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Psychometric Properties of the Insomnia Severity Index Among Arabic Chronic Diseases Patients

INTRODUCTION: The Insomnia Severity Index (ISI) is a self-administrated questionnaire most frequently used to assess insomnia in clinical and non-clinical populations. OBJECTIVE: To evaluate the psychometric properties of the Arabic ISI among patients diagnosed with chronic diseases. METHODS: A cros...

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Detalles Bibliográficos
Autores principales: Al Maqbali, Mohammed, Madkhali, Norah, Dickens, Geoffrey L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235306/
https://www.ncbi.nlm.nih.gov/pubmed/35769607
http://dx.doi.org/10.1177/23779608221107278
Descripción
Sumario:INTRODUCTION: The Insomnia Severity Index (ISI) is a self-administrated questionnaire most frequently used to assess insomnia in clinical and non-clinical populations. OBJECTIVE: To evaluate the psychometric properties of the Arabic ISI among patients diagnosed with chronic diseases. METHODS: A cross-sectional and descriptive correlational design was used. A total of 1,005 patients with chronic diseases completed the seven items of the Arabic ISI version. The scale was assessed in terms of acceptability, internal consistency, and validity. Construct validity was explored with the use of principal factor analysis and confirmatory factor analysis, to examine the dimensional structure of the ISI. RESULTS: The Cronbach's alpha coefficient for the Arabic ISI was 0.82, which shows good reliability. The total ISI score did not have floor or ceiling effects. There was evidence of discriminate validity. The Principal Component Analysis (PCA) indicated two factors (four items loading on Factor I and three items loading on Factor II). The construct validity of PCA in terms of two factors was explored by confirmatory factor analysis to examine the dimensional structure of the ISI. The confirmatory factor analysis showed an absolute fit for the two-factor model. CONCLUSION: The results support the two-factor structure of ISI. The Arabic version of the ISI demonstrated good reliability and validity for assessing insomnia in patients diagnosed with chronic diseases.