ABTRACT

The construct validity in relation to the dimensionality or factor structure of the Beck Hopelessness Scale (BHS) has long been debated in psychometrics. Irrelevant variance due to item wording (method effects) can distort the factor structure, and recent studies have examined the method factor’s role in the factor structure of the BHS. However, the models used to control the method effects have severe limitations, and new models are needed. One such model is the correlated trait-correlated method minus one (CT-C(M-1)), which is a powerful approach that gives the trait factor an unambiguous meaning and prevents the anomalous results associated with fully symmetrical bifactor modeling. The present work compares the fit and factor structure of the CT-C(M-1) model to bifactor models proposed in previous literature and evaluates the criterion validity of the CT-C(M-1) model and its discriminatory capacity by taking suicidal ideation as the criterion variable. This study used a large and heterogeneous open mode online sample of Argentinian people (N = 2,164). The results indicated that the CT-C(M-1) model with positive words as referenced items achieves the most adequate factor structure. The factorial scores derived from this model demonstrate good predictive and discriminating capabilities.

摘要

与贝克绝望量表（BHS）的维度或因子结构相关的结构效度在心理测量学中一直存在争议。由于项目措辞（方法效应）引起的不相关方差会扭曲因子结构，最近的研究已经检验了方法因子在 BHS 因子结构中的作用。然而，用于控制方法效果的模型有严重的局限性，需要新的模型。一种这样的模型是相关性状相关方法减一（CT-C（M-1）），这是一种强大的方法，可以为性状因素赋予明确的含义，并防止与完全对称的双因素建模相关的异常结果。本工作将 CT-C(M-1) 模型的拟合和因子结构与以往文献中提出的双因子模型进行比较，并评估 CT-C(M-1) 模型的标准效度及其判别能力。观念作为标准变量。本研究使用了一个大型且异质的开放模式在线阿根廷人样本（N = 2,164）。结果表明，以正面词为参考项的CT-C(M-1)模型实现了最充分的因子结构。从该模型得出的阶乘分数表现出良好的预测和辨别能力。结果表明，以正面词为参考项的CT-C(M-1)模型实现了最充分的因子结构。从该模型得出的阶乘分数表现出良好的预测和辨别能力。结果表明，以正面词为参考项的CT-C(M-1)模型实现了最充分的因子结构。从该模型得出的阶乘分数表现出良好的预测和辨别能力。