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The study analyzed factors associated with postpartum post-traumatic stress disorder (PP-PTSD) in first-time mothers using machine learning models.
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A total of 1,135 primiparous women were enrolled, with 794 in the training cohort and 341 in the independent validation cohort.
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Key predictors of PP-PTSD identified included social support, depression, neonatal caregiving style, husband's participation, and sleep quality.
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The Gradient Boosting model demonstrated the best performance in predicting PP-PTSD, achieving an AUC of 0.939 in the validation cohort.
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The study highlights the need for multicenter validation and the development of clinically implementable tools for PP-PTSD identification.
