{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T12:44:25Z","timestamp":1777725865934,"version":"3.51.4"},"reference-count":56,"publisher":"IMR Press","issue":"2","license":[{"start":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T00:00:00Z","timestamp":1773014400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Alpha Psychiatry"],"abstract":"<jats:p>Background: Substance-related and behavioral addictions frequently co-occur and are increasingly conceptualized as part of an interconnected psychopathological framework. Addictive behaviors are linked to internalizing symptoms, including depression, anxiety, and stress, through shared vulnerability. Although impulsivity, anhedonia, and stress-related processes have been proposed as transdiagnostic factors, their relative roles as central or bridging mechanisms remain unclear. This study aimed to clarify the network structure of multiple addictions by jointly modeling substance-related and behavioral addictions with multidimensional psychological features. Methods: A total of 169 university students completed standardized self-report measures assessing four substance-related addictions (alcohol, tobacco, cannabis, cocaine) and six behavioral addictions (gambling, shopping, gaming, eating, sexual activity, and work), alongside measures of impulsivity, anhedonia, depression, anxiety, stress, chronic stress, and childhood adversities. Three Extended Bayesian Information Criterion Graphical Least Absolute Shrinkage and Selection Operator (EBICglasso) network models were estimated: (i) an addiction-only network, (ii) an addictions-psychometric features network, and (iii) a focused network integrating selected addictions with affective symptoms, stress, and adversities. Centrality, bridge indices, and predictability were evaluated. Results: Substance-related and behavioral addictions formed a coherent and interconnected network, with alcohol (0.89), sexual activity (0.77), and cannabis (0.70) emerging as the most central hubs. Impulsivity and anxiety functioned as the primary bridge nodes linking addictive behaviors with internalizing symptomatology, with anxiety exhibiting the highest bridge strength (0.29), followed by impulsivity (0.20). The affective distress cluster, comprising depression, anxiety, and stress, demonstrated the strongest internal connectivity and the highest predictability (R2), with explained variance values of R2 = 0.33 for depression and R2 = 0.30 for both anxiety and stress. Stress exposure and childhood adversity showed cross-domain connections involving sexual activity and alcohol use. Conclusion: This study models substance-related and behavioral addictions together with internalizing symptoms, impulsivity, anhedonia, and stress-related factors to examine how addictive behaviors are organized within an interconnected network. Alcohol, cannabis, and sexual activity showed relatively high connectivity, while impulsivity and anxiety were consistently positioned as bridge variables linking addictive behaviors with affective distress. These findings provide a descriptive transdiagnostic framework in which shared regulatory traits emerge as key organizing features of addiction comorbidity; however, their potential clinical relevance remains hypothesis-generating and requires validation in longitudinal and clinically diagnosed samples.<\/jats:p>","DOI":"10.31083\/ap49511","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T10:41:17Z","timestamp":1777459277000},"source":"Crossref","is-referenced-by-count":0,"title":["Phenotypic Clustering of Addictions Reveals Impulsivity Links to Internalizing Disorders: A Network Analysis"],"prefix":"10.31083","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4515-7530","authenticated-orcid":true,"given":"Ard\u0131l Bayram","family":"\u015eahin","sequence":"first","affiliation":[{"name":"Graduate School of Health Sciences, Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"},{"name":"Research Center for Translational Medicine (KUTTAM), Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6816-5081","authenticated-orcid":true,"given":"Yusuf Huseyin","family":"Berrak","sequence":"additional","affiliation":[{"name":"School of Medicine, Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2724-589X","authenticated-orcid":true,"given":"Duru","family":"Besen","sequence":"additional","affiliation":[{"name":"School of Medicine, Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4933-1479","authenticated-orcid":true,"given":"Hilal","family":"Askin","sequence":"additional","affiliation":[{"name":"School of Medicine, Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0318-2770","authenticated-orcid":true,"given":"Hale","family":"Yapici Eser","sequence":"additional","affiliation":[{"name":"Research Center for Translational Medicine (KUTTAM), Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"},{"name":"Department of Psychiatry, School of Medicine, Ko\u00e7 University, 34010 Istanbul, T\u00fcrkiye"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16242","published-online":{"date-parts":[[2026,3,9]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","unstructured":"Konkol\u00ff Thege B, Hodgins DC, Wild TC. 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