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1.	Hellström, Amanda, et al. (författare) A classical test theory evaluation of the Sleep Condition Indicator accounting for the ordinal nature of item response data 2019 Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 14:3, s. 1-13 Tidskriftsartikel (refereegranskat)abstract Background 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. Aim 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. Methods 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. Results 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. Conclusions 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.

Hellström, Amanda, et al. (författare)
A classical test theory evaluation of the Sleep Condition Indicator accounting for the ordinal nature of item response data
2019
Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 14:3, s. 1-13
Tidskriftsartikel (refereegranskat)abstract
- Background 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. Aim 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. Methods 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. Results 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. Conclusions 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.

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