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Network analysis in clinical research
El análisis de redes en la investigación clínica
Palabras clave:
COVID-19, SARS-CoV-2, Pandemics, Network Meta-Analysis (en)COVID-19, SARS-CoV-2, Pandemias, Metaanálisis en red (es)
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A study published in Issue 1 of Volume 69 of this Journal evaluated burnout levels in Colombian medical residents and demonstrated the impact of this syndrome on those suffering from it.1 Burnout is a response to the emotional and interpersonal problems that arise at work, and it involves feelings of exhaustion, indifference, perception of incompetence due to a lack of resources to cope with responsibilities, dissatisfaction, and low self-esteem.2
En el número 1 del volumen 69 de la presente revista se publicó un
estudio que evaluó los niveles del burnout en residentes de medicina en
Colombia y que evidenció el impacto que puede causar este síndrome en
quienes lo padecen.1 El burnout es una respuesta a los problemas
emocionales e interpersonales que se presentan en el trabajo y en la
cual intervienen sentimientos de agotamiento, actitud indiferente,
percepción de incompetencia ante la falta de recursos para afrontar las
responsabilidades, insatisfacción y baja autoestima.2
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Larrotta-Castillo D, Cruz-Marroquín C, Rodríguez-Peñuela J, Alzate-Granados JP, Cote-Menéndez M, Galván-Villamarín JF. Ad honorem exhaustion: Burnout prevalence in residents from a Colombian university. Rev. Fac. Med. 2021;69(1):e82687. https://doi.org/f7ts.
Maslach C, Schaufeli WB, Leiter MP. Job Burnout. Annu Rev Psychol. 2001;52(1):397-422. https://doi.org/b2w8ff.
Sahu P. Closure of Universities Due to Coronavirus Disease 2019 (COVID-19): Impact on Education and Mental Health of Students and Academic Staff. Cureus. 2020;12(4):e7541. https://doi.org/ggq9zm.
Scott J, Carrington PJ, editors. The SAGE handbook of social network analysis. Los Angeles: SAGE; 2014.
Hevey D. Network analysis: a brief overview and tutorial. Health Psychol Behav Med. 2018;6(1):301-28. https://doi.org/gghm78.
Robinaugh DJ, Hoekstra RHA, Toner ER, Borsboom D. The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research. Psychol. Med. 2020;50(3):353-66. https://doi.org/gghndf.
Isvoranu AM, Abdin E, Chong SA, Vaingankar J, Boorsbom D, Subramaniam S. Extended network analysis: from psychopathology to chronic illness. BMC Psychiatry. 2021;21(1):119. https://doi.org/f7tx.
Van Bork R, Rhemtulla M, Waldorp LJ, Kruis J, Rezvanifar S, Borsboom D. Latent Variable Models and Networks: Statistical Equivalence and Testability. Multivariate Behav Res. 2019:1-24. https://doi.org/ggf5h5.
Peixoto EM, Palma B, Farias I, Santana N, Zanini D, Bueno JM. Questionário de Impulsividade, Autoagressão e Ideação Suicida para Adolescentes (QIAIS-A): propriedades psicométricas. Psicologia, Saúde & Doenças. 2019;20(2):271-85. https://doi.org/f7t8.
Ramos-Vera CA, Ramírez Y, Rojas, E, Serpa A, García FE. Evidencias psicométricas mediante SEM y análisis de red de la Escala de Crecimiento Postraumático en adolescentes peruanos. Psi Conductual. 2021;29(2):417-36. https://doi.org/hsj9.
Derks K, Burger J, van Doorn J, Kossakowski JJ, Matzke D, Atticciati, L, et al. Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance. J Eur Psychol Students. 2018;9(1):48-57. https://doi.org/gghm8s.
Di Blasi M, Gullo S, Mancinelli E, Freda MF, Esposito G, Gelo OCG, et al. Psychological distress associated with the COVID-19 lockdown: A two-wave network analysis. J Affect Disord. 2021;284:18-26. https://doi.org/f7vj.
Fried EI, von Stockert S, Haslbeck JMB, Lamers F, Schoevers RA, Penninx BWJH. Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates. Psychol Med. 2020;50(16):2682-90. https://doi.org/gg6378.
Tosi G, Borsani C, Castiglioni S, Daini R, Franceschi M, Romano D. Complexity in neuropsychological assessments of cognitive impairment: A network analysis approach. Cortex. 2020;124:85-96. https://doi.org/gh5dvd.
Hilland E, Landrø NI, Kraft B, Tamnes CK, Fried EI, Maglanoc LA, et al. Exploring the links between specific depression symptoms and brain structure: A network study. Psychiatry Clin Neurosci. 2020;74(3):220-1. https://doi.org/f7v2.
Isvoranu AM, Guloksuz S, Epskamp S, van Os J, Borsboom D. Toward incorporating genetic risk scores into symptom networks of psychosis. Psychol Med. 2020;50(4):636-43. https://doi.org/gg3hcz.
Kappelmann N, Czamara D, Rost N, Moser S, Schmoll V, Trastulla L, et al. Polygenic risk for immuno-metabolic markers and specific depressive symptoms: A multi-sample network analysis study. medRxiv. 2021. https://doi.org/gb9s.
Lunansky G, van Borkulo CD, Haslbeck JMB, van der Linden MA, Garay CJ, Etchevers MJ, et al. The Mental Health Ecosystem: Extending Symptom Networks with Risk and Protective Factors. Front Psychiatry. 2021;12:640658. https://doi.org/gjjf89.
Ramos-Vera CA. Red de síntomas psicopatológicos de la conducta alimentaria, depresión, ansiedad y estrés postraumático en adultos peruanos en cuarentena por COVID-19. Rev cubana Enferm. 2021 [cited 2021 Mar 14]; 37(Suppl 1):e4200. Available from: https://bit.ly/3tFz6jG.
Ramos-Vera CA. Las características dinámicas de la salud mental en adultos peruanos durante la cuarentena por COVID-19. Medisur. 2021 [cited 2021 Abr 14]; 19(2). Available from: https://bit.ly/3NsFap7.
Martín-Brufau R, Suso-Ribera C, Corbalán J. Emotion Network Analysis During COVID-19 Quarantine - A Longitudinal Study. Front Psychol. 2020;11:e559572. https://doi.org/f7vk.
Ramos-Vera C, Baños-Chaparro, J, Ogundokun RO. The network structure of depressive symptomatology in Peruvian adults with arterial hypertension [version 3; peer review: 2 approved]. F1000Research. 2022;10:19. https://doi.org/hw4j.
Ramos-Vera CA. Conceptos de interés en la atención integral de los pacientes con multimorbilidad. Aten Primaria. 2021;53(6): e101969. https://doi.org/f7v3.
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Derechos de autor 2021 Revista de la Facultad de Medicina
Esta obra está bajo una licencia Creative Commons Reconocimiento 3.0 Unported.
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