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Components of Pittsburgh Sleep Quality Index in Iranian Adult Population: An Item Response Theory Model Publisher



Khosravi A1 ; Emamian MH2 ; Hashemi H3 ; Fotouhi A4
Authors
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Authors Affiliations
  1. 1. Center for Health Related Social and Behavioral Sciences Research, Shahroud University of, Medical Sciences, Shahroud, Iran
  2. 2. Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran
  3. 3. Noor Ophthalmology Research Center, Noor Eye Hospital, Tehran, Iran
  4. 4. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Source: Sleep Medicine: X Published:2021


Abstract

Objective/background: There have been conducted few studies in Iran on the quality of sleep in the general population. This study aimed to use the item response theory (IRT) model to examine the accuracy of the seven components of the Pittsburgh Sleep Quality Index (PSQI) and to provide an appropriate cut-off point for population-based studies. Methods: This study was performed using the data of the second phase of the Shahroud Eye Cohort Study (ShECS) in 2014. The sleep quality of 4710 participants was measured through PSQI. Using an IRT model, the seven components of the index are considered as indicators and sleep quality as the latent variable in the measurement model. This model supposed that there is only one hidden component to explain the respondent's behavior to a number of items. Results: Results of analyzing different components of PSQI showed that component 6 (using sleep medication) and 7 (daytime dysfunction disorder) had the lowest values of discrimination parameter and component 4 (habitual sleep efficiency) and 1 (sleep quality) had the highest value of discrimination parameter. Persons with an expected sleep quality score of less than or equal to 6.5 will be defined as good sleep quality pattern. Conclusions: Since discrimination values for components 6 and 7 are less than the values for other components, the use of the standardized latent scores is emphasized for assessing the quality of sleep in the population. © 2021 The Author(s)
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