Explorando la validez de constructo del índice de Barthel en una muestra de pacientes hospitalizados españoles / Exploring the construct validity of the Barthel index in a sample of Spanish hospitalised patients

Objetivo: Examinar la validez de constructo del índice de Barthel en unidades de hospitalización de adultos. Métodos: Se realizó un análisis secundario en una muestra de 1.342 pacientes adultos ingresados en unidades de hospitalización. El análisis factorial confirmatorio del índice de Barthel no confirma su estructura unidimensional (CFA-1). Se exploraron dos métodos para encontrar una solución con un mejor ajuste. Se realizó la secuencia de los métodos clásicos de análisis factorial exploratorio y confirmatorio (CFA-2). Se realizó un modelo gráfico gaussiano y un análisis factorial confirmatorio (CFA-3). Se compararon tres modelos sobre una base de varios indicadores de bondad de ajuste. Resultados: Los resultados del CFA-1 (χ2 = 161.616; p < 0,001; RMSEA = 0,183) indicaron un mal ajuste entre el modelo y los datos obtenidos. El análisis factorial exploratorio proporcionó un modelo con dos dimensiones que explicaba 86% de la varianza y mejoró el indicador de bondad de ajuste en CFA-2 (χ2 = 846; p < 0,001; RMSEA = 0,133). El modelo gráfico gaussiano ofreció una solución con tres dimensiones que mejoró la bondad de ajuste con respecto a los modelos anteriores al eliminar el ítem continencia vesical (χ2 = 493; p < 0,001; RMSEA = 0,09). Conclusiones: El índice de Barthel no es una medida unidimensional de la capacidad funcional cuando se aplica en unidades de hospitalización de adultos. El modelo que mejor se ajusta tiene una estructura tridimensional (higiene, alimentación y eliminación, movilidad) que se relaciona con los dominios de los cuidados básicos.(AU)

Objective: Examine the construct validity of the Barthel Index in adult inpatient units. Methods: A secondary analysis was performed on a sample of 1342 adult patients admitted to inpatient units. A confirmatory factor analysis of the Barthel Index did not confirm its unidimensional structure (CFA-1). Therefore, two methods were explored to find a solution with a better fit. The sequence of the classical exploratory and confirmatory factor analysis methods was carried out (CFA-2). In contrast, a Gaussian graphical model and confirmatory factor analysis (CFA-3) were performed. Three models were compared on the basis of several goodness-of-fit indicators. Results: CFA-1 results (χ2 = 161616; P < .001; RMSEA = .183) indicated a poor fit between the model and the data. Exploratory factor analysis provided a model with two dimensions that explained 86% of the variance and improved the goodness-of-fit in CFA-2 (χ2 = 846; P < .001; RMSEA = .133). The Gaussian graphical model, by removing the item ‘Bladder’, offered a solution with three dimensions that improved the goodness-of-fit compared to the previous models (χ2 = 492; P < .001; RMSEA = .09). Conclusions: The Barthel Index is not a unidimensional measure of functional capacity when applied to adult inpatient units. The best-fitting model has a three-dimensional structure (Hygiene; Feeding and disposal; Mobility) that relates to the domains of care needs.

Exploring the construct validity of the Barthel index in a sample of Spanish hospitalised patients.

OBJECTIVE: Examine the construct validity of the Barthel Index in adult inpatient units. METHOD: A secondary analysis was performed on a sample of 1342 adult patients admitted to inpatient units. A confirmatory factor analysis of the Barthel Index did not confirm its unidimensional structure (CFA-1). Therefore, two methods were explored to find a solution with a better fit. The sequence of the classical exploratory and confirmatory factor analysis methods was carried out (CFA-2). In contrast, a Gaussian graphical model and confirmatory factor analysis (CFA-3) were performed. Three models were compared on the basis of several goodness-of-fit indicators. RESULTS: CFA-1 results (χ2 = 161,616; P < .001; RMSEA = .183) indicated a poor fit between the model and the data. Exploratory factor analysis provided a model with two dimensions that explained 86% of the variance and improved the goodness-of-fit in CFA-2 (χ2 = 846; P < .001; RMSEA = .133). The Gaussian graphical model, by removing the item 'Bladder', offered a solution with three dimensions that improved the goodness-of-fit compared to the previous models (χ2 = 492; P < .001; RMSEA = .09). CONCLUSION: The Barthel Index is not a unidimensional measure of functional capacity when applied to adult inpatient units. The best-fitting model has a three-dimensional structure (Hygiene; Feeding and disposal; Mobility) that relates to the domains of care needs.

COVID-19 Vaccines Safety Tracking (CoVaST): Protocol of a Multi-Center Prospective Cohort Study for Active Surveillance of COVID-19 Vaccines' Side Effects.

BACKGROUND: Coronavirus disease (COVID-19) vaccine-related side effects have a determinant role in the public decision regarding vaccination. Therefore, this study has been designed to actively monitor the safety and effectiveness of COVID-19 vaccines globally. METHODS: A multi-country, three-phase study including a cross-sectional survey to test for the short-term side effects of COVID-19 vaccines among target population groups. In the second phase, we will monitor the booster doses' side effects, while in the third phase, the long-term safety and effectiveness will be investigated. A validated, self-administered questionnaire will be used to collect data from the target population; Results: The study protocol has been registered at ClinicalTrials.gov, with the identifier NCT04834869. CONCLUSIONS: CoVaST is the first independent study aiming to monitor the side effects of COVID-19 vaccines following booster doses, and the long-term safety and effectiveness of said vaccines.

A systematic survey instrument translation process for multi-country, comparative health workforce studies.

BACKGROUND: As health services research (HSR) expands across the globe, researchers will adopt health services and health worker evaluation instruments developed in one country for use in another. This paper explores the cross-cultural methodological challenges involved in translating HSR in the language and context of different health systems. OBJECTIVES: To describe the pre-data collection systematic translation process used in a twelve country, eleven language nursing workforce survey. DESIGN AND SETTINGS: We illustrate the potential advantages of Content Validity Indexing (CVI) techniques to validate a nursing workforce survey developed for RN4CAST, a twelve country (Belgium, England, Finland, Germany, Greece, Ireland, Netherlands, Norway, Poland, Spain, Sweden, and Switzerland), eleven language (with modifications for regional dialects, including Dutch, English, Finnish, French, German, Greek, Italian, Norwegian, Polish, Spanish, and Swedish), comparative nursing workforce study in Europe. PARTICIPANTS: Expert review panels comprised of practicing nurses from twelve European countries who evaluated cross-cultural relevance, including translation, of a nursing workforce survey instrument developed by experts in the field. METHODS: The method described in this paper used Content Validity Indexing (CVI) techniques with chance correction and provides researchers with a systematic approach for standardizing language translation processes while simultaneously evaluating the cross-cultural applicability of a survey instrument in the new context. RESULTS: The cross-cultural evaluation process produced CVI scores for the instrument ranging from .61 to .95. The process successfully identified potentially problematic survey items and errors with translation. CONCLUSIONS: The translation approach described here may help researchers reduce threats to data validity and improve instrument reliability in multinational health services research studies involving comparisons across health systems and language translation.