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Title: Advanced psychometric testing on a clinical screening tool to evaluate insomnia : sleep condition indicator in patients with advanced cancer
Authors: Lin, CY 
Cheng, ASK 
Imani, V
Saffari, M
Ohayon, MM
Pakpour, AH
Issue Date: 2020
Source: Sleep and biological rhythms, 2020, p. 1-7
Abstract: Purpose To examine the psychometric properties of the Sleep Condition Indicator (SCI) using different psychometric approaches [including classical test theory, Rasch models, and receiver operating characteristics (ROC) curve] among patients with advanced cancer.
Methods Through convenience sampling, patients with cancer at stage III or IV (n = 859; 511 males; mean +/- SD age = 67.4 +/- 7.5 years) were recruited from several oncology units of university hospitals in Iran. All the participants completed the SCI, Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Hospital Anxiety and Depression Scale (HADS), General Health Questionnaire (GHQ), and Edmonton Symptom Assessment Scale (ESAS). In addition, 491 participants wore an actigraph device to capture objective sleep.
Results Classical test theory [factor loadings from confirmatory factor analysis = 0.76-0.89; test-retest reliability = 0.80-0.93] and Rasch analysis [infit mean square (MnSq) = 0.63-1.31; outfit MnSq = 0.61-1.23] both support the construct validity of the SCI. The SCI had significant associations with ISI, PSQI, ESS, HADS, GHQ, and ESAS. In addition, the SCI has satisfactory area under ROC curve (0.92) when comparing a gold standard of insomnia diagnosis. Significant differences in the actigraphy measure were found between insomniacs and non-insomniacs based on the SCI score defined by ROC.
Conclusion With the promising psychometric properties shown in the SCI, healthcare providers can use this simple assessment tool to target the patients with advanced cancer who are at risk of insomnia and subsequently provide personalized care efficiently.
Keywords: Advanced cancer
Insomnia
Oncology
Psychometric properties
Sleep
Publisher: Springer
Journal: Sleep and biological rhythms 
ISSN: 1446-9235
EISSN: 1479-8425
DOI: 10.1007/s41105-020-00279-5
Rights: © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The following publication Lin, C. Y., Cheng, A. S. K., Imani, V., Saffari, M., Ohayon, M. M., & Pakpour, A. H. (2020). Advanced psychometric testing on a clinical screening tool to evaluate insomnia: Sleep condition indicator in patients with advanced cancer. Sleep and Biological Rhythms, 1-7 is available at https://dx.doi.org/10.1007/s41105-020-00279-5
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