Background/Objectives: Lesbian, gay, bisexual, and transgender (LGBT) individuals often face discrimination in healthcare settings, resulting in health disparities. Evaluating healthcare professionals’ affirmative practices is essential for promoting inclusive care and addressing these disparities. The aim of this study was to assess the psychometric properties of the Spanish version of the Gay Affirmative Practice Scale (GAP-ES), which measures healthcare professionals’ affirmative practices towards gay individuals. Methods: Before assessing its psychometric properties, the original Gay Affirmative Practice Scale (GAP) was translated and culturally adapted from English to Spanish. Following the translation, the psychometric properties were tested on a sample of 236 healthcare professionals. The internal consistency of the questionnaire was measured using Cronbach’s alpha and the discriminatory power index. Factor structure was evaluated with Confirmatory Factor Analysis (CFA) using the Diagonally Weighted Least Squares method. Results: The sample consisted of 152 female (64.41%) and 84 male (35.59%) participants, with 58.05% identifying as heterosexual, 28.81% as homosexual, and 13.14% as bisexual. The internal consistency of the GAP-ES was strong, with Cronbach’s alpha values of 0.915 for the Beliefs subscale and 0.902 for the Behaviors subscale. The McDonald’s Omega coefficient was 0.942, indicating high reliability. CFA confirmed a two-factor structure with satisfactory fit indices (CFI = 0.999, RMSEA = 0.071). Conclusions: The GAP-ES demonstrates strong internal consistency and a stable factor structure. It is a reliable tool for evaluating affirmative practices toward LGBT patients in Spanish-speaking healthcare contexts, supporting improved care for this population. The integration of the GAP-ES into clinical practice and training programs may support the enhancement of cultural competence among healthcare professionals, contributing to the reduction of health disparities for LGBT patients in Spanish-speaking settings.
Read full abstract