IRT analysis of the BDI-II for early online depression detection: validation in a Mexican population

利用IRT分析BDI-II进行早期在线抑郁症检测:在墨西哥人群中的验证

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Abstract

INTRODUCTION: Identifying factors associated with depression is crucial to addressing the global rise in mental health needs. The Beck Depression Inventory II (BDI-II) has shown robustness in assessing depression, even in digital contexts. However, psychometric evidence is essential to support its use in online self-diagnosis, particularly in regions where it has not been widely employed for this purpose. OBJECTIVE: This study aimed to evaluate the psychometric properties of the BDI-II for online self-diagnosis among Mexican adults. METHOD: Data from 58,456 medical records were analysed using Item Response Theory (IRT). RESULTS: A good fit was found for a hierarchical confirmatory model with 1 s-order factor (overall severity) and two first-order factors (cognitive and somatic symptoms), as well as optimal accuracy estimates in both the IRT and the Classical Test Theory (CTT). DISCUSSION: These findings support the use of the BDI-II as a reliable online screening tool for depression in self-diagnosis settings for Mexican adults.

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