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

IntroductionIdentifying 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...

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Main Authors: Tonathiu Salcedo-Callado, Norberto Hernández-Llanes, Ricardo Sánchez-Domínguez, Ricardo Saracco-Alvarez, Rodrigo Marín-Navarrete
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Psychology
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Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1562016/full
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Summary:IntroductionIdentifying 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.ObjectiveThis study aimed to evaluate the psychometric properties of the BDI-II for online self-diagnosis among Mexican adults.MethodData from 58,456 medical records were analysed using Item Response Theory (IRT).ResultsA 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).DiscussionThese findings support the use of the BDI-II as a reliable online screening tool for depression in self-diagnosis settings for Mexican adults.
ISSN:1664-1078