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Advanced psychometr...
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Lin, C. -YDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
(författare)
Advanced psychometric testing on a clinical screening tool to evaluate insomnia : sleep condition indicator in patients with advanced cancer
- Artikel/kapitelEngelska2020
Förlag, utgivningsår, omfång ...
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2020-07-16
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Springer,2020
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printrdacarrier
Nummerbeteckningar
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LIBRIS-ID:oai:DiVA.org:hj-50284
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https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-50284URI
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https://doi.org/10.1007/s41105-020-00279-5DOI
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Språk:engelska
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Sammanfattning på:engelska
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Ämneskategori:ref swepub-contenttype
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Ämneskategori:art swepub-publicationtype
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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.
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Biuppslag (personer, institutioner, konferenser, titlar ...)
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Cheng, A. S. K.Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
(författare)
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Imani, V.Pediatric Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
(författare)
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Saffari, M.Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
(författare)
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Ohayon, M. M.Stanford Sleep Epidemiology Research Center, Stanford University, School of Medicine, Palo Alto, CA 94303, United States
(författare)
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Pakpour, Amir H.Jönköping University,HHJ, Avdelningen för omvårdnad(Swepub:hj)pakami
(författare)
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Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong KongPediatric Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:Sleep and Biological Rhythms: Springer18, s. 343-3491446-92351479-8425
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