Computer adaptive testing strategies for the Edinburgh Postnatal Depression Scale (EPDS)

Perinatal mood and anxiety disorders (PMADs) include depressive and anxiety disorders during pregnancy or postpartum and can have significant consequences for the parent, child, and family. When severe, these conditions can lead to suicide. Despite numerous policy efforts to improve screening, education, and referral structures, disparities in PMAD diagnosis and treatment still exists, particularly among racial and ethnic minorities. Computer Adaptive Testing (CAT) has been shown to improve the efficiency of screening by significantly reducing test length. This study evaluates whether applying CAT to the Edinburgh Postnatal Depression Scale (EPDS) maintains diagnostic accuracy while ensuring these methods do not exacerbate racial disparities in PMAD screening outcomes.

Using real data simulation, we assessed three CAT-based short-form versions of the EPDS, derived from one-, two-, and three-factor item response theory models. We evaluated their diagnostic precision and examined potential racial disparities in false negative rates compared to the full-length EPDS.

We demonstrate that estimated scores from three short versions of the EPDS administered through CAT-assuming one, two, and three-factor item response theory models-are more highly correlated with the full-length EPDS measure traditionally used to make clinical decisions (r's between 0.96 and 0.97) than the major depressive disorder subtest (CAT-MDD) from CAT-Mental Health (CAT-MH^®) (r =.82), as previously reported. Importantly, the false negative rates of the CAT-implied diagnoses did not significantly vary between racial groups, indicating no evidence of racial bias in diagnostic accuracy.

The CAT-based versions of the EPDS offers a promising solution for improving the efficiency of PMAD screening without sacrificing diagnostic precision or exacerbating racial groups. By reducing evaluation time, these tools could facilitate more widespread and equitable screening, enabling earlier diagnosis and treatment of PMADs across diverse populations.