Background: No study has examined the psychometric properties of the sleep condition indicator (SCI) for screening poststroke insomnia in the Indonesian population. We aimed to develop the Indonesian version of the sleep condition indicator (ISCI) and to examine its psychometric properties for screening adult patients in late sub-acute and chronic periods after stroke.
Methods: This was a cross-sectional study with two stages. In the first stage, the English version of the SCI was translated into the ISCI using standard procedures. The psychometric properties of the ISCI were tested in the second stage. Internal consistency and test-retest reliability of ISCI were used to evaluate reliability. A confirmatory factor analysis (CFA) was performed to test construct validity. To test concurrent and convergent validity, the Indonesian version of the insomnia severity index (ISI-INA), generalized anxiety disorder questionnaire (IGAD-7), and patient health questionnaire (IPHQ-9) were used. A receiver operating characteristic (ROC) analysis was conducted to calculate the optimal cutoff score of the ISCI on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for insomnia.
Results: A total of 160 adults with a diagnosis of stroke for more than 3 months were included (median age of 58.5 years, 31% met the DSM-5 criteria for insomnia). The ISCI had a satisfactory Cronbach's alpha of 0.89 and test-retest reliability of 0.78. The CFA revealed that the ISCI exhibited a satisfactory model fit and was associated with the ISI-INA, IGAD-7, and IPHQ-9 (r = -0.81, -0.32, and -0.52, respectively; all P < .001). The ROC test revealed that the optimal cutoff point of ≤23 yielded the highest sensitivity (94%) and specificity (97%).
Conclusion: The study results revealed that the 8-item ISCI is a reliable and valid screening tool for detecting insomnia symptoms according to the DSM-5 criteria in the chronic period after stroke.
Keywords: Insomnia; Poststroke insomnia; Psychometric testing; SCI; Sleep condition indicator; Stroke.
© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.