<b>Psychometric 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.

失眠症在青少年群体中是一种普遍且具有显著影响的健康问题，但其精准测量仍面临诸多挑战。<b>失眠严重指数量表（Insomnia Severity Index）</b>是当前广泛应用的自评式失眠症状评估工具，其缩写为ISI，但针对中国青少年群体，目前尚未建立起公认的因子结构与心理测量学特性。为填补这一研究空白，本研究依托<b>572095名中国青少年</b>的大样本数据，采用<b>双因子模型（bifactor modeling）</b>与<b>项目反应理论（item response theory, IRT）</b>，探究该量表的维度结构与信效度。

<b>因子结构探究</b>：本研究通过<b>验证性因子分析（confirmatory factor analysis, CFA）</b>检验了五种备选因子模型。拟合效果最优的模型为包含三个相关因子的<b>三因子结构</b>。然而，进一步的<b>双因子验证性因子分析（bifactor CFA）</b>结果显示，剔除第4题后的<b>双因子两因子模型</b>拥有更优异的拟合指标，且能够解释量表项目中更多的共同方差。

<b>信度与区分度</b>：基于上述双因子两因子模型，本研究采用<b>双因子多维项目反应理论（bifactor multidimensional IRT, MIRT）</b>评估量表的项目参数与测验信息函数。结果表明，该量表在评估<b>失眠严重程度中等至偏高的群体</b>时，展现出较高的信度与区分度；但在评估<b>失眠严重程度极低或极高的群体</b>时，其信度与区分度表现欠佳。

<b>研究意义</b>：本研究结果对中国青少年群体的失眠<b>测量与诊断</b>具有重要参考价值。研究者与临床工作者在该群体中使用ISI时，需结合具体情境与受试者的失眠严重程度水平进行综合考量。综上，失眠严重指数量表可作为评估中国青少年失眠严重程度的可靠且有效的工具，但其性能会随受试者的失眠严重程度水平发生变化。未来研究可进一步探索影响青少年失眠的其他因素，并据此对测量工具进行优化完善。