ABSTRACT
INTRODUCTION: The Pittsburgh Sleep Quality Questionnaire is capable of covering different stages of sleep, and it is regarded as one of the best ones available, and checking for its validity and reliability among depressed patients is a step in this direction. The aim of this study was to evaluate the reliability and validity of the Persian version of the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires in patients with depression. METHODS: In this study, 93 depressed patients were in the study group, and 100 patients were in the control group. The Persian translation of the PSQI and ESS questionnaires and the Beck Depression Inventory (BDI) were at the disposal of both validity and reliability of PSQI and ESS, and its correlation with BDI scores were analyzed. RESULTS: In our study, Cronbach's alpha coefficient of the PSQI questionnaire was 0.821. According to the PSQI and BDI-II scores, the results between the PSQI and ESS scores were significantly correlated. CONCLUSION: Using the Persian PSQI and ESS questionnaires to evaluate sleep quality and daytime sleepiness in patients with depression provides a reliable and valid measure for subjective sleep quality in clinical practice and research.
ABSTRACT
OBJECTIVE: Insomnia is the most common sleep disorder whose origin is attributed to various variables. The current study aims to predict the symptoms of insomnia by investigating some of its predictors. METHODS: Numerous variables such as depression and anxiety symptoms, worry, pre-sleep arousal (cognitive arousal and somatic arousal), dysfunctional cognitions, and metacognitive beliefs about sleep were assessed as insomnia predictors. A total of 400 students of Tehran University of Medical Sciences completed the Depression Anxiety Stress Scale (DASS), the Penn State Worry Questionnaire (PSWQ), the Pre-Sleep Arousal Scale (PSAS), the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-10), the Metacognitions Questionnaire-Insomnia (MCQ-I), and the Insomnia Severity Index (ISI). RESULTS: All variables were significantly correlated with insomnia symptoms (P < .001). Stepwise multiple regression analysis suggested a predictive model for insomnia including cognitive arousal, dysfunctional beliefs about sleep, metacognitive beliefs about sleep, and depressive symptoms. CONCLUSIONS: The findings underline the significant role of cognitive and metacognitive variables for predicting insomnia symptoms. Moreover, the results suggest that metacognitive beliefs about sleep may need to be considered as a significant component in the context of insomnia.
