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Drinot, P. Coronavirus en el Reino Unido: el costo del excepcionalismo. Hist Cienc Saude Manguinhos 28, 12691274 (2021).

Article PubMed Google Scholar

Snchez Ferro S. LA RESPUESTA BRITNICA FRENTE A LA CRISIS DESATADA POR LA COVID-19. In: Los Efectos Horizontales de la COVID sobre el sistema constitucional. Fundacin Manuel Gimnez Abad, 2020. Epub ahead of print 2020. https://doi.org/10.47919/FMGA.OC20.0022.

Unger, S. & Meiran, W. Student attitudes towards online education during the COVID-19 viral outbreak of 2020: Distance learning in a time of social distance. Int. J. Technol. Educ. Sci. 4, 256266 (2020).

Article Google Scholar

Hettich, N. et al. Impact of the COVID-19 pandemic on depression, anxiety, loneliness, and satisfaction in the German general population: A longitudinal analysis. Soc. Psychiatry Psychiatr. Epidemiol. 57, 24812490 (2022).

Article PubMed PubMed Central Google Scholar

McBride, O. et al. Monitoring the psychological, social, and economic impact of the COVID-19 pandemic in the population: Context, design and conduct of the longitudinal COVID-19 psychological research consortium (C19PRC) study. Int. J. Methods Psychiatr. Res. https://doi.org/10.1002/mpr.1861 (2021).

Article PubMed PubMed Central Google Scholar

Steptoe, A. & Di Gessa, G. Mental health and social interactions of older people with physical disabilities in England during the COVID-19 pandemic: A longitudinal cohort study. Lancet Public Health 6, e365e373 (2021).

Article PubMed PubMed Central Google Scholar

van der Velden, P. G. et al. Anxiety and depression symptoms, the recovery from symptoms, and loneliness before and after the COVID-19 outbreak among the general population: Findings from a Dutch population-based longitudinal study. PLoS ONE 16, e0245057 (2021).

Article PubMed PubMed Central Google Scholar

Umer, A. et al. Depression and sleep issues in aging: A prospective study. Pak. J. Health Sci. 3, 149153 (2022).

Google Scholar

Girdhar, R., Srivastava, V. & Sethi, S. Managing mental health issues among elderly during COVID-19 pandemic. J. Geriatr. Care Res. 7, 3235 (2020).

Google Scholar

Granda-Oblitas, A., Quiroz Gil, G. X. & Runzer Colmenares, F. M. Efectos del aislamiento en adultos mayores durante la pandemia: una revisin de la literatura. Acta Medica Peruana https://doi.org/10.35663/amp.2021.384.2225 (2022).

Article Google Scholar

Grey, I. et al. The role of perceived social support on depression and sleep during the COVID-19 pandemic. Psychiatry Res. 293, 113452 (2020).

Article CAS PubMed PubMed Central Google Scholar

Martnez-Gonzlez, L., Olvera, V. G. & Villarreal, R. E. Efecto de la tcnica de respiracin profunda en el nivel de ansiedad en adultos mayores. Rev Enferm Inst Mex Seguro Soc 26, 99104 (2018).

Google Scholar

King, M. V., Cceres, J. A. G. & Abdulkadir, M. S. Prevalencia de depresin y factores de riesgo asociados a deterioro cognitivo en adultos mayores. Revista Cubana de Medicina General Integral 36, 117 (2021).

Google Scholar

Groen, R. N. et al. Comorbidity between depression and anxiety: Assessing the role of bridge mental states in dynamic psychological networks. BMC Med. 18, 308 (2020).

Article PubMed PubMed Central Google Scholar

Rector, N. A., Szacun-Shimizu, K. & Leybman, M. Anxiety sensitivity within the anxiety disorders: Disorder-specific sensitivities and depression comorbidity. Behav. Res. Ther. 45, 19671975 (2007).

Article PubMed Google Scholar

Hevey, D. Network analysis: A brief overview and tutorial. Health Psychol. Behav. Med. 6, 301328 (2018).

