In Progress in neuro-psychopharmacology & biological psychiatry
INTRODUCTION : Postpartum depression (PPD) is defined as a major depressive disorder (MDD) beginning after childbirth. Wide debates aim to better understand PPD's specificities compared with MDD. One of the keys in differentiating PPD from MDD is to systematically study scientific "Areas Of Interest" (AOIs) of these disorders.
METHODS : In November 2021, we performed an extraction and textual computational analysis of associated terms for PPD and MDD, using the biomedical database PubMed. We performed an undirected lexical network analysis to map the 150 first terms in space. Then, we used an unsupervised machine learning technique to detect word patterns and automatically cluster AOIs with a topic-modeling analysis.
RESULTS : We identified 30,000 articles of the 554,724 articles for MDD and 15,642 articles for PPD. Four AOIs were detected in the MDD network: mood disorders and their treatments, risk factors, consequences and quality of life, and mental health and comorbidities. Five AOIs were detected in the PPD network: mood disorders and treatments, risk factors, consequences and child health, patient's background, and the challenges of screening.
DISCUSSION AND CONCLUSION : Limitations are both methodological, in particular due to the qualitative interpretation of AOIs, and are also related to the difficult transferability of these research results to the clinical practice. The partial overlap between AOIs for MDD and for PPD suggest that the latter is a particular form of the former.
Gauld Christophe, Pignon Baptiste, Fourneret Pierre, Dubertret Caroline, Tebeka Sarah
2022-Oct-29
Major depressive disorder, Natural language processing, Postpartum depression, Scientific representations, Text-mining
