Internet addiction and depressive symptoms among nursing students: A network analysis with implications for nursing education.
Internet addiction and depressive symptoms co-occur frequently among nursing students, threatening their well-being and academic success in a demanding educational environment. The underlying symptom dynamics, however, remain unclear. Network analysis can identify key symptom interactions, providing...
| Publicado en: | Nurse Education Today Vol. 157 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189515784&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189515784 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02606917 8IS jtl: Nurse Education Today issn: 02606917 maglogo: N pubinfo: dt: Feb2026 vid: 157 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 189515784 189515784 189515784 10.1016/j.nedt.2025.106913 189515784 ppct: 1 formats: tig: atl: Internet addiction and depressive symptoms among nursing students: A network analysis with implications for nursing education. aug: au: Li, Yuan Luo, Biru Shi, Jing Chen, Miao Fu, Mei Rosemary Liao, Shujuan affil: Department of Nursing, West China Second University Hospital, Sichuan University, Chengdu, China sug: subj: Internet Addiction Evaluation Behavior, Addictive Evaluation Students, Nursing Psychosocial Factors Education, Nursing Student Attitudes Evaluation Depression Symptoms Psychological Well-Being Academic Performance China Human Male Female Descriptive Statistics Multicenter Studies Cross Sectional Studies Psychological Tests Questionnaires Sex Factors Emotional Regulation Self Concept Fatigue Mental Health Professional Development Male Female ab: Internet addiction and depressive symptoms co-occur frequently among nursing students, threatening their well-being and academic success in a demanding educational environment. The underlying symptom dynamics, however, remain unclear. Network analysis can identify key symptom interactions, providing an empirical basis for targeted interventions and support strategies within nursing education. This study aimed to (1) identify central symptoms within the Internet addiction-depressive symptom network, (2) detect bridge symptoms connecting distinct symptom clusters, and (3) examine gender-specific network patterns among nursing students. A multicenter cross-sectional study. Fourteen universities across seven major geographical regions of China. 6019 nursing students recruited through two-stage sampling. Data were collected between April and July 2024 using the 6-item Internet Addiction Test and the 9-item Patient Health Questionnaire. Network analysis was performed to estimate symptom networks, identify central and bridge symptoms, and examine gender-specific patterns. Analysis of 5984 valid responses revealed a stable network comprising 15 nodes with 80 non-zero edges. Fatigue/low energy (Expected Influence [EI] = 1.497) and Internet preoccupation (EI = 1.211) emerged as the most central symptoms in the network, while offline emotional dysregulation (bridge EI = 0.234) served as the primary bridge symptom. Gender comparisons revealed significant structural differences (P = 0.049); regarding local connectivity patterns, males showed stronger connections in behavioral control failure and physiological-emotional instability, and females exhibited elevated connectivity in academic impairment and self-concept preservation. Fatigue/low energy and Internet preoccupation emerged as central symptoms, with offline emotional dysregulation as the primary bridge. Gender-specific network patterns demonstrated distinct symptom interactions, suggesting that targeted interventions should be designed respectively for males and females. These findings advance understanding of symptom-level dynamics and provide evidence-based implications for developing targeted psychological and behavioral interventions within nursing education to enhance students' mental health, academic success, and professional development. • First network analysis of Internet addiction and depressive symptoms in nursing students • Fatigue and Internet preoccupation are central symptoms maintaining the network. • Offline emotional dysregulation serves as primary bridge between symptom clusters. • Gender-specific network patterns suggest targeted intervention priorities for males and females. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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