Diagnóstico de síntomas depresivos mediante dispositivos móviles: una revisión sistemática
DOI:
https://doi.org/10.37914/riis.v8i2.439Palabras clave:
revisión sistemática, trastorno depresivo, sensores remotos, mHealthResumen
Marco contextual: la depresión es un problema de salud mental generalizado, a menudo infradiagnosticado y subtratado debido a la dependencia de autoinformes subjetivos y al acceso limitado a la atención. Las tecnologías de salud móvil (mHealth), que utilizan sensores de teléfonos inteligentes y portátiles, ofrecen soluciones innovadoras para diagnósticos objetivos y escalables. Objetivos: esta revisión examina la eficacia de los sensores de dispositivos móviles para diagnosticar la depresión, identificar bioseñales relevantes y explorar métodos de diagnóstico. Metodología: se realizó una búsqueda sistemática siguiendo las pautas PRISMA-DTA en MEDLINE/PubMed y Embase, centrándose en la precisión diagnóstica de los sensores mHealth validados contra estándares de oro como DSM-5 o PHQ-9. Resultados: once estudios mostraron que los acelerómetros y los monitores de frecuencia cardíaca son clave para detectar movimiento, actividad y patrones fisiológicos vinculados a la depresión. Los algoritmos de aprendizaje automático, especialmente los bosques aleatorios, lograron una alta precisión diagnóstica. Conclusión: las tecnologías mHealth son prometedoras para el diagnóstico de la depresión, pero se necesitan mejoras en la consistencia metodológica, el tamaño de la muestra y la validación externa para un uso clínico más amplio.
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Derechos de autor 2025 Matheus Damasceno, Paulo Abrantes, André Takahata, Antonio Valerio Netto
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
