A qualitative study of maternal health knowledge and healthcare-seeking behaviour among rural married women in Bangladesh using the social-ecological model

Maternal health is one of the pivotal concerns in rural Bangladesh, where many women still face obstacles to safe and timely care during pregnancy and childbirth. This study explores maternal health knowledge and their healthcare-seeking behavior during pregnancy, delivery, and after childbirth among the rural married women in Bangladesh. This is a qualitative data-based study, and it conducted 12 In-depth Interviews (IDIs) and 3 Key Informant Interviews (KIIs) in Salimpur village, Trishal municipality of Mymensingh District, Bangladesh. This study interviewed 12 married women of reproductive age (18–35 years) and 3 key informants (two household heads and a village doctor) using purposive sampling. In addition, the data were analyzed using reflexive thematic analysis, combining inductive and deductive approaches guided by the Social-Ecological Model. All interviews were audio-recorded, transcribed verbatim, and coded to ensure credibility. In this study four key themes emerged in the light of Social-Ecological Model, namely: (1) education as an enabler of health literacy and autonomy; (2) family gatekeeping through the decision-making authority of mothers-in-law and husbands; (3) emerging skepticism toward some restrictive cultural practices, particularly among younger and more educated women; and (4) quality preference over cost that drives the utilization of private healthcare despite financial difficulties or constraints. Rural women face multiple barriers to maternal healthcare services. For this, improving maternal health outcomes requires ensuring accessible and affordable services, and needs to improve women’s health knowledge and decision-making power. Moreover, findings of this study are contextually situated within one rural village and are not intended to be statistically generalizable, but offer transferable insights for rural Bangladesh and similar low-resource settings.