Soowon Park1, Seungchan Lee2, Boungho Choi3, Seunghee Cho4, Jin-Pyo Hong5, Hong Jin Jeon5, Jeongsim Kim6, Jee Eun Park7,8, Jun-Young Lee9. 1. Department of Education, Sejong University, Seoul, Republic of Korea. 2. Seoul National University College of Medicine, Seoul, Republic of Korea. 3. Department of Criminology, Graduate School of Police Studies, Korean National Police University, Asan, Republic of Korea. 4. Department of Psychology, University of California, Los Angeles, California, USA. 5. Department of Psychiatry, Depression Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 6. Department of Psychiatry and Neuroscience Research Institute, Seoul National University College of Medicine and SMG-SNU Boramae Medical Center, Seoul, Republic of Korea. 7. Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea. 8. Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea. 9. Department of Psychiatry and Neuroscience Research Institute, Seoul National University College of Medicine and SMG-SNU Boramae Medical Center, Seoul, Republic of Korea, benji@snu.ac.kr.
Abstract
AIMS: The aim of the current study was to develop and validate a short-form of the internet overuse screening questionnaire (IOS-Qs). METHODS: A total of 571 adults were recruited from a representative, stratified, and multistage cluster sample. Among participants, 188 and 383 were used in the development and validation of the IOS-Qs, respectively. RESULTS: Experts' ratings and Rasch model analyses led to the selection of 8 items from the IOS-Qs; latent-class analysis using these 8 items revealed an estimated prevalence of 8.6% (33 out of 383) of problematic internet over-users. Problematic internet over-users were positively associated with a 1-year prevalence rate of any mental disorder (OR 3.08, p = 0.008), mood disorder (OR 7.11, p = 0.003), and depressive disorder (OR 5.22, p = 0.016). The receiver operating characteristic curves identified an optimal cutoff score of 9.5 for differentiating problematic internet over-users from unproblematic internet users with 94% sensitivity and 94% specificity. CONCLUSION: The results suggest that the IOS-Qs was valid, and items including social isolation were crucial to the brief distinction of at-risk internet users. Because of its brevity, the questionnaire can be effectively administered as a large-scale survey.
AIMS: The aim of the current study was to develop and validate a short-form of the internet overuse screening questionnaire (IOS-Qs). METHODS: A total of 571 adults were recruited from a representative, stratified, and multistage cluster sample. Among participants, 188 and 383 were used in the development and validation of the IOS-Qs, respectively. RESULTS: Experts' ratings and Rasch model analyses led to the selection of 8 items from the IOS-Qs; latent-class analysis using these 8 items revealed an estimated prevalence of 8.6% (33 out of 383) of problematic internet over-users. Problematic internet over-users were positively associated with a 1-year prevalence rate of any mental disorder (OR 3.08, p = 0.008), mood disorder (OR 7.11, p = 0.003), and depressive disorder (OR 5.22, p = 0.016). The receiver operating characteristic curves identified an optimal cutoff score of 9.5 for differentiating problematic internet over-users from unproblematic internet users with 94% sensitivity and 94% specificity. CONCLUSION: The results suggest that the IOS-Qs was valid, and items including social isolation were crucial to the brief distinction of at-risk internet users. Because of its brevity, the questionnaire can be effectively administered as a large-scale survey.