Revisiting the Semantic Severity of Anxiety and Depression: Computational Linguistic Study of Normalization and Pathologization
Jazyk angličtina Země Kanada Médium electronic
Typ dokumentu časopisecké články
PubMed
40694505
PubMed Central
PMC12306585
DOI
10.2196/73950
PII: v27i1e73950
Knihovny.cz E-zdroje
- Klíčová slova
- anxiety, concept creep, depression, mental health discourse, normalization, pathologization, prevalence inflation, psychiatrization, semantic severity, trauma,
- MeSH
- deprese * psychologie MeSH
- lidé MeSH
- lingvistika * MeSH
- sémantika * MeSH
- stupeň závažnosti nemoci MeSH
- úzkost * psychologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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<.001), while anxiety (τ=0.08; P=.42) and trauma (τ=0.10; 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 nonsignificant. For specific mental disorder constructs (eg, schizophrenia), semantic severity decreased over time, whereas generic disorder terms (eg, 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.
Interdisciplinary School of Doctoral Studies University of Bucharest Bucharest Romania
Laboratory of Cognitive Clinical Sciences University of Bucharest Bucharest Romania
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Frances A. Saving Normal: An Insider’s Revolt Against Out-of-Control Psychiatric Diagnosis, DSM-5, Big Pharma, and the Medicalization of Ordinary Life. William Morrow & Co; 2013.
Cova F, Fernández D, Inostroza C. Increasing Mental Disorders or Social Psychiatrization: Excluding Options. Human Arenas Springer Science and Business Media B.V; 2023. pp. 1–15. doi. DOI
Batstra L, Thoutenhoofd ED. The risk that DSM-5 will further inflate the diagnostic bubble. Curr Psychiatry Rev. 2012;8(4):260–263. doi: 10.2174/157340012803520531. doi. DOI
Pierre JM. Overdiagnosis, Underdiagnosis, Synthesis: A Dialectic for Psychiatry and the DSM Making the DSM-5: Concepts and Controversies. Springer; 2013. pp. 105–124. doi. DOI
Beeker T, Mills C, Bhugra D, et al. Psychiatrization of society: a conceptual framework and call for transdisciplinary research. Front Psychiatry. 2021;12:645556. doi: 10.3389/fpsyt.2021.645556. doi. Medline. PubMed DOI PMC
Haslam N, Tse JSY, De Deyne S. Concept creep and psychiatrization. Front Sociol. 2021 Dec 16;6:806147. doi: 10.3389/fsoc.2021.806147. doi. PubMed DOI PMC
Foulkes L, Andrews JL. Are mental health awareness efforts contributing to the rise in reported mental health problems? A call to test the prevalence inflation hypothesis. New Ideas Psychol. 2023 Apr;69:101010. doi: 10.1016/j.newideapsych.2023.101010. doi. DOI
Bergström T. From treatment of mental disorders to the treatment of difficult life situations: a hypothesis and rationale. Med Hypotheses. 2023 Jul;176:111099. doi: 10.1016/j.mehy.2023.111099. doi. DOI
Batstra L, Frances A. Diagnostic inflation: causes and a suggested cure. J Nerv Ment Dis. 2012 Jun;200(6):474–479. doi: 10.1097/NMD.0b013e318257c4a2. doi. Medline. PubMed DOI
Haslam N. Concept creep: psychology’s expanding concepts of harm and pathology. Psychol Inq. 2016 Jan 2;27(1):1–17. doi: 10.1080/1047840X.2016.1082418. doi. DOI
Haslam N, Dakin BC, Fabiano F, et al. Harm inflation: making sense of concept creep. Eur Rev Soc Psychol. 2020 Jan 1;31(1):254–286. doi: 10.1080/10463283.2020.1796080. doi. DOI
Haslam N, McGrath MJ. The creeping concept of trauma. Soc Res (New York) 2020 Sep;87(3):509–531. doi: 10.1353/sor.2020.0052. doi. DOI
Vylomova E, Murphy S, Haslam N. Evaluation of semantic change of harm-related concepts in psychology. Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change; Aug 2, 2019; Florence, Italy. [18-07-2024]. Presented at. URL. Accessed. doi. DOI
Xiao Y, Baes N, Vylomova E, Haslam N. Have the concepts of “anxiety” and “depression” been normalized or pathologized? A corpus study of historical semantic change. PLoS ONE. 2023;18(6):e0288027. doi: 10.1371/journal.pone.0288027. doi. Medline. PubMed DOI PMC
Vylomova E, Haslam N. In: Semantic Changes in Harm-Related Concepts in English. Tahmasebi N, Borin L, editors. Language Science Press; 2021. pp. 93–122.
