Validating Insomnia Severity Index (ISI) in a Bangladeshi Population: Using Classical Test Theory and Rasch Analysis

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.

Interpreting Action Research Arm Test Assessment Scores to Plan Treatment

Rasch keyforms can help interpret clinical assessment scores. The Action Research Arm Test (ARAT) is a commonly used assessment, yet no keyform currently exists. The aim is to provide a keyform for the ARAT and demonstrate how a clinician can use the keyform to design optimally challenging rehabilitation sessions. Secondary analysis of ARAT data ( n = 122) using confirmatory factor and Rasch analyses were used to examine the measurement properties and generate a keyform. The item standardized factor loadings were >0.40 (range = 0.82-0.96) and R2 values were >.60 (range = .65-.96). All items exhibited adequate infit statistics with point measure correlations >.60 (range = .72-.97). Person reliability was .98, and person separation was 7.07. Item-difficulty measures ranged from −2.78 logits to 2.64 logits. The ARAT has strong measurement properties, and a keyform was provided. We showed how the keyform can be utilized by clinicians to interpret scores, set goals, and plan treatment.