Article PubMed PubMed Central Google Scholar

Ramos-Vera, C. & Serpa-Barrientos, A. Network analysis in clinical research in the COVID-19 context. Rev. Fac. Med. 70, e94407 (2021).

Article Google Scholar

Quintana, R. The ecology of human behavior: A network perspective. Method Innov. 15, 4261 (2022).

Article Google Scholar

Zhao, Y., Tang, Q. & Zhang, C., et al. Anxiety and depression symptoms among older Chinese migrants during COVID-19: A network analysis. PREPRINT Available at Research Square. https://doi.org/10.21203/rs3.rs-3206545/v1.

Zavlis, O. et al. How does the COVID-19 pandemic impact on population mental health? A network analysis of COVID influences on depression, anxiety and traumatic stress in the UK population. Psychol. Med. 52, 38253833 (2022).

Article Google Scholar

Yu, J. & Mahendran, R. COVID-19 lockdown has altered the dynamics between affective symptoms and social isolation among older adults: results from a longitudinal network analysis. Sci. Rep. 11, 14739 (2021).

Article ADS CAS PubMed PubMed Central Google Scholar

Borsboom, D. et al. Network analysis of multivariate data in psychological science. Nat. Rev. Methods Prim. 1, 58 (2021).

Article CAS Google Scholar

Li, W. et al. Network analysis of depression, anxiety, posttraumatic stress symptoms, insomnia, pain, and fatigue in clinically stable older patients with psychiatric disorders during the COVID-19 outbreak. J. Geriatr. Psychiatry Neurol. 35, 196205 (2022).

Article PubMed Google Scholar

Zhang, L. et al. Seeking bridge symptoms of anxiety, depression, and sleep disturbance among the elderly during the lockdown of the COVID-19 pandemicA network approach. Front. Psychiatry https://doi.org/10.3389/fpsyt.2022.919251 (2022).

Article PubMed PubMed Central Google Scholar

Jin, Y. et al. Depressive symptoms and gender differences in older adults in Hong Kong during the COVID-19 pandemic: A network analysis approach. Int. J. Biol. Sci. 18, 39343941 (2022).

Article CAS PubMed PubMed Central Google Scholar

Lange, J. & Zickfeld, J. H. Emotions as overlapping causal networks of emotion components: Implications and methodological approaches. Emot. Rev. 13, 157167 (2021).

Article Google Scholar

Ribeiro, P. H. et al. The performance of the Clique Percolation to identify overlapping symptoms in psychological networks. PsyArXiv https://doi.org/10.31234/osf.io/fk963 (2022).

Article Google Scholar

Dalgleish, T. et al. Transdiagnostic approaches to mental health problems: Current status and future directions. J. Consult. Clin. Psychol. 88, 179195 (2020).

Article PubMed PubMed Central Google Scholar

Garabiles, M. R. et al. Exploring comorbidity between anxiety and depression among migrant Filipino domestic workers: A network approach. J. Affect. Disord. 250, 8593 (2019).

Article PubMed Google Scholar

Owczarek, M. et al. How is loneliness related to anxiety and depression: A population-based network analysis in the early lockdown period. Int. J. Psychol. 57, 585596 (2022).

Article PubMed PubMed Central Google Scholar

Ramos-Vera, C. et al. Psychological impact of COVID-19: A cross-lagged network analysis from the English Longitudinal Study of Aging COVID-19 database. Front. Psychiatry https://doi.org/10.3389/fpsyt.2023.1124257 (2023).

Article PubMed PubMed Central Google Scholar

Di Gessa, G. & Zaninotto, P. Health behaviors and mental health during the COVID-19 pandemic: Evidence from the English longitudinal study of aging. J. Appl. Gerontol. 42, 15411550 (2023).

Article PubMed PubMed Central Google Scholar

Radloff, L. S. The CES-D scale. Appl. Psychol. Meas. 1, 385401 (1977).

Article Google Scholar

Spitzer, R. L. et al. A brief measure for assessing generalized anxiety disorder. Arch. Intern. Med. 166, 1092 (2006).

