From the way we move and sleep to the way we relate to the people around us, depression changes almost everything. It is also noticeable in the way you speak and in your writing. In some cases, this “word of melancholy” can have a strong effect on others. Consider the influence of the poems and lyrics of Sylvia Plath and Kurt Cobain, who suffered from depression and committed suicide.
Scientists have long tried to pinpoint the exact link between depression and language, but technology is bringing us closer to the big picture. Our new research clinical psychologyhas published a class of words that can help accurately predict if someone is suffering from depression.
Traditionally, linguistic analysis in this area has been done by researchers reading and taking notes. Computer-assisted text analysis techniques can now process very large databanks in minutes. It helps identify linguistic features that humans may miss, calculating word and word class prevalence, lexical diversity, average sentence length, grammatical patterns, and many other metrics.
So far, personal essays and diaries by people with depression have been helpful, as are works by famous artists such as Cobain and Plath. For spoken language, we also gained insights from snippets of natural language from depressed patients. Taken together, these studies reveal clear and consistent differences in the language of people with and without symptoms of depression.
Language can be divided into two components: content and style. Content relates to what we express, the meaning or subject of a statement. If someone with symptoms of depression finds out that they overuse words that convey negative emotions, especially negative adjectives and adverbs such as “lonely,” “sad,” and “miserable,” no one can help. No one should be surprised.
More interesting is the use of pronouns. People with symptoms of depression use significantly more first-person singular pronouns such as “I,” “I,” and “I,” and second- and third-person pronouns such as “they,” “they,” and “they.” reduce significantly. “She.” This pronoun usage pattern suggests that people with depression are more focused on themselves and less connected to others. Researchers reported that pronouns were actually more reliable than negative emotional words when identifying depression.
We know that rumination (brooding over personal problems) and social isolation are common features of depression. However, we do not know whether these findings reflect differences in attentiveness or thinking styles. Does depression cause us to focus on ourselves, or do people who focus too much on themselves develop symptoms of depression?
The style of a language is about how you express yourself, not what you express. Our lab recently conducted a big data text analysis of 64 different online mental health forums, surveying over 6,400 members. “Absolutist words” that convey absolute magnitudes or probabilities, such as “always,” “never,” or “completely,” are better markers in mental health forums than pronouns or words of negative emotion. turned out to be.
From the beginning, we predicted that depressed patients have a more black-and-white view of the world, and that would show in their language style. When compared to 19 different control forums (such as Mumsnet and StudentRoom), the prevalence of absolutist language is about 50 percent higher in the anxiety and depression forums and about 80 percent higher in the suicidal ideation forums.
Pronouns generated similar distribution patterns as absolutist words across forums, but with a smaller impact. In contrast, paradoxically, negative emotion language was less prevalent in suicidal ideation forums than in anxiety and depression forums.
Our research also includes recovery forums where members who feel recovered from depressive episodes write positive and encouraging posts about their recovery. Here we see that while negative sentiment words are used to moderate the forum at similar levels, positive sentiment words increase by about 70%. Nevertheless, the prevalence of absolutist language was significantly higher than in the control group, but slightly lower than in the anxiety and depression forums.
Importantly, people who have experienced symptoms of depression before are more likely to experience symptoms of depression again. Thus, even in the absence of current symptoms of depression, a strong propensity for absolutist thinking may play a role in triggering depressive episodes. The same effect is seen with the use of pronouns, but not with negative sentiment words.
Understanding the language of depression helps us understand the mindset of someone with symptoms of depression, but it also has practical implications. Researchers combine automated text analysis with machine learning (computers that can learn from experience without being programmed) to classify different mental health conditions from samples of natural language text, such as blog posts.
Such classification surpasses that of already trained therapists. Importantly, machine learning classification only gets better as more data is provided and more sophisticated algorithms are developed. This is not only considering the broad patterns of absolutism, negativity and pronouns already described. Efforts are underway to use computers to pinpoint more specific subcategories of mental health problems, such as perfectionism, self-esteem issues, and social anxiety.
That said, it is certainly possible to use depression-related language without actually being depressed. Ultimately, it’s how you feel over time that determines whether or not you suffer. However, the World Health Organization now estimates that more than 300 million people worldwide are living with depression, an increase of more than 18% since 2005, and the number of drugs used to detect depression is increasing. Having more tools available is certainly critical to improving health and preventing tragic suicides such as: Plath and Cobain stuff.
This article was originally published in The Conversation by Mohammed Al-Mosaiwi of the University of Reading. Read the original article here.
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