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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 14, 2025
Date Accepted: May 23, 2025

The final, peer-reviewed published version of this preprint can be found here:

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

Pisl V, Bucur AM, Podina IR

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

J Med Internet Res 2025;27:e73950

DOI: 10.2196/73950

PMID: 40694505

PMCID: 12306585

From Normalization to Pathologization: Revisiting the Semantic Severity of Anxiety and Depression

  • Vojtech Pisl; 
  • Ana-Maria Bucur; 
  • Ioana R. Podina

ABSTRACT

Background:

Psychiatrization may contribute to the deterioration of public mental health observed in recent decades. Cultural shifts driving this process can be examined through the concept creep 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 these findings 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 analysed 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 (e.g., sad, 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 = .35; p < .001), while anxiety (τ = .08; p = .42) and trauma (τ = .10; p = .33) showed no significant change. However, when controlling for context, severity was consistently higher in mental health-related contexts, and the effect of time became non-significant. For specific mental disorder constructs (e.g., schizophrenia), semantic severity decreased over time, whereas generic disorder terms (e.g., mental illness) remained stable. Lay emotional constructs became increasingly associated with mental health discourse but showed no clear severity trend.

Conclusions:

The increasing semantic severity of depression appears to be driven by its growing presence in mental health discourse, rather than an inherent shift in meaning. The declining severity of specific, but not generic disorder constructs suggests that the overall representation of mental disorders remains severe, despite its expansion to less serious experiences. Meanwhile, ordinary emotions such as sadness and fear are increasingly discussed in mental health contexts. These trends highlight the evolving cultural framing of mental health and suggest that psychiatrization is shaping public perceptions of emotional experiences.


 Citation

Please cite as:

Pisl V, Bucur AM, Podina IR

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

J Med Internet Res 2025;27:e73950

DOI: 10.2196/73950

PMID: 40694505

PMCID: 12306585

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