Antibiotic resistance is a growing public health concern, particularly in low- and middle-income countries such as Bangladesh. This cross-sectional empirical study analyzed primary survey data collected from 254 respondents in Bangladesh using Structural Equation Modeling (SEM). Structural Equation Modeling (SEM) with Smart-PLS 4.0 was employed to analyze the relationships between key variables, ensuring accurate results despite non-normal data. The findings reveal that economic pressures, inadequate diagnostics, and cultural misconceptions are key contributors to antibiotic overuse and misuse. The study is grounded in the Health Belief Model and Ecological Systems Theory, offering a framework to understand these behaviors. It underscores the need for targeted policies, improved diagnostic resources, and heightened public awareness to address the growing problem of antimicrobial resistance. The findings indicate that economic incentives, diagnostic uncertainty, healthcare infrastructure, and sociocultural beliefs significantly influence antibiotic resistance within the surveyed population.
Rakib et al. (Mon,) studied this question.