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Validating Insomnia Severity Index (ISI) in a Bangladeshi Population : Using Classical Test Theory and Rasch Analysis
- Publication Year :
- 2022
-
Abstract
- The COVID-19 outbreak is associated with sleep problems and mental health issues among individuals. Therefore, there is a need to assess sleep efficiency during this tough period. Unfortunately, the commonly used instrument on insomnia severity-the Insomnia Severity Index (ISI)-has never been translated and validated among Bangladeshis. Additionally, the ISI has never been validated during a major protracted disaster (such as the COVID-19 outbreak) when individuals encounter mental health problems. The present study aimed to translate the ISI into Bangla language (ISI-Bangla) and validate its psychometric properties. First, the linguistic validity of the ISI-Bangla was established. Then, 9790 Bangladeshis (mean age = 26.7 years; SD = 8.5; 5489 [56.1%] males) completed the Bangla versions of the following questionnaires: ISI, Fear of COVID-19 Scale (FCV-19S), and Patient Health Questionnaire-9 (PHQ-9). All the participants also answered an item on suicidal ideation. Classical test theory and Rasch analyses were conducted to evaluate the psychometric properties of the ISI-Bangla. Both classical test theory and Rasch analyses support a one-factor structure for the ISI-Bangla. Moreover, no substantial differential item functioning was observed across different subgroups (gender, depression status (determined using PHQ-9), and suicidal ideation). Additionally, concurrent validity of the ISI-Bangla was supported by significant and moderate correlations with FCV-19S and PHQ-9; known-group validity was established by the significant difference of the ISI-Bangla scores between participants who experienced suicidal ideation and those without. The present psychometric validation conducted during the COVID-19 outbreak suggests that the ISI-Bangla is a promising and operationally adequate instrument to assess insomnia in Bangladeshis.
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1312817174
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.3390.ijerph19010225