Inteligencia Artificial Generativa como apoyo para la personalización de intervenciones terapéuticas para la depresión: una revisión exploratoria
DOI:
https://doi.org/10.61347/ei.v5i1.283Palabras clave:
Depresión, inteligencia artificial generativa, personalización, psicoterapia digital, salud mentalResumen
La depresión constituye un problema prioritario de salud pública y, ante la heterogeneidad de la respuesta terapéutica y las barreras de acceso, la inteligencia artificial generativa ha emergido como una alternativa prometedora para apoyar la personalización de intervenciones clínicas. El objetivo de esta revisión exploratoria fue mapear, sintetizar y analizar críticamente la evidencia disponible sobre el uso de la inteligencia artificial generativa en la personalización de intervenciones terapéuticas para la depresión. Se siguieron las directrices PRISMA-ScR y se realizaron búsquedas en las bases de datos Scopus, PubMed y Web of Science sin restricciones de idioma ni de año de publicación. Se recuperaron 47 registros, de los cuales, tras la eliminación de duplicados y el proceso de selección por títulos, resúmenes y texto completo, se incluyeron finalmente 10 estudios originales. Los resultados mostraron una clara predominancia de chatbots terapéuticos basados en modelos de lenguaje a gran escala, así como enfoques híbridos con recuperación de información, monitoreo contextual y aplicaciones multimodales. Asimismo, se identificó que la personalización se implementó principalmente a través de estrategias dinámicas, contextuales, intraindividuales y participativas, orientadas al apoyo emocional, la psicoeducación, la activación conductual, la terapia cognitivo-conductual y la toma de decisiones clínicas. No obstante, persistieron limitaciones relacionadas con tamaños de muestra reducidos, validación clínica insuficiente, presencia de sesgos en los datos, necesidad de supervisión humana, desafíos éticos y barreras de implementación. En conclusión, la inteligencia artificial generativa presenta un potencial significativo para fortalecer las intervenciones terapéuticas personalizadas en la depresión; sin embargo, su adopción clínica requiere el fortalecimiento de la robustez metodológica, la validación en contextos reales y el desarrollo de marcos de seguridad más sólidos.
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Derechos de autor 2026 Johanna Paola Basantes Insuasti, Diego Paul Corrales Vargas, Verónica Alexandra Villa Yánez
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
