Repository of Research and Investigative Information

Repository of Research and Investigative Information

Baqiyatallah University of Medical Sciences

Advanced psychometric testing on a clinical screening tool to evaluate insomnia: sleep condition indicator in patients with advanced cancer

(2020) Advanced psychometric testing on a clinical screening tool to evaluate insomnia: sleep condition indicator in patients with advanced cancer. Sleep and Biological Rhythms. pp. 343-349. ISSN 1446-9235

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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.

Item Type: Article
Keywords: Advanced cancer Insomnia Oncology Psychometric properties Sleep persian version severity index scale validation validity quality reliability disturbance disorder fatigue Neurosciences & Neurology
Page Range: pp. 343-349
Journal or Publication Title: Sleep and Biological Rhythms
Journal Index: ISI
Volume: 18
Number: 4
Identification Number: https://doi.org/10.1007/s41105-020-00279-5
ISSN: 1446-9235
Depositing User: مهندس مهدی شریفی
URI: http://eprints.bmsu.ac.ir/id/eprint/8702

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