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Olabarrieta Landa, Laiene

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https://academica-e.unavarra.es/handle/2454/49667

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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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2022 - 20232
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  • Thumbnail Image
    PublicationOpen Access
    A multidimensional approach to assessing factors impacting health-related quality of life after pediatric traumatic brain injury
    (MDPI, 2023) Von Steinbuechel, Nicole; Krenz, Ugne; Bockhop, Fabian; Koerte, Inga K.; Timmermann, Dagmar; Cunitz, Katrin; Zeldovich, Marina; Andelic, Nada; Rojczyk, Philine; Bonfert, Michaela Veronika; Berweck, Steffen; Kieslich, Matthias; Brockmann, Knut; Roediger, Maike; Lendt, Michael; Buchheim, Anna; Muehlan, Holger; Holloway, Ivana; Olabarrieta Landa, Laiene; Ciencias de la Salud; Osasun Zientziak
    In the field of pediatric traumatic brain injury (TBI), relationships between pre-injury and injury-related characteristics and post-TBI outcomes (functional recovery, post-concussion depression, anxiety) and their impact on disease-specific health-related quality of life (HRQoL) are under-investigated. Here, a multidimensional conceptual model was tested using a structural equation model (SEM). The final SEM evaluates the associations between these four latent variables. We retrospectively investigated 152 children (8–12 years) and 148 adolescents (13–17 years) after TBI at the recruiting clinics or online. The final SEM displayed a fair goodness-of-fit (SRMR = 0.09, RMSEA = 0.08 with 90% CI [0.068, 0.085], GFI = 0.87, CFI = 0.83), explaining 39% of the variance across the four latent variables and 45% of the variance in HRQoL in particular. The relationships between pre-injury and post-injury outcomes and between post-injury outcomes and TBI-specific HRQoL were moderately strong. Especially, pre-injury characteristics (children’s age, sensory, cognitive, or physical impairments, neurological and chronic diseases, and parental education) may aggravate post-injury outcomes, which in turn may influence TBI-specific HRQoL negatively. Thus, the SEM comprises potential risk factors for developing negative post-injury outcomes, impacting TBI-specific HRQoL. Our findings may assist healthcare providers and parents in the management, therapy, rehabilitation, and care of pediatric individuals after TBI.
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    PublicationOpen Access
    Factor structure of the 10-item CES-D scale among patients with persistent COVID-19
    (Wiley, 2022) Ramírez Vélez, Robinson; Olabarrieta Landa, Laiene; Rivera, Diego; Izquierdo Redín, Mikel; Ciencias de la Salud; Osasun Zientziak; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
    The 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 (±standard deviation) ages: 47.4 ± 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(α=0.82Ord;ω=0.78u−cat), somatic retardation factor (α=0.78Ord;ω=0.56u−cat),and positive affect factor (α=0.56Ord;ω=0.55u−cat). The second‐order model fitshowed good Omega reliability (ω=0.87ho). Regarding CFAs, the unidimensional‐factor model shows poor goodness of fit, especially residuals analysis (root meansquare error of approximation [RMSEA] = 0.081 [95% confidence interval,CI = 0.040–0.119]; standardized root mean square residual [SRMR] = 0.101). The two‐factor correlated model, three‐factor correlated model, and second‐order factormodel showed adequate goodness of fit, and theχ2difference test (∆X2) did not show significant differences between the goodness of fit for these models(∆X= 4.11282;p= 0.127). Several indices showed a good fit with the three‐factor correlated model: goodness‐of‐fit 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 cut‐off establishing adequate fit. On the other hand RMSEA = 0.049 (95% CI = 0.000–0.095), where an RMSEA < 0.06–0.08 indicates anadequate fit. Item loadings on the factors were statistically significant (λ≥0.449j;p's < 0.001), indicating that the items loaded correctly on the corresponding factors and the relationship between factors (φ≥0.382;p's≤0.001. To our knowledge, thisis the first study to provide validity and reliability to 10‐item CES‐D in a persistentCOVID‐19 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.