Desarrollo y Validación de una Escala para Medir las Actitudes Hacia el Uso de la Inteligencia Artificial en la Selección de Personal
DOI:
https://doi.org/10.71332/jj8kd256Palabras clave:
Inteligencia Artificial, Seleccion de personal , Validacion de escalasResumen
El presente estudio desarrolló y aportó evidencia inicial de validez y confiabilidad de la Escala de Actitudes hacia el Uso de la Inteligencia Artificial en los Procesos de Selección de Personal (ACT-IA), un instrumento fundamentado en el modelo tripartito de las actitudes (cognitivo, afectivo y conductual). Participaron 236 profesionales y estudiantes de Recursos Humanos y Psicología Industrial/Organizacional de Puerto Rico. La validez de contenido se evaluó mediante juicio de expertos con el método de Lawshe modificado por Tristán-López; la estructura interna se examinó con análisis factorial exploratorio y, posteriormente, mediante la comparación de modelos confirmatorios competitivos (unidimensional, tres factores oblicuos, bifactor-CFA y ESEM) estimados con un procedimiento robusto para datos ordinales. La interpretación de los índices de ajuste se realizó mediante los puntos de corte basados en percentiles propuestos por Howard et al. (2025), que clasifican el ajuste como Muy Débil a Muy Fuerte según la posición del índice respecto a la distribución de valores publicados. La versión final de 19 reactivos quedó mejor representada por un modelo bifactor con un factor general dominante (ECV = .731; ωH = .873) acompañado de facetas afectiva y conductual con varianza específica moderada. La escala mostró invarianza configural, métrica y escalar por género, consistencia interna excelente (α y ω entre .943 y .966) y una influencia mínima de la deseabilidad social. Se concluye que la puntuación total de la ACT-IA constituye el indicador más robusto del constructo.
Palabras clave: Inteligencia Artificial, Selección de Personal, Actitudes, Validación de Escalas, Modelo Bifactor, Modelamiento de Ecuaciones Estructurales Exploratorio (ESEM), Invarianza de Medición
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