Psychometric properties of the 21-item Depression, Anxiety and Stress Scale (DASS-21) among Malaysians during COVID-19: a methodological study

In the last decade, mental health conditions have gained attention due to their increasing burden across the world. The 2019 Global Burden of Disease study estimates that depressive and anxiety disorders are two of the leading causes of disability globally (13th and 24th, respectively, among all causes of disability) (Vos et al., 2020). These conditions cost US$1 trillion annually across the global economy (WHO, 2016). Therefore, expanding mental health services, as well as diagnosing and treating these mental health conditions, is critical to improving global health and achieving international health goals.

In low- and middle-income countries, lack of sustainable care, stigma and low awareness of mental health disorders are the main factors contributing to their increased burden (Rathod et al., 2017; Wainberg et al., 2017) . Malaysia is a tropical country in Southeast Asia with more than 31 million residents according to 2018 estimates (WorldBank, 2018). Although the country has improved economically over the last 50 years, the number of mental health facilities and psychiatrists is insufficient (Parameshvara Deva, 2004). Similar to neighboring developing countries (Mia and Griffiths, 2021), the prevalence of mental health conditions in Malaysia is alarming and requires sustainable mental health solutions (IHME, 2017). One-fifth of primary care patients in Malaysia experience anxiety or depression (Deva, 2005), and depressive disorders are the 7th leading cause of death and disability in Malaysia (IHME, 2017). However, when considering Malaysia’s lack of resources and health professionals, the current estimate likely underrepresents the true burden of mental health problems among Malaysians.

Proper screening and diagnosis are essential for developing treatment plans and improving patient health outcomes. While clinical judgment is always warranted, a screening tool (eg, a rating scale) helps to get a quick indication of cross-sectional mental well-being and can be valuable in aiding diagnosis and treatment. Self-reported questionnaires and clinician-rated scales are common approaches to measuring mental health disorders. One such self-report questionnaire/scale is the 21-item Depression, Anxiety, and Stress Scale (ie, DASS-21), an abbreviated version of the DASS-41 designed to capture the constructs of depression, anxiety, and stress. The construction of the DASS-21 relied heavily on strong evidence of the reliability and validity of the scores obtained from the DASS-41 (Lovibond and Lovibond, 1995). The DASS-21 is one of the most widely used depression screening measures in addition to the Patient Health Questionnaire (9-item, 8-item, and 2-item versions), and has been used across cultures and populations (Peters et al., 2021). It not only covers the main symptoms of depression and anxiety, but has been proven to discriminate well between the subscales (Beaufort et al., 2017). Other studies have investigated psychometric properties in different environments and in different populations (Wardenaar et al., 2018; Yohannes et al., 2019; Lee and Kim, 2022). In the Malaysian population, some studies have explored the psychometric properties of the DASS-21 using Classic Test Theory (CTT) (Musa, et al., 2007; Ramli et al., 2009), but the DASS-21 scale and its depression , the anxiety and stress subscales are less explored through the use of modern test theory, specifically item response theory (IRT).

IRT, or latent response theory, employs mathematical models to measure a relationship between latent traits (eg, depression) and observed response outcomes (Hambleton et al., 1991). In CTT, the test (or in this case, the entire DASS-21) is the unit of analysis. In contrast, IRT considers items as the unit of analysis, and the measurement accuracy of an item depends on a respondent’s latent trait (known as “theta”, I🇧🇷 Unlike the CTT, the IRT is considered a strong assumption model, requiring tests of monotonicity, unidimensionality and local independence. When these assumptions are supported, IRT allows us to examine invariant item statistics (item information, item characteristics, conditional reliability) and ability estimates (discriminatory ability, location parameter, slope parameter, and general scale characteristics) (Embretson and Reise, 2000; Fan and Sun, 2013).

The DASS-21 comprises items from ordinal multiple response categories; therefore, it is essential to consider the ordinality and polytomic nature of the scale items. Among the different IRT models, we use the graded response model (GRM), the graded rating scale model (GRSM) and the generalized partial credit model (GPCM). GRM is one of the IRT families of mathematical models for ordinal responses (Samejima, 1997). The GRM is a generalization of the two-parameter logistic model (2PL), which estimates the probability of receiving a given score or higher, given the level of the underlying latent trait (Keller, 2005). The 2PL model is used for dichotomous response data, while the GRM for ordered polytomous categorized data. The GRM allows you to examine the likelihood that a participant will select a specific response category for each item; estimating latent or test subject trait (eg, levels of depression); to estimate how well the test questions measure that latent trait or ability. The GRSM is a modified version of the GRM that allows for a common limit for all items. It also works similarly to the GRM in terms of classical IRT parameterization, except that the graded ratings scale model applies to the slope intercept (Muraki, 1990). It assumes an equivalent spacing structure between items in the representation of Likert-type items. GPCM is also the same as GRM, but GPCM estimates separate response parameters for each category, while GRM assumes equivalence of response category threshold across items. In contrast to GRM, GPCM uses an adjacent categories approach where the probability of selecting a specific response category is not necessarily ordered; that is, for example, a response category for a higher level of depression may actually have a higher probability of selection.

Our aim is to use statistics estimated under the CTT paradigm and IRT models to explore the various latent traits of the overall DASS-21 scale and the properties of its subscales. The specific objectives of our study were to evaluate the DASS-21 subscales using IRT and to determine internal consistency, factor structure, discriminating characteristics, and item-level properties.

Psychometric properties of the 21-item Depression, Anxiety and Stress Scale (DASS-21) among Malaysians during COVID-19: a methodological study

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