Validación de un modelo de rasgos positivos y negativos de personalidad como predictores del bienestar psicológico aplicando algoritmos de machine learning
DOI:
https://doi.org/10.22235/cp.v18i1.3286Palabras clave:
rasgos positivos, rasgos negativos, personalidad, bienestar psicológico, algoritmosResumen
El objetivo de este estudio fue verificar un modelo predictivo de rasgos de personalidad positivos y negativos tomando como criterio el bienestar psicológico mediante la implementación de algoritmos de machine learning. Participaron 2038 sujetos adultos (51.9 % mujeres). Para la recolección de datos se utilizó: Big Five Inventory y Mental Health Continuum-Short Form. Además, para evaluar los rasgos positivos y negativos de personalidad se utilizaron los ítems ya validados de los modelos de rasgos positivos (HFM) y negativos (BAM) de forma conjunta. A partir de los hallazgos encontrados se pudo verificar que la eficacia predictiva del modelo testeado de rasgos positivos y negativos derivados de un enfoque léxico resultó superior a la capacidad predictiva de los rasgos normales de personalidad para la predicción del bienestar.
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