Gender Differences in Human Trust and Contextual Perception of Robots

INTRODUCTION: Trust is a prerequisite for safe and effective Human–Robot Interaction (HRI), yet reported gender differences are inconsistent and likely contingent on context and socio-perceptual processes. OBJECTIVES: Within a unified framework spanning four canonical HRI contexts (healthcare, education, manufacturing, security), we test whether (a) gender predicts trust, (b) context moderates gender effects, and (c) perceived warmth and perceived threat mediate gender–trust relations. METHODS: A vignette-based experiment with adults (N = 132; male/female) measured affective and cognitive trust, perceived warmth, and perceived threat on 7-point scales. Analyses followed a preregistered plan: 2×4 mixed ANOVAs (Gender × Context) and parallel mediation (PROCESS Model 4; 5,000 bootstrap resamples) with covariates (age, education, prior HRI experience). RESULTS: Gender showed a significant main effect for affective trust (females > males), but not for cognitive trust. Context effects were significant for both trust facets. Gender × Context interactions emerged: the female advantage in affective trust was concentrated in healthcare, while males reported higher cognitive trust in education and manufacturing. Mediation indicated that females’ higher perceived warmth and lower perceived threat jointly accounted for gender differences in overall trust; the direct gender effect was not significant after including mediators. Robustness checks (ANCOVAs; order effects) supported all primary findings. CONCLUSION: Gender differences in robot trust are context-dependent and arise via warmth-enhancing and threat-reducing socio-perceptual pathways. Design should emphasize empathy/assurance cues in caring roles and competence/reliability cues in task/authority roles, alongside systematic threat mitigation.