A Fuzzy Inference System for Assessing Parental Mental Health and Postpartum Depression

Resumen

ABSTRACT: The period after childbirth for both mothers and fathers is a very crucial time physically, psychologically, and socially, yet standard psychological assessments often restrict these complex feelings into rigid categories. Designing and testing a Mamdani-type Fuzzy Inference System (FIS), which ties together fuzzy logic with well-known psychological concepts, was measured using depression (EPDS), parental stress (PSS), social support (MSPSS), and emotional regulation (ERQ). This study fulfills that gap. The FIS uses linguistic categories-low, moderate, and high-based on data from 400 parents in Aurangabad, Bihar. The theoretical interaction and the application of these methods to these variables are modeled using expert-defined fuzzy rules that produce a continuous, understandable mental health index. The majority of parents showed moderate emotional well-being, with fathers showing somewhat poor results. The cross-sectional design limits causal inference. Parental emotional risks can be identified early using the fuzzy model.

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Biografía del autor/a

Zahoor Lone, Associate Professor

With a strong academic background and a passion for fostering student growth, I have supervised five PhD research scholars and guided six PhDs to completion. My recent promotion to Associate Professor on August 24, 2024, is a testament to my dedication and hard work. As Training and Placement Coordinator, I have successfully created over 100 leads for summer internships and placed 128 students in corporate jobs.

My expertise extends beyond academia, with involvement in the Happiness and Counselling Cell and collaboration with MOHAN Foundation (Chandigarh) for allied healthcare training and workshops. I have published 17 research papers, 2 book chapters, and presented in 10 national and international conferences

Citas

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Publicado
2026-03-16
Sección
Special Issue: Mathematics and Computing - Innovations and Applications