Purpose: This study examined the structural determinants of antimicrobial prescribing practices and resistance awareness among healthcare providers in Oyo State, Nigeria, addressing a critical gap in understanding how knowledge, institutional support, workload pressure, training access, and patient expectations influence prescribing behaviour.

Methodology/Design: A quantitative cross-sectional survey design was employed, grounded in the positivist paradigm. Data were collected from 298 healthcare providers (doctors, pharmacists, and nurses) across tertiary, secondary, and primary healthcare facilities using a structured questionnaire with 33 items across seven constructs. Structural equation modelling using SmartPLS 4.0 was used to test six hypotheses, assessing both measurement and structural models.

Findings/Results: All six hypotheses were supported. Knowledge positively influenced prescribing practices (β = 0.34, t = 4.21), as did institutional support (β = 0.28, t = 3.56) and training access (β = 0.19, t = 2.45). Workload pressure unexpectedly showed a negative relationship with inappropriate prescribing (β = -0.41, t = 5.12), indicating that higher workload was associated with less inappropriate prescribing. Training access strongly predicted resistance awareness (β = 0.52, t = 6.78), and patient expectations positively influenced prescribing practices (β = 0.31, t = 3.89).

Implications: Theoretical implications extend the Theory of Planned Behavior and Health Belief Model by demonstrating that environmental factors may be more powerful determinants of prescribing behaviour than individual cognitive factors. Practical implications include recommendations for mandatory AMR training, strengthening institutional support, implementing audit-and-feedback mechanisms, and public awareness campaigns targeting patient expectations.

Originality/Value: This study provides the first structural equation modelling analysis of antimicrobial prescribing determinants in southwestern Nigeria, offering a validated framework for understanding the relative importance of multiple predictors and revealing the counterintuitive protective effect of workload pressure on prescribing quality.