Two decades and counting: The enduring legacy of the Attribution Questionnaire - Pingani, Luca; De Marco, Erika; Evans-Lacko, Sara; Marchi, Mattia; Meloni, Matteo; Rüsch, Nicolas; Galeazzi, Gian Maria (Acta Biomedica Atenei Parmensis, 2026)
Background and aim: This study examines the psychometric properties of three versions of the Attribution Questionnaire (AQ) in an Italian context. The AQ is a widely used tool for assessing public stigma toward mental illness, a phenomenon that profoundly affects individuals, their quality of life, and healthcare policies. The three versions analyzed include the AQ-21 (2003), comprising six domains (Personal Responsibility, Fear, Pity, Anger, Helping, Coercion/Segregation); the AQ-26 (2008), reorganized into six factors (Fear/Dangerousness, Help/Interaction, Responsibility, Forced Treatment, Empathy, Negative Emotions); and the Italian AQ-27, an expanded version with nine domains. Methods: A total of 233 participants, recruited via snowball sampling, completed the AQ-27-I. Confirmatory Factor Analysis and Structural Equation Modeling were used to evaluate the fit of the AQ models and to explore causal relationships between latent variables within the best-fitting model. Results: All three AQ versions demonstrated acceptable psychometric properties, with the AQ-27 emerging as the most robust due to its more detailed structural configuration. Analysis of AQ-27-I identified two distinct models: the personal responsibility model and the dangerousness model. The former showed that attributing responsibility for mental distress to individuals is associated with anger and a paradoxical combination of desires to help and segregate those individuals. The latter confirmed that perceiving individuals with mental illness as dangerous leads to heightened fear and increased social avoidance. Conclusions: The findings confirm the AQ-27’s reliability in assessing public stigma and emphasize the importance of exploring interactions between its domains. A better understanding of stigma dynamics could enhance targeted interventions.