Network analysis of anxiety and depressive symptoms during the COVID‑19 pandemic in older adults in the United Kingdom

dc.contributor.authorRamos Vera, Cristian
dc.contributor.authorBasauri Delgado, Miguel
dc.contributor.authorSaintila, Jacksaint
dc.contributor.authorGarcía O’Diana, Angel
dc.contributor.authorCalizaya-Milla, Yaquelin E.
dc.contributor.unifeBasauri Delgado, Miguel Ángel
dc.date.accessioned2024-06-04T20:05:50Z
dc.date.available2024-06-04T20:05:50Z
dc.date.issued2024
dc.descriptionIndexado en Scopus.es_PE
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Institucional UNIFE. Deberá acceder por el DOI ó URL de la casa editorial externa.es_PE
dc.descriptionScientific Reports; Vol. 14, N° 1; 2024; pp. 7741es_PE
dc.description.abstractThe health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June–July and November–December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: “Nervousness (A1)” and “Inability to relax (A4)” in expected influence and predictability, and “depressed mood (D1”; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology. es_PE
dc.identifier.doihttps://doi.org/10.1038/s41598-024-58256-8es_PE
dc.identifier.journalScientific Reportses_PE
dc.identifier.urihttp://hdl.handle.net/20.500.11955/1250
dc.identifier.urlhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85189307663&doi=10.1038%2fs41598-024-58256-8&origin=inward&txGid=33a395dd6036ce864772a6c9fac5a532
dc.language.isoenges_PE
dc.publisherNature Researches_PE
dc.publisher.countryGBes_PE
dc.relation.ispartofurn:issn:2045-2322es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.sourceRepositorio Institucional - UNIFÉes_PE
dc.subjectAnsiedades_PE
dc.subjectDepresión en ancianoses_PE
dc.subjectCovid-19es_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#5.01.01es_PE
dc.titleNetwork analysis of anxiety and depressive symptoms during the COVID‑19 pandemic in older adults in the United Kingdomes_PE
dc.typeinfo:eu-repo/semantics/articlees_PE

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