Revisiting the Semantic Severity of Anxiety and Depression: Computational Linguistic Study of Normalization and Pathologization

Abstract

Background: Psychiatrization may contribute to the deterioration of public mental health observed in recent decades. The cultural aspects of psychiatrization can be understood as a form of concept creep (progressive expansion) of mental health terminology. Over time, concepts of psychopathology have expanded to encompass a broader range of human experiences, potentially diluting their meaning. Accordingly, previous research has shown a gradual decline in the semantic severity of the word trauma. However, the semantic severity of anxiety and depression has been increasing over time. Objective: This study aims to replicate and explain the increases in semantic severity of anxiety and depression by distinguishing between disorder constructs (clinical terms) and lay emotional constructs (everyday emotional terms) and assessing how their semantic severity changes over time. Additionally, we investigate whether mental health discourse and the broader context in which these terms appear influence these changes. Methods: We analyzed the semantic severity of anxiety, depression, and trauma using leading paragraphs from 4.7 million New York Times articles (1970-2023). We extended this analysis to broader disorder constructs (both generic terms, such as mental illness, and specific terms, such as schizophrenia) and lay emotional constructs (eg, sad and worried). A word2vec model was used to estimate the degree to which these terms appeared in mental health–related contexts, and a Mental Health Index was developed to quantify shifts in discourse. Regression analyses were conducted to assess whether changes in semantic severity were influenced by time and context. Results: The semantic severity of depression increased significantly (τ=0.35; P