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Un enfoque de incorporación basado en transformadores para desarrollar medidas psicológicas en forma corta

Se-Jin Jung1, Jang-Won Seo1

  • 1Department of Psychology, Jeonbuk National University, Jeonju, Republic of Korea.

Frontiers in psychology
|August 29, 2025
PubMed
Resumen

Este estudio introduce un nuevo método para crear encuestas psicológicas más cortas utilizando incrustaciones semánticas impulsadas por IA. Este enfoque reduce de manera eficiente los elementos al tiempo que mantiene fuertes propiedades psicométricas, ofreciendo una alternativa independiente de los datos para el desarrollo de medidas psicológicas.

Palabras clave:
Reducción de los artículosMedidas psicológicasagrupación semánticaDesarrollo en forma abreviadaEmbebidos basados en transformadores

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Área de la Ciencia:

  • Medición psicológica
  • Inteligencia artificial
  • Procesamiento del lenguaje natural

Sus antecedentes:

  • El desarrollo de medidas psicológicas breves es crucial para reducir la carga de los participantes y el gasto de recursos.
  • Los métodos existentes para el desarrollo de formularios cortos a menudo requieren una amplia recopilación y análisis de datos utilizando análisis de factores o aprendizaje automático.
  • Se necesitan enfoques eficientes e independientes de los datos para la reducción de elementos psicológicos.

Objetivo del estudio:

  • Proponer y evaluar un método novedoso e independiente de los datos para la reducción de elementos psicológicos utilizando incorporaciones semánticas basadas en transformadores.
  • Desarrollar una versión abreviada de los marcadores de cinco factores del grupo internacional de elementos de la personalidad (IPIP-50) utilizando este nuevo enfoque.
  • Comparar las propiedades psicométricas de la forma abreviada desarrollada con los métodos existentes.

Principales métodos:

  • Utilizó incorporaciones semánticas basadas en transformadores (modelo sentencia-t5-xxl) para representar elementos del IPIP-50.
  • Aplicado K-significa agrupamiento a las incorporaciones semánticas para agrupar elementos similares.
  • Elementos representativos seleccionados en función de su proximidad a los centros del cúmulo para formar una forma abreviada de 30 elementos.

Principales resultados:

  • El formulario corto de 30 puntos resultante conservó con éxito la estructura original de cinco factores del IPIP-50.
  • La forma corta demostró fuertes propiedades psicométricas, incluida la fiabilidad y la validez.
  • El método propuesto logró una fiabilidad, una validez convergente y un rendimiento predictivo comparables a los enfoques de teoría de pruebas clásicas y algoritmos genéticos.

Conclusiones:

  • Las incorporaciones semánticas basadas en transformadores ofrecen un enfoque poderoso y eficiente para la reducción de elementos psicológicos y el desarrollo de nuevas medidas.
  • Este método independiente de los datos ofrece una alternativa lingüística y eficiente en términos de recursos a las técnicas tradicionales de reducción dependientes de los datos.
  • Los hallazgos apoyan la viabilidad del uso de la IA para desarrollar evaluaciones psicológicas sólidas y concisas.