Depression has been identified as the most prevalent mental disorder worldwide. Due to the stigma of mental illness, the population remains unidentified, undiagnosed, and untreated. Various studies have been carried out to detect and track depression following symptoms of dichotomous thinking, absolutist thinking, linguistic markers, and linguistic behavior. However, there is little study focused on the linguistic behavior of bilingual and multilingual with anxiety and depression. This chapter aims to identify the bi-multilingual linguistic markers by analyzing the recorded verbal content of depressive discourse resulting from life situations and stressors causing anxiety, depression, and suicidal ideation. Different contextual domains of word usage, content words, function words (pronouns), and negative valance words have been identified as indicators of psychological process affecting cognitive behavior, emotional health, and mental illness. These findings are discussed within the framework of Beck's model of depression to support the linguistic connection to mental illness-depression.
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The increasing levels of strain, anxiety and unending pressure of life events, adversities and constant life stress have been identified to be a source and trigger for depression (Fried et al., 2015; Mehl et al., 2017).The consistent source of stressors conjures depression particularly in interpersonal relationships demonstrating the bi-directional link between stress and depression(Hammen, 2015).According to WHO report (2017), depression is a common mental disorder that affects the people of all age group. The mental illness is considered a major cause of neural disability, neurodegenerator and most likely to incur suicide (Tarai et al.,2016). The onset of depression often goes undetected until it erupts into dysfunctional behavior, emotional disability, psychotic episode and even suicidality (Briggs et al., 2018; Stafford, 2018). The cause of depression could be biological, medical, social, situational, relational, or psychological. Most often mental illness remains untreated, undiagnosed and unidentified due to the stigma associated with mental health (Corrigan et al., 2014). A study by Beck and Alford (2009), has provided insights into understanding depression which assists both patients and their caregivers. Beck’s study (1979), has established an understanding of depression as a cognitive disorder, whereas depression according to Fossati (2018), is a disorder with both emotional and cognitive symptoms in which cognition is the key element responsible for functional and social outcomes. Both linguists and psychologists agree that language is an effective medium indicating the emotional, psychological states and behavioural changes (Pennebaker & Stone, 2003; Rude et al., 2004; Pennebaker et al., 2003; Chung & Pennebaker, 2007). Language also identifies personality traits and emotional changes which are echoed in not only in the verbal communication of an individual but also in online digital communication between individuals (Boyd & Pennebaker, 2017; De Chaudhary et al., 2013). The key to understanding oneself and others is understanding emotions. Study of language is the most apt mode to understand emotions as language represents emotions and emotions enhance the use of language (Dewaele, 2010; Argaman, 2010; Yule, 2016). The increasing accuracy of emotion detection in text and transcript analysis has paved the way for numerous uses ranging from utilization in the field of Artificial Intelligence (AI) to preventing suicide. As established, at every dimension and structure of language (the syntactic and semantic elements), there is an expression of emotion in the style and content (Jedud, 2018).