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| Published: June 25, 2025

Efficacy of the Biopsychosocial Model in Managing the Symptoms of Postpartum Depression in Women

Kusum Sharma

Ph.D Psychology research scholar, School of Liberal Arts and Management, DIT University, Dehradun Google Scholar More about the auther

DIP: 18.01.373.20251302

DOI: 10.25215/1302.373

ABSTRACT

Postpartum Depression is one of the most common as well as underdiagnosed mental health conditions in women. It generally develops within the first week just after childbirth. Symptoms like sleepless nights, irritability, severe mood swings, sadness, and loss of appetite could be signs of postpartum depression if they persist for more than one week. Biopsychological model is a trans- disciplinary approach that attempts to resolve the major maternal mental health issue by combining the three domains of Biology, Psychology, and social. Aim of the study: The present study aims to develop a Biopsychosocial Model for the management of Postpartum Depression symptoms, also investigates the associated risk factors causing Postpartum Depression in women. Methods and construct: The study is theoretical. The model developed in the study is based on previous research and studies. Only secondary data has been used to collect information from different sources and studies to draw conclusions. Findings of the study: Findings of the study suggest that the Biopsychosocial model is an amalgamation of three domains, Biological, Social, and Psychological models, and could be very helpful in planning an individualized treatment plan for women, keeping in mind their different needs. However, the practical applicability of this model is still an argument for researchers but if implemented and used correctly by clinicians, it could prove helpful not just for studying the associated risk factors but also provide a more comprehensive plan to alleviate the sufferings of women with postpartum depression.

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Kusum Sharma @ kusumsharma161@gmail.com

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ISSN 2348-5396

ISSN 2349-3429

18.01.373.20251302

10.25215/1302.373

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Published in   Volume 13, Issue 2, April-June, 2025