Una alternativa de análisis de redes en la exploración de los estados de salud mental, condiciones crónicas y COVID-19
DOI:
https://doi.org/10.17533/udea.iatreia.161Palabras clave:
Comorbilidad , COVID-19 , Diagnóstico , Métodos , Salud Mental , Signos y SíntomasResumen
El análisis de redes es una técnica estadística gráfica que permite visualizar e interpretar intuitivamente asociaciones entre síntomas y múltiples variables vinculadas al funcionamiento y espectro de diversas condiciones de salud. Siendo de relevancia clínica en el contexto actual de la pandemia de COVID-19, y ante su poca difusión en Sudamérica, se tuvo como objetivo un análisis narrativo de este modelo de red durante la pandemia.
Se realizó una revisión narrativa de los estudios empíricos publicados desde mayo de 2020 a julio de 2021 en la base de datos de PubMed y ScienceDirect. Se seleccionaron las investigaciones que utilizaron redes psicométricas de correlación parcial en participantes evaluados durante la pandemia de COVID-19. Esta revisión reporta 13 estudios de red que utilizaron mayormente síntomas relacionados a la ansiedad (7 estudios), depresión (6 estudios) y estrés (6 estudios).
La información resultante se agrupa en 3 grupos (publicaciones en revistas de psiquiatría, ciencias psicológicas, medicina y afines). La revisión presentada refiere que este análisis de red permite una nueva forma de identificar aspectos clínicos mportantes como la comorbilidad, concurrencia de los síntomas y medidas no sintomatológicas, agrupaciones de síntomas con otras variables de naturaleza latente u observable que comparten una causa común, la exploración de nuevas hipótesis clínicas holísticas con variables epidemiológicas, psicológicas, biomédicas y contextuales de mayor interés, como la comparación de sistemas de asociación causal de variables de múltiples niveles en el proceso psicobiológico y sus factores de riesgo y protección en varios periodos de tiempo.
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