Assessment of the Psychometric Properties of the Holland Sleep Disorders Questionnaire in the Iranian Population

Background. Assessing sleep disorders and understanding their causes are essential for the proper treatment and management of the disorders. The Holland Sleep Disorders Questionnaire (HSDQ) is a self-assessment questionnaire that measures sleep problems and symptoms based on the six categories of sleep disorders described in the International Classification of Sleep Disorders-2 (ICSD-2). The aim of this study was at validating and assessing the psychometric properties of the HSDQ in Iranian adults. Method. The study was carried out as a methodological and validation work. The guidelines for translation and cultural adaptation of patient-reported outcome measures were followed for the translation and the cultural validation of the tool. To examine construct validity, exploratory factor analysis (EFA) with 216 participants and confirmatory factor analysis (CFA) with 355 participants were used. As to the reliability, the test-retest method and, as to internal consistency, Cronbach’s alpha were employed. Data analyses were done in SPSS-25 and LISREL-8. Results. The CFA and EFA results confirmed the tool with six factors and 31 items. The index of the model was 0.99, which indicated that 99% of changes in the dependent variable (adults’ sleep problem) were attributed to the independent variable (the 31 items). In other words, 0.99 of the changes in the dependent variable were due to the independent variables. The main indices of CFA (, , , ) were acceptable. In addition, a correlation coefficient below 0.05 was considered as significant. Reliability of the tool based on internal correlation (Cronbach’s alpha) was in the 0.701–0.924 range for the subscales and equal to 0.789 for the whole tool. Conclusion. In general, the results showed that the Farsi version of HSDQ (six factors and 31 items) had acceptable and applicable indices and it can be used as a valid tool in the Iranian society. The tool can be used as a reliable tool in different fields of medical sciences.

1. Introduction
Sleep is a process that is essential for maintaining brain function, and the lack of it can lead to memory and attention impairments [1]. Sleep problems are hazardous for health and treating them is very expensive [2]. Sleep disorders are comorbid of other diseases such as an increased risk of obesity, diabetes, hypertension, tachycardia, and stroke [3]. Sleep disruptions have short-term health consequences (somatic pain, emotional distress, mood disorders, and cognitive, memory, and performance deficits) and also long-term health consequences (hypertension, dyslipidemia, cardiovascular disease, weight-related issues, and colorectal cancer) [4].

Through decreasing the quality of life, sleep deprivation imposes risks to physical, mental, social, and emotional health. In addition, low sleep quality has a relationship with an increase in stress, depression, irritation, and lower satisfaction with life [5]. Changes in sleep pattern are one of the earliest behavioral symptoms of psychophysical problems [6] such as somatic pain, emotional distress, and weight-related issues [4]. The lack of balance in sleep and rest process can create excessive fatigue and nervousness [7].