Research Article: A classical test theory evaluation of the Sleep Condition Indicator accounting for the ordinal nature of item response data

Date Published: March 14, 2019

Publisher: Public Library of Science

Author(s): Amanda Hellström, Peter Hagell, Anders Broström, Martin Ulander, Annemarie I. Luik, Colin A. Espie, Kristofer Årestedt, Agustin Martínez Molina.


Insomnia symptoms are common among young adults and affect about 5% to 26% of 19 to 34-year-olds. In addition, insomnia is associated with poor mental health and may affect daily performance. In research, as well as in clinical practice, sleep questionnaires are used to screen for and diagnose insomnia. However, most questionnaires are not developed according to current DSM-5 diagnostic criteria. An exception is the recently developed Sleep Condition Indicator (SCI), an eight-item scale screening for insomnia.

The aim of this study was to perform a Classical Test Theory (CTT) based psychometric evaluation of the SCI in a sample of Swedish university students, by taking the ordinal nature of item level data into account.

The SCI was translated into Swedish and distributed online to undergraduate students at three Swedish universities, within programs of health, psychology, science or economy. Of 3673 invited students, 634 (mean age 26.9 years; SD = 7.4) completed the questionnaire that, in addition to the SCI, comprised other scales on sleep, stress, lifestyle and students’ study environment. Data were analyzed according to CTT investigating data completeness, item homogeneity and unidimensionality.

Polychoric based explorative factor analysis suggested unidimensionality of the SCI, and internal consistency was good (Cronbach’s alpha, 0.91; ordinal alpha, 0.94). SCI scores correlated with the Insomnia Severity Index (-0.88) as well as with sleep quality (-0.85) and perceived stress (-0.50), supporting external construct validity.

These observations support the integrity of the of the SCI. The SCI demonstrates sound CTT-based psychometric properties, supporting its use as an insomnia screening tool.

Partial Text

Insomnia disorder is defined as difficulty initiating or maintaining sleep and/or waking up too early, accompanied by daytime complaints for at least 3 days a week for 3 or more months [1]. Insomnia is associated with a range of health problems, such as cardiovascular disorders and type 2 diabetes, and mental disorders such as depression, anxiety, bipolar disorder and suicidal ideation [2, 3]. There is a preponderance of insomnia in women compared to men [4, 5] and there is an age-related increase in prevalence [6]. Insomnia symptoms have been reported in 5.3% – 26.3% of young adults (19–34 years) in the general population [4], with a somewhat higher rate (9.5% – 39.4%) among university students [7, 8].

The aim of this study was to perform a CTT based psychometric evaluation of the SCI by taking the ordinal nature of item level data into account. This is, to the best of our knowledge, the first study to address the psychometric properties of the SCI using CTT methods appropriate for ordinal level data. Our observations provide initial support for the psychometric properties of the SCI.

Our CTT-based psychometric testing supports the SCI as a user-friendly, unidimensional insomnia screening tool, with high internal consistency. Future research should address its psychometric properties across more diverse populations, and evaluate additional properties such as responsiveness and differential item functioning.




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