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...
| Published in: | International Journal of Mental Health & Addiction Vol. 23; no. 1; pp. 15 - 35 |
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| Main Authors: | , , , |
| Format: | Article |
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Springer Nature
Feb2025
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=183893110&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 183893110 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 15571874 46AW jtl: International Journal of Mental Health & Addiction issn: 15571874 maglogo: N pubinfo: dt: Feb2025 vid: 23 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 183893110 10.1007/s11469-022-00995-8 ppf: 15 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 980KB tig: 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 refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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