Gender-dependent color discrimination ability and speed–accuracy tradeoff: insights from ND-100 hue tests

Background: Time pressure influences perceptual decisions, but its effects on speed-accuracy tradeoff (SAT) and decision processes in color discrimination remains poorly understood, particularly regarding potential gender differences. Objective: To systematically examine how varying time pressures influence color discrimination performance, SATs, and underlying decision processes in males and females. Methods: A total of 356 university students (18-28 years) completed the ND-100 hue test under four time conditions (120, 105, 90, and 75 s). Each participant performed up to four trials to reduce task unfamiliarity effects. The study introduced three methodological innovations: (1) the first use of a 75-s time limit to model high-pressure conditions; (2) a fine-grained range of time limits (75-120 s) to capture detailed performance changes; and (3) multiple trials per participant to minimize learning and unfamiliarity effects. Results: = 0.918), indicating convergence of performance under extreme time pressure. Both sexes exhibited a clear SAT, with females' performance declining more sharply at 75 s, suggesting differential reliance on analytical processing, experience-based strategies, and decision-threshold adjustments. Mechanistic interpretation: The observed effects are interpreted within an integrative triple-mechanism framework, in which time pressure modulates the dynamic interplay among: (1) biological predispositions (e.g., photopigment variation, P-cell density differences, and interhemispheric connectivity differences); (2) experience-dependent perceptual plasticity; and (3) adaptive cognitive strategies for decision making. Conclusions: This study provides the first systematic evidence of gender differences in color discrimination performance under extreme temporal constraints, supports an integrative biological-experiential-cognitive model of time-pressured perception, and offers practical implications for training, task design, and interface development in real-world contexts requiring rapid color-based decisions.