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Internet Addiction and the Psychometric Properties of the Nine-item Internet Disorder Scale-Short Form: An Application of Rasch Analysis

BACKGROUND: The aim of the present study was to determine the prevalence of disordered internet use among adolescent university students and its association with various health complaints and behaviours, and most importantly to examine the psychometric properties of 9-item Internet Disorder Scale-Sh...

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Detalles Bibliográficos
Autores principales: Bener, Abdulbari, Griffiths, Mark D., Baysoy, Nuket Guler, Catan, Funda, Yurtseven, Eray
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Kerman University of Medical Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073813/
https://www.ncbi.nlm.nih.gov/pubmed/32206216
http://dx.doi.org/10.22122/ahj.v11i4.247
Descripción
Sumario:BACKGROUND: The aim of the present study was to determine the prevalence of disordered internet use among adolescent university students and its association with various health complaints and behaviours, and most importantly to examine the psychometric properties of 9-item Internet Disorder Scale-Short Form (IDS9-SF) using factor analyses and Rasch analysis. METHODS: A total of 1988 university students aged 18 to 25 years were selected via a multi-stage stratified random sampling technique among university students in Istanbul, Turkey (September 2017 to February 2018). Data collected included socio-demographics, lifestyle and dietary habits, and the 9-item IDS9-SF. Statistical analysis included descriptive statistics, multivariate analyses, factor analyses, path analysis, and Rasch analysis. FINDINGS: Using confirmatory factor analysis (CFA), the study investigated the latent structure of the IDS9-SF instrument and results supported its reliability and validity. The prevalence of disordered internet use was 18.3% in the sample. There were significant differences between those who had disordered internet use and those who did not in gender, family income, school performance, number of bedrooms at home, and number of people living at home, as well as internet use duration. Using multivariate regression analysis, key predictors of disordered internet use included (among others): gender, body mass index (BMI), household income, number of people living at home, having a computer at home, internet facilities, duration of internet use, sleeping hours, frequency of eating fast food, watching television, headache, hurting eyes, tired eyes, and hearing problems. Rash analysis demonstrated that four of the nine items (2, 3, 6, and 7) were more difficult for individuals to endorse compared to other items. CONCLUSION: Problems arising from excessive internet use were apparent among the study sample and the IDS9-SF is a valid and reliable measure for assessing disordered internet use among Turkish adolescent population.