Psychometric properties and measurement invariance of the Arabic Self-Care Inventory

Jehad A Rababah, Mohammed Munther Al-Hammouri and Michela Luciani

PLOS ONE, 2023, vol. 18, issue 9, 1-14

Abstract: Background: Self-care is a fundamental aspect of health and well-being for healthy individuals and those with chronic illnesses. However, the available self-care measurement instruments have limited support regarding their psychometric properties. Research about the validation of comprehensive, theory-based self-care tools in the Arabic language and culture is also limited. In addition, many self-care measurement tools are available only for people with chronic illnesses. Objective: To examine the psychometric properties of the Arabic version of the Self-care Inventory (SCI) in the general adult population in Jordan. Methods: This study was conducted using a cross-sectional design. Data collection was performed using a demographics questionnaire, and Arabic versions of the SCI, Self-care Self-Efficacy, and the Center for Epidemiologic Studies Depression Scale-revised. SPSS and AMOS were used to analyze the data. Data analysis was conducted by performing confirmatory factor analysis, measurement invariance, internal consistency, and bivariate correlations. Results: The results revealed that the SCI comprises three scales: self-care maintenance, self-care monitoring, and self-care management. The goodness of mode fit indices showed that the models of these scales fit the data well by meeting the following set a priori criteria: (RMSEA .95, and X2/df

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0291904

DOI: 10.1371/journal.pone.0291904

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