There has been increased research examining the psychometric properties on the Internet Addiction Test across different ages and populations. This population-based study examined the psychometric properties using Confirmatory Factory Analysis and measurement invariance using Item Response Theory (IRT) of the IAT in adolescents from three Asian countries. In the Asian Adolescent Risk Behavior Survey (AARBS), 2,535 secondary school students (55.91% girls) in Grade 7 to Grade 13 (Mean age = 15.61 years; SD = 1.56) from Hong Kong (n = 844), Japan (n = 744), and Malaysia (n = 947) completed a survey on their Internet use that incorporated the IAT scale. A nested hierarchy of hypotheses concerning IAT cross-country invariance was tested using multi-group confirmatory factor analysis. Replicating past finding in Hong Kong adolescents, the construct of IAT is best represented by a second-order three-factor structure in Malaysian and Japanese adolescents. Configural, metric, scalar, and partial strict factorial invariance was established across the three samples. No cross-country differences on Internet addiction were detected at latent mean level. This study provided empirical support to the IAT as a reliable and factorially stable instrument, and valid to be used across Asian adolescent populations.
Background: The COVID-19 pandemic is a novel population-level stressor. As such, it is important to examine pandemic-related changes in mental health and to identify which individuals are at greatest risk of worsening symptoms.Methods: Online questionnaires were administered to 34,465 individuals in the UK, recruited from existing cohorts or via social media. Around one third (n = 12,718) with prior diagnoses of depression or anxiety completed pre-pandemic mental health assessments, allowing prospective investigation of symptom change. We examined changes in depression, anxiety and PTSD symptoms using prospective, retrospective and global ratings of change assessments. We also examined the effect of key risk factors on changes in symptoms.Outcomes: Prospective analyses showed small decreases in depression (PHQ-9: - .43 points) and anxiety symptoms (GAD-7: -.33 points), and increases in PTSD symptoms (PCL-6: .22 points). Conversely, retrospective analyses demonstrated large significant increases in depression (2.40 points) and anxiety symptoms (1.97 points) and 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Using both prospective and retrospective symptom measures, regression analyses demonstrated that worsening depression, anxiety and PTSD symptoms were associated with i) prior mental health diagnoses, ii) female gender; iii) young age, and iv) unemployed or student status.Interpretation: We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously-reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias underestimating prior symptom severity.
The wide array of symptoms of unipolar depressive and anxiety disorders has raised questions about the relationship between these disorders, and factor analysis provides one approach to examining these relationships. In this paper, we replicate the tri-level model of symptoms of anxiety and depression first proposed by Prenoveau et al. (2010) in a sample of young adults selected to vary in their risk for psychopathology. In the tri-level model, symptom-specific items load on three factors arranged in a bifactor structure: a narrow (or disorder-specific) factor, an intermediate (or category-specific) factor, and a general distress factor. The tri-level model fit well in this sample. Furthermore, it fit significantly better than models that eliminated one of the three levels, suggesting that each level of the tri-level model contributes significantly to model fit. This conceptual replication once again supports the tri-level model. Implications for research and treatment are discussed.
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