Article PubMed Google Scholar

R Core Team. R: A language and environment for statistical computing (4.2.1 Funny-Looking Kid). R Core Team. https://www.r-project.org/ (2022). Accessed 5 September 2023.

Epskamp, S. et al. qgraph: Network visualizations of relationships in psychometric data. J. Stat. Softw. https://doi.org/10.18637/jss.v048.i04 (2012).

Article Google Scholar

Csardi G, NT. igraph: Network analysis and visualization (1.3.5). R-CRAN. R-CRAN. https://CRAN.R-project.org/package=igraph (2022). Accessed 4 September 2023.

Csrdi, G. & Nepusz, T. The igraph software package for complex network research. InterJ. Complex Syst. 1695, 19 (2006).

Google Scholar

Epskamp S. bootnet: Bootstrap methods for various network estimation routines (1.5). R-CRAN. https://cran.r-project.org/package=bootnet (2021). Accessed 5 September 2023.

Lange, J. CliquePercolation: An R package for conducting and visualizing results of the clique percolation network community detection algorithm. J. Open Source Softw. 6, 3210 (2021).

Article ADS Google Scholar

Jones P. Networktools: Tools for identifying important nodes in networks (1.5.0). R-CRAN. https://cran.r-project.org/package=networktools (2022). Accessed 5 September 2023.

van Borkulo, C., Epskamp, S. & Jones P. NetworkComparisonTest: Statistical comparison of two networks based on three invariance measures (2.2.1). R-CRAN. https://CRAN.R-project.org/package=NetworkComparisonTest (2019). Accessed 5 September 2023.

Rosseel, Y. lavaan: An R package for structural equation modeling. J. Stat. Softw. https://doi.org/10.18637/jss.v048.i02 (2012).

Article Google Scholar

Jiang, H., Fei, X., Liu, H., Roeder, K., Lafferty, J., Wasserman, L., Li, X. & Zhao, T.. huge: High-dimensional undirected graph estimation (1.3.5). R-CRAN. https://cran.r-project.org/package=huge (2019). Accessed 5 September 2023.

Zhao, T. et al. The huge package for high-dimensional undirected graph estimation in R. J. Mach. Learn. Res. 13, 10591062 (2012).

MathSciNet PubMed PubMed Central Google Scholar

Liu, H., Lafferty, J. & Wasserman, L. The nonparanormal: Semiparametric estimation of high dimensional undirected graphs. J. Mach. Learn. Res. 10, 22952328 (2009).

MathSciNet Google Scholar

Lysen, S. Permuted Inclusion Criterion: A Variable Selection Technique. Dissertation, University of Pennsylvania (2009).

Epskamp, S., Borsboom, D. & Fried, E. I. Estimating psychological networks and their accuracy: A tutorial paper. Behav. Res. Methods 50, 195212 (2018).

Article PubMed Google Scholar

Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004).

Article ADS CAS Google Scholar

Reichardt, J. & Bornholdt, S. Statistical mechanics of community detection. Phys. Rev. E 74, 016110 (2006).

Article ADS MathSciNet Google Scholar

Traag, V. A. & Bruggeman, J. Community detection in networks with positive and negative links. Phys. Rev. E 80, 036115 (2009).

Article ADS CAS Google Scholar

Robinaugh, D. J., Millner, A. J. & McNally, R. J. Identifying highly influential nodes in the complicated grief network. J. Abnorm. Psychol. 125, 747757 (2016).

Article PubMed PubMed Central Google Scholar

Adamcsek, B. et al. CFinder: Locating cliques and overlapping modules in biological networks. Bioinformatics 22, 10211023 (2006).

Article CAS PubMed Google Scholar

Hochberg, Y. & Tamhane, A. C. Stepwise procedures for pairwise and more general comparisons among all treatments. In: Wiley Series in Probability and Statistics 110133 (1987).

van Borkulo, C. D. et al. Comparing network structures on three aspects: A permutation test. Psychol. Methods https://doi.org/10.1037/met0000476 (2022).

Article PubMed Google Scholar

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