{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T07:44:19Z","timestamp":1785743059463,"version":"3.56.0"},"reference-count":85,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behav. Sci.","Behavioral Sciences"],"abstract":"<jats:p>Smartphone addiction (SA) has become a widespread issue and is consistently linked to a range of internalizing problems, including anxiety, depression, and sleep disorders. Previous studies have primarily focused on the overall association between SA and internalizing problems; however, differences in symptom patterns and potential intervention targets across SA risk groups remain unclear. This study recruited 1411 adults (Mage = 28.87 years, 45.64% female) who completed the survey. Data analysis was conducted using latent profile analysis and network analysis with simulation-based techniques. Latent profile analysis identified low-, moderate-, and high-SA groups. \u201cAnxiety and panic\u201d was the primary central node in low- and moderate-SA groups, whereas \u201cSleep disturbances\u201d was the most central node in the high-SA group. Central bridge symptoms varied by SA severity: the \u201cDepressed mood index\u201d in the moderate- and high-SA groups and the \u201cSomatic symptoms index\u201d in the low-SA group. Simulation analyses identified specific anxiety and sleep nodes as candidate intervention targets, whose modeled changes were associated with variations in overall internalizing problems. Optimal targets differed by SA severity, generating hypotheses for future prospective research. These findings highlight the potential value of severity-sensitive, symptom-focused intervention strategies for preventing and alleviating internalizing problems across varying levels of SA.<\/jats:p>","DOI":"10.3390\/bs16081318","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T06:17:40Z","timestamp":1785737860000},"page":"1318","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Differences in Internalizing Problems Across Risk Groups of Smartphone Addiction: Simulation-Based Network Analysis of Intervention Targets"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8842-4118","authenticated-orcid":false,"given":"Yi","family":"Huang","sequence":"first","affiliation":[{"name":"School of Humanities and Social Sciences, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenwu","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Humanities and Social Sciences, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihui","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Humanities and Social Sciences, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1200\/JCO.22.00699","article-title":"Smartphone psychotherapy reduces fear of cancer recurrence among breast cancer survivors: A fully decentralized randomized controlled clinical trial (J-SUPPORT 1703 Study)","volume":"41","author":"Akechi","year":"2023","journal-title":"Journal of Clinical Oncology"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Alotaibi, M. 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