Generative artificial intelligence (GenAI) has rapidly entered undergraduate research training, yet its relationship with research self-efficacy and attitudes toward scientific research remains underexplored among Health Sciences students. This cross-sectional study examined how self-reported GenAI literacy and research self-efficacy are associated with attitudes toward scientific research, separately and when modelled together. Of 101 submissions from undergraduate Health Sciences students enrolled in research courses at a private Peruvian university, 91 were analysed after 10 invariant response patterns were excluded. Students completed a 36-item self-report questionnaire whose items had been reviewed for content relevance and clarity by three experts. Analyses combined Spearman correlations, multiple regression with HC3 standard errors, a bootstrapped indirect-effect model and exploratory fuzzy-set qualitative comparative analysis (fsQCA). Reliability computed from the three dimension scores of each construct was α = 0.861 for GenAI literacy, 0.927 for research self-efficacy and 0.790 for attitudes. GenAI literacy correlated with attitudes (ρ = 0.475, Holm-adjusted p < 0.001), but in the female–male regression model (n = 90), research self-efficacy was the only one of the two capability scores that retained a statistically significant adjusted association (b = 0.353, 95% CI 0.087 to 0.619, p = 0.010; GenAI literacy b = 0.088, 95% CI −0.214 to 0.389, p = 0.564; R² = 0.405). The indirect term through research self-efficacy (0.313, 95% CI 0.092 to 0.536) is a statistical decomposition of overlapping, contemporaneous scores rather than evidence of a mechanism. Discriminant validity between GenAI literacy and research self-efficacy was not established (HTMT = 0.912), and parallel analysis favoured two factors rather than three. Under the primary calibration (theoretical anchors 2-3-4 with crossover memberships assigned to 0.501), functional knowledge and the critical–ethical evaluation of GenAI appeared in both terms of the intermediate fsQCA solution (consistency = 0.913, coverage = 0.741), but the minimised solutions changed with alternative anchors and with the handling of cases at the crossover. The findings describe associations among self-reported measures; whether developing both capabilities jointly improves research attitudes remains a question for future evaluation.

Generative artificial intelligence (GenAI) has rapidly permeated undergraduate research training, yet its relationship with research self-efficacy and attitudes toward scientific research remains underexplored in health sciences students. This cross-sectional study examined how GenAI literacy and research self-efficacy relate to attitudes toward scientific research, and whether their contribution is direct or channelled through self-efficacy. A total of 91 undergraduate health sciences students enrolled in research courses at a private Peruvian university with campuses across several regions completed a 36-item Likert scale covering three higher-order constructs, validated by three expert researchers. Data were collected between March and May 2026. Analyses combined descriptive statistics, Spearman correlations, HC3 robust multiple regression, and fuzzy-set qualitative comparative analysis (fsQCA). Reliability was adequate to excellent (GenAI literacy α = 0.861, AVE = 0.675; research self-efficacy α = 0.927, AVE = 0.810; attitudes α = 0.790, AVE = 0.603). GenAI literacy correlated with attitudes (ρ = 0.475, adjusted p < 0.001) but lost independent weight once self-efficacy entered the regression (b = 0.084, p = 0.570), whereas research self-efficacy remained the strongest adjusted predictor (b = 0.356, 95% CI 0.091-0.620, p = 0.009); the model explained 40.4% of the variance (F(4, 86) = 14.60, p < 0.001). Discriminant validity between GenAI literacy and self-efficacy was incomplete (HTMT = 0.912). The fsQCA identified functional knowledge and critical-ethical evaluation of GenAI as core conditions present in every sufficient configuration for high attitudes (intermediate solution consistency = 0.913). Findings indicate that GenAI literacy shapes research attitudes indirectly, through research self-efficacy, and that its ethical-critical dimension is a recurrent ingredient of favourable dispositions. Interventions should strengthen research confidence and critical GenAI literacy jointly rather than as separate competencies.