Abstract
BACKGROUND: Binary categorical approaches to diagnosing depression have been widely criticized due to clinical limitations and potential negative consequences. In place of such categorical models of depression, a 'staged model' has recently been proposed to classify populations into four tiers according to severity of symptoms: 'Wellness;' 'Distress;' 'Disorder;' and 'Refractory.' However, empirical approaches to deriving this model are limited, especially with populations in low- and middle-income countries. METHODS: A mixed-methods study using latent class analysis (LCA) was conducted to empirically test non-binary models to determine the application of LCA to derive the 'staged model' of depression. The study population was 18 to 29-year-old men (n = 824) from an urban slum of Bangladesh, a low resource country in South Asia. Subsequently, qualitative interviews (n = 60) were conducted with members of each latent class to understand experiential differences among class members. RESULTS: The LCA derived 3 latent classes: (1) Severely distressed (n = 211), (2) Distressed (n = 329), and (3) Wellness (n = 284). Across the classes, some symptoms followed a continuum of severity: 'levels of strain', 'difficulty making decisions', and 'inability to overcome difficulties.' However, more severe symptoms such as 'anhedonia', 'concentration issues', and 'inability to face problems' only emerged in the severely distressed class. Qualitatively, groups were distinguished by severity of tension, a local idiom of distress. CONCLUSIONS: The results indicate that LCA can be a useful empirical tool to inform the 'staged model' of depression. In the findings, a subset of distress symptoms was continuously distributed, but other acute symptoms were only present in the class with the highest distress severity. This suggests a distress-continuum, disorder-threshold model of depression, wherein a constellation of impairing symptoms emerge together after exceeding a high level of distress, i.e., a tipping point of tension heralds a host of depression symptoms.