Integrating Gender Equity into Psychosocial Risk Assessment: Development and Pilot Validation of a Perceived Gender Disparity Subscale Within the OPRA Framework

Background: Gender equity is an increasingly relevant dimension in psychosocial risk assessment within organisational settings. This pilot study examines the integration of a Perceived Gender Disparity subscale into the Organisational and Psychosocial Risk Assessment (OPRA) inventory in an Italian manufacturing sample (N = 65). Methods: The five-item subscale, grounded in the literature on workplace gender discrimination and harassment, underwent reliability analysis (Cronbach’s α = 0.706), bivariate correlations (Pearson’s r), Exploratory Factor Analysis (EFA), non-parametric sensitivity analysis (Spearman’s ρ), and exploratory gender comparisons (exact Mann–Whitney U tests). Results: Results indicate statistically significant associations with seven of nine OPRA subscales: a large correlation with Role (r = 0.508, p < 0.001), medium-sized associations with Organisational Culture, Workload, Quality of Relationships, and Career Development (|r| = 0.331–0.427, p ≤ 0.007), and small-to-medium associations with Environment and Safety and Autonomy (|r| = 0.268–0.275, p < 0.05). No significant associations emerged for Working Hours or Work–Life Balance. Spearman’s correlations confirmed and strengthened all significant associations. Exploratory gender comparisons revealed medium-sized effects in the expected direction on the items assessing gender-specific disadvantage. EFA revealed a unidimensional structure with adequate loadings (λ = 0.475–0.785), accounting for 41.90% of the total variance. Conclusions: This study constitutes an initial psychometric evaluation rather than a definitive validation. Despite the limitations of a single-site, male-dominated sample, the findings provide preliminary support for including perceived gender disparity as a source of organisational risk within the OPRA framework. Larger and more diverse samples are required to confirm the factor structure and to establish the generalizability of the findings.