<b>Psychometric Evaluation of the Insomnia Severity Index in 570,295 Chinese Adolescents: A Bifactor Item Response Theory Analysis</b>
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Insomnia is a prevalent and significant issue among adolescents, yet its accurate measurement remains challenging. The <b>Insomnia Severity Index (ISI)</b>, a widely used self-report measure for assessing insomnia symptoms, lacks well-established factor structure and psychometric properties in Chinese adolescents. To address this gap, our study employed <b>bifactor modeling</b> and <b>item response theory (IRT)</b> to explore the dimensionality and reliability of the ISI in a large sample of <b>572,095 Chinese adolescents</b>.<b>Factor Structure Investigation</b>:We tested five alternative factor models using <b>confirmatory factor analysis (CFA)</b>.The best-fitting model was a <b>three-factor structure</b> with three correlated factors.However, <b>bifactor CFA</b> revealed that a <b>bifactor two-factor model</b>, excluding item 4, exhibited superior fit indices and accounted for more common variance in the ISI items.<b>Reliability and Discrimination</b>:Based on the bifactor two-factor model, we employed <b>bifactor multidimensional IRT (MIRT)</b> to assess item parameters and the test information function of the ISI.The results indicated that the ISI demonstrated <b>high reliability and discrimination</b> for measuring individuals with <b>average to high levels of insomnia severity</b>.However, its reliability and discrimination were lower when assessing individuals with <b>very low or very high levels of insomnia severity</b>.<b>Implications</b>:These findings have important implications for the <b>measurement and diagnosis of insomnia</b> in Chinese adolescents.Researchers and clinicians should consider the specific context and severity levels when utilizing the ISI in this population.In summary, the ISI proves to be a <b>reliable and valid measure</b> for assessing insomnia severity in Chinese adolescents, but its performance varies across different severity levels. Future research should explore additional factors influencing insomnia and refine measurement tools accordingly.
