TY - JOUR
T1 - Advanced psychometric testing on a clinical screening tool to evaluate insomnia : sleep condition indicator in patients with advanced cancer
AU - Lin, C.-Y.
AU - Cheng, Andy S. K.
AU - Imani, V.
AU - Saffari, M.
AU - Ohayon, M. M.
AU - Pakpour, A. H.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - https://hdl.handle.net/1959.7/uws:76199
U2 - 10.1007/s41105-020-00279-5
DO - 10.1007/s41105-020-00279-5
M3 - Article
SN - 1446-9235
VL - 18
SP - 343
EP - 349
JO - Sleep and Biological Rhythms
JF - Sleep and Biological Rhythms
IS - 4
ER -
