Behavioral Addictions: Using Network Analysis to Identify Central Addictions and Their Associations with Each Other.

The present study used network analysis to examine the network properties (network graph, centrality, and edge weights) comprising ten different types of common addictions (alcohol, cigarette smoking, drug, sex, social media, shopping, exercise, gambling, internet gaming, and internet use) controlli...

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Published in:International Journal of Mental Health & Addiction Vol. 23; no. 1; pp. 15 - 35
Main Authors: Gomez, Rapson, Brown, Taylor, Tullett-Prado, Deon, Stavropoulos, Vasileios
Format: Article
Published: Springer Nature Feb2025
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Feb2025
      vid: 23
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      pub: Springer Nature
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        183893110
        10.1007/s11469-022-00995-8
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        atl: Co-occurrence of Common Biological and Behavioral Addictions: Using Network Analysis to Identify Central Addictions and Their Associations with Each Other.
      aug:
        au:
          Gomez, Rapson
          Brown, Taylor
          Tullett-Prado, Deon
          Stavropoulos, Vasileios
        affil:
          https://ror.org/05qbzwv83 Federation University, Ballarat, Australia
          https://ror.org/04j757h98 Victoria University, Footscray, Australia
          https://ror.org/04gnjpq42 National and Kapodistrian University of Athens, Athens, Greece
      su:
        Compulsive gambling
        Compulsive behavior
        Exercise addiction
        Substance abuse
        Gambling
      sug:
        subj:
          Compulsive gambling
          Compulsive behavior
          Exercise addiction
          Substance abuse
          Other Gambling Industries
          Gambling
      keyword:
        Addictions
        Centrality
        Co-occurrence
        Edge weights
        Network analysis
        Addictions
        Centrality
        Co-occurrence
        Edge weights
        Network analysis
      ab: The present study used network analysis to examine the network properties (network graph, centrality, and edge weights) comprising ten different types of common addictions (alcohol, cigarette smoking, drug, sex, social media, shopping, exercise, gambling, internet gaming, and internet use) controlling for age and gender effects. Participants (N = 968; males = 64.3%) were adults from the general community, with ages ranging from 18 to 64 years (mean = 29.54 years; SD = 9.36 years). All the participants completed well-standardized questionnaires that together covered the ten addictions. The network findings showed different clusters for substance use and behavioral addictions and exercise. In relation to centrality, the highest value was for internet usage, followed by gaming and then gambling addiction. Concerning edge weights, there was a large effect size association between internet gaming and internet usage; a medium effect size association between internet usage and social media and alcohol and drugs; and several small and negligible effect size associations. Also, only 48.88% of potential edges or associations between addictions were significant. Taken together, these findings must be prioritized in theoretical models of addictions and when planning treatment of co-occurring addictions. Relatedly, as this study is the first to use network analysis to explore the properties of co-occurring addictions, the findings can be considered as providing new contributions to our understanding of the co-occurrence of common addictions.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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