Artificial intelligence predicts healthcare workers' antibiotic use intentions from psychological and behavioral measures across multiple theories.

ABSTRACT: Antimicrobial resistance (AMR) remains a global health priority, partly driven by non-guideline-concordant antibiotic prescribing among healthcare workers. Existing interventions often overlook the psychological and contextual factors that shape prescribing behaviour. This study integrated behavioural theory with explainable machine learning to identify psychological predictors of intention to use antimicrobials appropriately among clinicians. A cross-sectional survey was conducted among 1135 healthcare workers from four public hospitals in China. Participants completed questionnaires based on constructs from the Theory of Planned Behavior, the Health Belief Model, the Theory of Reasoned Action (TRA), Self-Efficacy Theory, Social Support Theory, and cognitive processing frameworks. LASSO r

SUBMITTER: Han L 

PROVIDER: S-EPMC12909973 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature