Person: Olabarrieta Landa, Laiene
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Olabarrieta Landa
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Laiene
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Ciencias de la Salud
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0000-0002-8305-8720
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811807
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Publication Open Access Network analysis of neurobehavioral symptom patterns in an international sample of spanish-speakers with a history of COVID-19 and controls(MDPI, 2023) Perrin, Paul B.; Ramos Usuga, Daniela; West, Samuel J.; Merced, Kritzia; Klyce, Daniel W.; Lequerica, Anthony H.; Olabarrieta Landa, Laiene; Alzueta, Elisabet; Baker, Fiona C.; Iacovides, Stella; Cortes, Mar; Arango Lasprilla, Juan Carlos; Ciencias de la Salud; Osasun Zientziak; Universidad PĆŗblica de Navarra / Nafarroako Unibertsitate PublikoaBackground: Psychometric network analysis provides a novel statistical approach allowing researchers to model clusters of related symptoms as a dynamic system. This study applied network analysis to investigate the patterns of somatic, cognitive, and affective neurobehavioral symptoms in an international sample of Spanish-speaking individuals with a history of COVID-19 positivity and non-COVID controls; (2) methods: the sample (n = 1093) included 650 adults from 26 countries who reported having previously tested positive for COVID-19 (COVID+) through a viral and/or antigen test (average of 147 days since diagnosis). The control group (COVIDā) was comprised of 443 adults from 20 countries who had completed the survey prior to the COVID19 pandemic; (3) results: relative to the COVIDā network, the COVID+ network was very wellconnected, such that each neurobehavioral symptom was positively connected to the network. The organize-to-headache and dizzy-to-balance connections in the COVID+ network were stronger than in the COVIDā network. The hearing, numbness, and tense symptoms were more central to the COVID+ network with the latter connected to the sleep, fatigue, and frustrated symptoms. The COVIDā network was largely disjointed, with most of the somatosensory symptoms forming their own cluster with no connections to other symptom groups and fatigue not being connected to any other symptom. The cognitive and affective symptoms in the COVIDā network were also largely connected to symptoms from within their own groups; (4) conclusions: These findings suggest that many of the long-term neurobehavioral symptoms of COVID-19 form a discernable network and that headaches, frustration, hearing problems, forgetfulness, and tension are the most central symptoms. Cognitive and behavioral rehabilitation strategies targeting these central symptom network features may hold promise to help fracture the lingering symptom network of COVID-19.Publication Open Access Moderate, little, or no improvements in neurobehavioral symptoms among individuals with long COVID: A 34-country retrospective study(MDPI, 2022) Ramos Usuga, Daniela; Perrin, Paul B.; Bogdanova, Yelena; Olabarrieta Landa, Laiene; Alzueta, Elisabet; Baker, Fiona C.; Iacovides, Stella; Cortes, Mar; Arango Lasprilla, Juan Carlos; Ciencias de la Salud; Osasun Zientziak(1) Background: Some people with COVID-19 develop a series of symptoms that last for several months after infection, known as Long COVID. Although these symptoms interfere with peopleās daily functioning and quality of life, few studies have focused on neurobehavioral symptoms and the risk factors associated with their development; (2) Methods: 1001 adults from 34 countries who had previously tested positive for COVID-19 completed the Neurobehavioral Symptom Inventory reporting the symptoms before their COVID-19 diagnosis, during the COVID-19 infection, and currently; (3) Results: Participants reported large-sized increases before vs. during COVID-19 in all domains. Participants reported a medium-sized improvement (during COVID-19 vs. now) in somatic symptoms, a small-sized improvement in affective symptoms, and very minor/no improvement in cognitive symptoms. The risk factors for increased neurobehavioral symptoms were: being female/trans, unemployed, younger age, low education, having another chronic health condition, greater COVID-19 severity, greater number of days since the COVID-19 diagnosis, not having received oxygen therapy, and having been hospitalized. Additionally, participants from North America, Europe, and Central Asia reported higher levels of symptoms across all domains relative to Latin America and Sub-Saharan Africa; (4) Conclusions: The results highlight the importance of evaluating and treating neurobehavioral symptoms after COVID-19, especially targeting the higher-risk groups identified. General rehabilitation strategies and evidence-based cognitive rehabilitation are needed in both the acute and Long COVID phases.Publication Open Access Factor structure of the 10-item CES-D scale among patients with persistent COVID-19(Wiley, 2022) RamĆrez VĆ©lez, Robinson; Olabarrieta Landa, Laiene; Rivera, Diego; Izquierdo RedĆn, Mikel; Ciencias de la Salud; Osasun Zientziak; Universidad PĆŗblica de Navarra / Nafarroako Unibertsitate PublikoaThe presence of persistent coronavirus disease 2019 (COVID-19) might beassociated with significant levels of psychological distress that would meet thethreshold for clinical relevance. The Center for Epidemiologic Studies DepressionScale (CES-D) version 10 has been widely used in assessing psychological distressamong general and clinical populations from different cultural backgrounds. To ourknowledge, however, researchers have not yet validated these findings amongpatients with persistent COVID-19. A cross-sectional validation study wasconducted with 100 patients from the EXER-COVID project (69.8% women;mean (Ā±standard deviation) ages: 47.4 Ā± 9.5 years). Confirmatory factor analyses(CFAs) were performed on the 10-item CES-D to test four model fits: (a)unidimensional model, (b) two-factor correlated model, (c) three-factor correlatedmodel, and (d) second-order factor model. The diagonal-weighted least-squares estimator was used, as it is commonly applied to latent variable modelswith ordered categorical variables. The reliability indices of the 10-item CES-D in patients with persistent COVID-19 were as follows: depressive affect factor(Ī±=0.82Ord;Ļ=0.78uācat), somatic retardation factor (Ī±=0.78Ord;Ļ=0.56uācat),and positive affect factor (Ī±=0.56Ord;Ļ=0.55uācat). The secondāorder model fitshowed good Omega reliability (Ļ=0.87ho). Regarding CFAs, the unidimensionalāfactor model shows poor goodness of fit, especially residuals analysis (root meansquare error of approximation [RMSEA] = 0.081 [95% confidence interval,CI = 0.040ā0.119]; standardized root mean square residual [SRMR] = 0.101). The twoāfactor correlated model, threeāfactor correlated model, and secondāorder factormodel showed adequate goodness of fit, and theĻ2difference test (āX2) did not show significant differences between the goodness of fit for these models(āX= 4.11282;p= 0.127). Several indices showed a good fit with the threeāfactor correlated model: goodnessāofāfit index = 0.974, comparative fit index = 0.990,relative noncentrality index = 0.990, and incremental fit index = 0.990, which were all above 0.95, the traditional cutāoff establishing adequate fit. On the other hand RMSEA = 0.049 (95% CI = 0.000ā0.095), where an RMSEA < 0.06ā0.08 indicates anadequate fit. Item loadings on the factors were statistically significant (Ī»ā„0.449j;p's < 0.001), indicating that the items loaded correctly on the corresponding factors and the relationship between factors (Ļā„0.382;p'sā¤0.001. To our knowledge, thisis the first study to provide validity and reliability to 10āitem CESāD in a persistentCOVIDā19 Spanish patient sample. The validation and reliability of this shortscreening tool allow us to increase the chance of obtaining complete data in aparticular patient profile with increased fatigue and brain fog that limit patients' capacity to complete questionnaires.