The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses
Abstract Smartphone addiction is a global problem affecting university students. Previous studies have explored smartphone addiction and related factors using latent variables. In contrast, this study examines the role of smartphone addiction and related factors among university students using a cro...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-11-01
|
| Series: | BMC Psychiatry |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12888-023-05384-6 |
| _version_ | 1797414313000960000 |
|---|---|
| author | Cunjia Liu |
| author_facet | Cunjia Liu |
| author_sort | Cunjia Liu |
| collection | DOAJ |
| description | Abstract Smartphone addiction is a global problem affecting university students. Previous studies have explored smartphone addiction and related factors using latent variables. In contrast, this study examines the role of smartphone addiction and related factors among university students using a cross-sectional and cross-lagged panel network analysis model at the level of manifest variables. A questionnaire method was used to investigate smartphone addiction and related factors twice with nearly six-month intervals among 1564 first-year university students (M = 19.14, SD = 0.66). The study found that procrastination behavior, academic burnout, self-control, fear of missing out, social anxiety, and self-esteem directly influenced smartphone addiction. Additionally, smartphone addiction predicted the level of self-control, academic burnout, social anxiety, and perceived social support among university students. Self-control exhibited the strongest predictive relationship with smartphone addiction. Overall, self-control, self-esteem, perceived social support, and academic burnout were identified as key factors influencing smartphone addiction among university students. Developing prevention and intervention programs that target these core influencing factors would be more cost-effective. |
| first_indexed | 2024-03-09T05:31:02Z |
| format | Article |
| id | doaj.art-2ddbddcc1b4645f18e4acc8ac70c968c |
| institution | Directory Open Access Journal |
| issn | 1471-244X |
| language | English |
| last_indexed | 2024-03-09T05:31:02Z |
| publishDate | 2023-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Psychiatry |
| spelling | doaj.art-2ddbddcc1b4645f18e4acc8ac70c968c2023-12-03T12:32:14ZengBMCBMC Psychiatry1471-244X2023-11-0123111210.1186/s12888-023-05384-6The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analysesCunjia Liu0College of Information and Intelligence, Hunan Agricultural UniversityAbstract Smartphone addiction is a global problem affecting university students. Previous studies have explored smartphone addiction and related factors using latent variables. In contrast, this study examines the role of smartphone addiction and related factors among university students using a cross-sectional and cross-lagged panel network analysis model at the level of manifest variables. A questionnaire method was used to investigate smartphone addiction and related factors twice with nearly six-month intervals among 1564 first-year university students (M = 19.14, SD = 0.66). The study found that procrastination behavior, academic burnout, self-control, fear of missing out, social anxiety, and self-esteem directly influenced smartphone addiction. Additionally, smartphone addiction predicted the level of self-control, academic burnout, social anxiety, and perceived social support among university students. Self-control exhibited the strongest predictive relationship with smartphone addiction. Overall, self-control, self-esteem, perceived social support, and academic burnout were identified as key factors influencing smartphone addiction among university students. Developing prevention and intervention programs that target these core influencing factors would be more cost-effective.https://doi.org/10.1186/s12888-023-05384-6Smartphone addictionCross-sectional network analysisCross-lagged panel network analysisInteraction of Person-Affect-Cognition-Execution modelThe network theory of mental disorder |
| spellingShingle | Cunjia Liu The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses BMC Psychiatry Smartphone addiction Cross-sectional network analysis Cross-lagged panel network analysis Interaction of Person-Affect-Cognition-Execution model The network theory of mental disorder |
| title | The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses |
| title_full | The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses |
| title_fullStr | The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses |
| title_full_unstemmed | The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses |
| title_short | The unique role of smartphone addiction and related factors among university students: a model based on cross-sectional and cross-lagged network analyses |
| title_sort | unique role of smartphone addiction and related factors among university students a model based on cross sectional and cross lagged network analyses |
| topic | Smartphone addiction Cross-sectional network analysis Cross-lagged panel network analysis Interaction of Person-Affect-Cognition-Execution model The network theory of mental disorder |
| url | https://doi.org/10.1186/s12888-023-05384-6 |
| work_keys_str_mv | AT cunjialiu theuniqueroleofsmartphoneaddictionandrelatedfactorsamonguniversitystudentsamodelbasedoncrosssectionalandcrosslaggednetworkanalyses AT cunjialiu uniqueroleofsmartphoneaddictionandrelatedfactorsamonguniversitystudentsamodelbasedoncrosssectionalandcrosslaggednetworkanalyses |