Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms
ObjectiveRumination and anxiety have been posited as correlates of smartphone dependence (SPD). However, little is known regarding how the components of both affect SPD symptoms at subtle levels. Therefore, we used the network analysis approach to identify the connections at a micro level to provide...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1506721/full |
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| author | Sen sen Zhang Sen sen Zhang Shao hong Yong Shao hong Yong Jia tai Chen |
| author_facet | Sen sen Zhang Sen sen Zhang Shao hong Yong Shao hong Yong Jia tai Chen |
| author_sort | Sen sen Zhang |
| collection | DOAJ |
| description | ObjectiveRumination and anxiety have been posited as correlates of smartphone dependence (SPD). However, little is known regarding how the components of both affect SPD symptoms at subtle levels. Therefore, we used the network analysis approach to identify the connections at a micro level to provide possible interventions for reducing SPD symptoms.MethodsUsing symptom-level network analysis, we used the ruminative response scale-10, the generalized anxiety disorder scale-7, and the mobile phone addiction index scale-17 to investigate Chinese preservice teachers (Mage = 21.1, N = 1160). Subsequently, we estimated a graphical lasso correlation network for these teachers, which encompassed rumination components, anxiety components, and SPD symptoms. Specifically, the central and bridge centralities within the network structure were examined for the impacts of rumination and anxiety on SPD symptoms.ResultsThe three intracluster connections of rumination, anxiety, and SPD were tighter than the intercluster, with structural connections in rumination and anxiety networks closer than the triggered SPD symptoms cluster. Importantly, reflection reactions towards “write down what you are thinking and analyze it” (a component of rumination) were identified as a central and bridging node that might be a target for intervention for SPD symptoms.ConclusionWe identify potential edge-bridging rumination and anxiety on SPD and locate highly central components within each cluster via network analysis. |
| format | Article |
| id | doaj-art-9a153aea5f8140d99198b1d0a6a07b4a |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-9a153aea5f8140d99198b1d0a6a07b4a2025-02-04T06:32:07ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-02-011610.3389/fpsyt.2025.15067211506721Network analysis of interactions of rumination and anxiety on smartphone dependence symptomsSen sen Zhang0Sen sen Zhang1Shao hong Yong2Shao hong Yong3Jia tai Chen4Faculty of Business Administration, Guangzhou Institute Of Science And Technology, Guangzhou, ChinaDepartment of Psychology, Institute of Teacher Education, Ningxia University, Yinchuan, ChinaFaculty of Business Administration, Guangzhou Institute Of Science And Technology, Guangzhou, ChinaDepartment of Psychology, Institute of Teacher Education, Ningxia University, Yinchuan, ChinaBusiness School, University of Exeter, Exeter, United KingdomObjectiveRumination and anxiety have been posited as correlates of smartphone dependence (SPD). However, little is known regarding how the components of both affect SPD symptoms at subtle levels. Therefore, we used the network analysis approach to identify the connections at a micro level to provide possible interventions for reducing SPD symptoms.MethodsUsing symptom-level network analysis, we used the ruminative response scale-10, the generalized anxiety disorder scale-7, and the mobile phone addiction index scale-17 to investigate Chinese preservice teachers (Mage = 21.1, N = 1160). Subsequently, we estimated a graphical lasso correlation network for these teachers, which encompassed rumination components, anxiety components, and SPD symptoms. Specifically, the central and bridge centralities within the network structure were examined for the impacts of rumination and anxiety on SPD symptoms.ResultsThe three intracluster connections of rumination, anxiety, and SPD were tighter than the intercluster, with structural connections in rumination and anxiety networks closer than the triggered SPD symptoms cluster. Importantly, reflection reactions towards “write down what you are thinking and analyze it” (a component of rumination) were identified as a central and bridging node that might be a target for intervention for SPD symptoms.ConclusionWe identify potential edge-bridging rumination and anxiety on SPD and locate highly central components within each cluster via network analysis.https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1506721/fullnetwork analysisruminationanxietysmartphone dependencepreservice teachers |
| spellingShingle | Sen sen Zhang Sen sen Zhang Shao hong Yong Shao hong Yong Jia tai Chen Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms Frontiers in Psychiatry network analysis rumination anxiety smartphone dependence preservice teachers |
| title | Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| title_full | Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| title_fullStr | Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| title_full_unstemmed | Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| title_short | Network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| title_sort | network analysis of interactions of rumination and anxiety on smartphone dependence symptoms |
| topic | network analysis rumination anxiety smartphone dependence preservice teachers |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1506721/full |
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