Study of the Glasgow Sleep Effort Scale (GSES) psychometric properties through CTT, IRT and network analysis

• Autor(a) principal: Dias, Sofia Alexandra Fontoura
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/32886
• topic: Insomnia; Sleep effort; Psychometrics; Classical test theory; Item response theory; Network analysis

The Glasgow Sleep Effort Scale (GSES) was developed with the aim of measuring sleep effort. The present study evaluates the psychometric properties of the European Portuguese version of the GSES through Classical Test Theory (CTT), Item Response Theory (IRT), and Network Analysis (NA). It was used an existing database comprising a community sample of 227 Portuguese adults, aged 20–74 (M = 42.99; SD = 12.44) years old, encopassing 49.8% men and 50.2% women. In CFA, a well-adjusted to data one-factor model was identified, with sleep effort as the single factor. IRT analysis indicated an adequate performance of all items and satisfactory coverage of the latent trait, with items 3 (a = 3.37), 4 (a = 3 .18), and 6 (a = 3.02) as the most discriminative ones. Considering NA, items 4 and 7 presented the strongest edge weight (.48). Item 1 was displayed at the centre of the networks and accounted for the largest number of connections with the remaining items. The results suggest that the GSES is a reliable measure, comprising highly discriminative items with good centrality indices. Moreover, the measure is particularly important in the evaluation of individuals with moderate to severe levels of sleep effort. We underline the application of more contemporary psychometric techniques (IRT and NA) beyond CTT in the emergent sophistication of measures with the integration of approaches. Specifically, this study builds upon the evidence regarding the development of shorter, yet reliable and valid measures in the sleep medicine area to face the overloading of patients with extensive research protocols and clinical evaluations.