Objective The aim of this study was to explore the psychometric properties of the Insomnia Severity Index (ISI) based on modern test theory, such as item response theory (IRT) and Rasch analysis, with shortened versions of the ISI among the general population.Methods We conducted two studies to evaluate the reliability and validity of the shortened versions of the ISI in a Korean population. In Study I, conducted via online survey, we performed an exploratory factor analysis (n=400). In Study II, confirmatory factor analysis (CFA) was conducted (n=400). IRT and Rasch analysis were performed on all samples. Participants symptoms were rated using the ISI, Dysfunctional Beliefs and Attitudes about Sleep–16 items, Dysfunctional Beliefs about Sleep–2 items, Patient Health Questionnaire–9 items, and discrepancy between desired time in bed and desired total sleep time.Results CFA showed a good fit for the 2-factor model of the ISI (comparative fit index=0.994, Tucker–Lewis index=0.990, root-meansquare-error of approximation=0.039, and standardized root-mean-square residual=0.046). The 3-item versions also showed a good fit for the model. All scales showed good internal consistency reliability. The scale information curve of the 2-item scale was similar to that of the full-scale ISI. The Rasch analysis outputs suggested a good model fit.Conclusion The shortened 2-factor ISI is a reliable and valid model for assessing the severity of insomnia in the Korean population. The results are needed to be explored further among the clinical sample of insomnia.

Various physiological and psychological functions are influenced by circadian typology (CT), which was reported to be related to resilience. However, few studies have assessed the effects of CT in relation to resilience. The aim of the present study was to assess the influence of CT on sleep-related symptoms, physical fatigue and psychological well-being in relation to resilience. The present study included a total of 1794 healthy hospital employees, and they completed the Morningness–Eveningness Questionnaire, Connor–Davidson Resilience Scale, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Fatigue Severity Scale, Hospital Anxiety and Depression Scale and World Health Organization Quality of Life Scale Abbreviated Version. Subjects with evening type showed lower sleep quality, more daytime sleepiness and physical fatigue than neither types and morning types. Additionally, evening types were more depressed and anxious and reported a poorer quality of life. CT was found to be a significant predictor of sleep quality, but CT was minimally associated with physical fatigue and psychological well-being in the regression analysis. Instead, resilience was substantially related to all of the variables measured. In conclusion, CT independently predicts sleep quality, but the effects of CT on physical fatigue and psychological well-being are negligible compared to those of resilience.

Lee JY, et al. Korean J Radiol. 2020 Jul;21:e171. https://doi.org/10.3348/kjr.2020.0518

Yim Y, et al. Yonsei Med J. 2021 Mar;62(3):255-261. https://doi.org/10.3349/ymj.2021.62.3.255

Background: Insomnia is prevalent among the general population, and studies have shown an increase in insomnia symptoms during the novel coronavirus (COVID-19) pandemic. Despite numerous studies of insomnia, few studies have investigated insomnia symptoms in detail. In this study, we used network analysis to investigate interactions between insomnia symptoms in the general population. Furthermore, given the effect of COVID-19 on mental health, we also investigated how anxiety response to COVID-19 and depression related to insomnia symptoms. Methods: Data from 785 non-infected participants were used. The Insomnia Severity Index (ISI), Stress and Anxiety to Viral Epidemics—6 Scale (SAVE-6), and Patient Health Questionnaire—9 (PHQ-9) were used to measure insomnia symptoms, anxiety response to COVID-19, and depression, respectively. Network analysis was performed using R Studio. Centrality indices and edge weights were obtained, and each index was evaluated using bootstrapping methods. Results: The network revealed ISI7 (worry about current sleep pattern) to be the most central insomnia symptom. ISI7 was strongly connected to SAVE-6 total score, and ISI2 (difficulty staying asleep) was strongly connected to PHQ-9 total score. Conclusion: High centrality of ISI7 supports the role of dysfunctional cognitions in etiological models of insomnia and thus the cognitive behavioral therapy for insomnia. The relationship between ISI7 and SAVE-6 is explained by transposition of worry and fear of contracting COVID-19 to worry about sleep patterns. The link between ISI2 and PHQ-9 necessitate further investigations of whether specific symptoms of insomnia are more associated with depression.