EconPapers    
Economics at your fingertips  
 

The Six-Item Version of the Internet Addiction Test: Its Development, Psychometric Properties, and Measurement Invariance among Women with Eating Disorders and Healthy School and University Students

Amira Mohammed Ali, Amin Omar Hendawy, Abdulaziz Mofdy Almarwani, Naif Alzahrani, Nashwa Ibrahim, Abdulmajeed A. Alkhamees and Hiroshi Kunugi
Additional contact information
Amira Mohammed Ali: Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1, Ogawahigashi, Kodaira, Tokyo 187-8553, Japan
Amin Omar Hendawy: Department of Biological Production, Tokyo University of Agriculture and Technology, Tokyo 183-8509, Japan
Abdulaziz Mofdy Almarwani: Department of Psychiatric Nursing, College of Nursing, Taibah University, Janadah Bin Umayyah Road, Tayba, Medina 42353, Saudi Arabia
Naif Alzahrani: Department of Medical Surgical Nursing, College of Nursing, Taibah University, Janadah Bin Umayyah Road, Tayba, Medina 42353, Saudi Arabia
Nashwa Ibrahim: Department of Psychiatric and Mental Health Nursing, Faculty of Nursing, Mansoura University, Mansoura 35516, Egypt
Abdulmajeed A. Alkhamees: Department of Medicine, College of Medicine and Medical Sciences, Qassim University, Al Qassim, Buraydah 52571, Saudi Arabia
Hiroshi Kunugi: Department of Psychiatry, School of Medicine, Teikyo University, 2-11-1 Kaga, Itabashi-ku, Tokyo 173-8605, Japan

IJERPH, 2021, vol. 18, issue 23, 1-26

Abstract: Internet addiction (IA) is widespread, comorbid with other conditions, and commonly undetected, which may impede recovery. The Internet Addiction Test (IAT) is widely used to evaluate IA among healthy respondents, with less agreement on its dimensional structure. This study investigated the factor structure, invariance, predictive validity, criterion validity, and reliability of the IAT among Spanish women with eating disorders (EDs, N = 123), Chinese school children ( N = 1072), and Malay/Chinese university students ( N = 1119). In school children, four factors with eigen values > 1 explained 50.2% of the variance, with several items cross-loading on more than two factors and three items failing to load on any factor. Among 19 tested models, CFA revealed excellent fit of a unidimensional six-item IAT among ED women and university students (χ 2 (7) = 8.695, 35.038; p = 0.275, 0.001; CFI = 0.998, 981; TLI = 0.996, 0.960; RMSEA = 0.045, 0.060; SRMR = 0.0096, 0.0241). It was perfectly invariant across genders, academic grades, majors, internet use activities, nationalities (Malay vs. Chinese), and Malay/Chinese female university students vs. Spanish women with anorexia nervosa, albeit it was variant at the scalar level in tests involving other EDs, signifying increased tendency for IA in pathological overeating. The six-item IAT correlated with the effects of internet use on academic performance at a greater level than the original IAT ( r = −0.106, p < 0.01 vs. r = −0.78, p < 0.05), indicating superior criterion validity. The six-item IAT is a robust and brief measure of IA in healthy and diseased individuals from different cultures.

Keywords: coronavirus disease 2019; anorexia nervosa/binge eating/eating disorder; women; school children; university students; factorial structure/psychometric properties/structural validity/validation; Internet Addiction Test/six-item Internet Addiction Test; invariance; internet dependence/problematic internet use (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/18/23/12341/pdf (application/pdf)
https://www.mdpi.com/1660-4601/18/23/12341/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:18:y:2021:i:23:p:12341-:d:686719

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12341-:d:686719