Auto-revelación y agentes relacionales para la salud mental: un protocolo de revisión de alcance

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Sia Sha¹, Kate Loveys², Isla Francis³

¹The London School of Economics and Political Science, London, UK.

|August 24, 2025

Resumen

Esta revisión de alcance mapea la literatura sobre la auto-revelación en los agentes relacionales para la salud mental. Comprender cómo los pacientes comparten información con los chatbots de IA es crucial para mejorar los resultados terapéuticos y reducir los tiempos de espera para los servicios de salud mental.

Área de la Ciencia:

Interacción hombre-computadora
Tecnología de la salud mental
Inteligencia artificial en el cuidado de la salud

Sus antecedentes:

Los agentes relacionales, una forma de chatbots de IA, son herramientas emergentes para abordar los tiempos de espera del servicio de salud mental.
Estos agentes tienen como objetivo construir relaciones terapéuticas con los pacientes a través de interfaces conversacionales.
La autodescubrimiento eficaz del paciente es vital para obtener resultados terapéuticos positivos en las intervenciones de salud mental.

Objetivo del estudio:

Realizar una revisión de alcance de la literatura existente sobre la auto-divulgación en los agentes relacionales para la salud mental.
Identificar y sintetizar la investigación sobre cómo los pacientes se involucran en la auto-divulgación con IA en un contexto terapéutico.
Mapear el panorama actual de la investigación e identificar las brechas en la comprensión de la dinámica de la auto-divulgación con las herramientas de salud mental de la IA.

Principales métodos:

La revisión sigue las directrices del Instituto Joanna Briggs y la Extensión PRISMA para las revisiones de alcance.
Se llevará a cabo una búsqueda sistemática en las principales bases de datos académicas (Ovid, EBSCO, Scopus, Web of Science, ProQuest).
Dos revisores independientes examinarán los estudios, incluidas las investigaciones cualitativas y cuantitativas publicadas en inglés, con una síntesis narrativa de los resultados.

Principales resultados:

La revisión sintetizará los hallazgos sobre la naturaleza, el alcance y el impacto de la autorrevelación a los agentes relacionales.
Las tablas de datos presentarán las características clave de los estudios incluidos.
Una síntesis narrativa resumirá las tendencias y los patrones en la literatura.

Conclusiones:

Los hallazgos servirán de base para el desarrollo y la aplicación de herramientas de salud mental más eficaces basadas en la IA.
Comprender la auto-revelación es clave para optimizar el compromiso del paciente y la alianza terapéutica con los agentes relacionales.
Esta revisión resaltará las áreas para futuras investigaciones en IA y atención de la salud mental.

Palabras clave:

Informática de la salud Salud mental Salud pública

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