<b>Large-Scale Evaluation of the Insomnia Severity Index in 570,295 Chinese Adolescents: A Bifactor Item Response Theory Analysis</b>

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.

失眠是青少年群体中高发且影响深远的问题，但其精准测评仍存在挑战。当前广泛用于评估失眠症状的自评量表**失眠严重指数量表（Insomnia Severity Index, ISI）**，在中国青少年群体中尚未确立成熟的因子结构与心理测量学属性。为填补这一研究空白，本研究依托572095名中国青少年的大样本数据，采用**双因子模型（bifactor modeling）**与**项目反应理论（Item Response Theory, IRT）**，探究ISI的维度结构与信效度。

因子结构探究：本研究通过**验证性因子分析（Confirmatory Factor Analysis, CFA）**检验了5种备选因子模型。拟合最优的模型为包含3个相关因子的**三因子结构**。然而，**双因子验证性因子分析（bifactor CFA）**结果显示，剔除第4个条目后的**双因子二因子模型**拥有更优异的拟合指数，且能解释ISI条目更多的共同方差。

信度与区分度分析：基于上述双因子二因子模型，本研究采用**双因子多维项目反应理论（Multidimensional Item Response Theory, MIRT）**评估了ISI的项目参数与测验信息函数。结果表明，ISI在测评**失眠严重程度中等至偏高的个体**时，展现出高信度与区分度；但在评估**失眠严重程度极低或极高的个体**时，其信度与区分度表现欠佳。

研究启示：本研究结果对中国青少年群体的**失眠评估与诊断**具有重要实践价值。研究者与临床工作者在该群体中使用ISI时，应结合具体情境与失眠严重程度层级进行考量。

综上，失眠严重指数量表是用于评估中国青少年失眠严重程度的信效度良好的测评工具，但其表现在不同严重程度层级中存在差异。未来研究应进一步探究影响失眠的其他因素，并据此优化测评工具。