Berger J, Packard G. Using natural language processing to understand people and culture. Am Psychol. 2022;77(4):525–537. doi: 10.1037/amp0000882. doi. Medline. PubMed DOI
Garg N, Schiebinger L, Jurafsky D, Zou J. Word embeddings quantify 100 years of gender and ethnic stereotypes. Proc Natl Acad Sci U S A. 2018 Apr 17;115(16):E3635–E3644. doi: 10.1073/pnas.1720347115. doi. Medline. PubMed DOI PMC
Kozlowski AC, Taddy M, Evans JA. The geometry of culture: analyzing the meanings of class through word embeddings. Am Sociol Rev. 2019 Oct;84(5):905–949. doi: 10.1177/0003122419877135. doi. DOI
Mendelsohn J, Tsvetkov Y, Jurafsky D. A framework for the computational linguistic analysis of dehumanization. Front Artif Intell. 2020 Aug 7;3:540127. doi: 10.3389/FRAI.2020.00055/BIBTEX. doi. PubMed DOI PMC
Baes N, Vylomova E, Zyphur M, Haslam N. The semantic inflation of “trauma” in psychology. Psychol Lang Commun. 2023 Feb 20;27(1):23–45. doi: 10.58734/plc-2023-0002. doi. DOI
Lane C. Shyness: How Normal Behavior Became a Sickness. Yale University Press; 2008.
Horwitz A, Wakefield J. The Loss of Sadness: How Psychiatry Transformed Normal Sorrow into Depressive Disorder. Oxford University Press; 2007. doi. PubMed DOI
Bonanno GA. The Other Side of Sadness: What the New Science of Bereavement Tells Us About Life After Loss. Basic Books; 2009.
Pisl V. Psychiatrization in Czech lexical data: everyday adjectives are acquiring clinical connotations. New Ideas Psychol. 2025 Aug;78:101148. doi: 10.1016/j.newideapsych.2025.101148. doi. DOI
Keenan HL, Baes N. New York Times Article Corpus (1930-2023) GitHub. 2023. [18-06-2025]. https://github.com/naomibaes/NYT URL. Accessed.
Warriner AB, Kuperman V, Brysbaert M. Norms of valence, arousal, and dominance for 13,915 English lemmas. Behav Res. 2013 Dec;45(4):1191–1207. doi: 10.3758/s13428-012-0314-x. doi. PubMed DOI
Wijffels J, Watanabe K, Fomichev M. word2vec: Distributed Representations of Words. 2023. [18-06-2025]. https://cran.r-project.org/web/packages/word2vec URL. Accessed.
The Merriam-Webster Thesaurus. 2024. [30-11-2024]. https://www.merriam-webster.com/thesaurus URL. Accessed.
OSF storage. Open Science Framework. [15-07-2025]. https://osf.io/zhgce/files/osfstorage URL. Accessed.
Brinkmann S. Languages of suffering. Theory Psychol. 2014 Oct;24(5):630–648. doi: 10.1177/0959354314531523. doi. DOI
Fabiano F, Haslam N. Diagnostic inflation in the DSM: a meta-analysis of changes in the stringency of psychiatric diagnosis from DSM-III to DSM-5. Clin Psychol Rev. 2020 Aug;80:101889. doi: 10.1016/j.cpr.2020.101889. doi. PubMed DOI
Hacking I. Kinds of people: moving targets. Proc Br Acad. 2007;151:285–318. doi: 10.5871/bacad/9780197264249.003.0010. doi. DOI
Malla A, Gold I. Public discourse on mental health: a critical view. J Psychiatry Neurosci. 2024;49(2):E126–E131. doi: 10.1503/jpn.230161. doi. Medline. PubMed DOI PMC
Murphy G. The Big Book of Concepts. The MIT Press; 2002.
Margolis E, Laurence S. Concepts. The Stanford Encyclopedia of Philosophy; 2023.
Batstra L, van Roy ACM, Thoutenhoofd ED. Teachers with special needs. De-psychiatrization of children in schools. Front Sociol. 2021 Dec 8;6:781057. doi: 10.3389/fsoc.2021.781057. doi. PubMed DOI PMC
Baes N, Haslam N, Vylomova E. Semantic shifts in mental health-related concepts. Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change; Dec 6, 2023; Singapore. pp. 119–128. Presented at. doi. DOI
Dubossarsky H, Tsvetkov Y, Dyer C, Grossman E. A bottom up approach to category mapping and meaning change. In: Pirrelli V, Marzi C, Ferro M, editors. Word Structure and Word Usage Proceedings of the NetWordS Final Conference; Mar 30 to Apr 1, 2015; Pisa. In. Presented at.
Dubossarsky H, Weinshall D, Grossman E. Outta control: laws of semantic change and inherent biases in word representation models. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing; Sep 7-11, 2017; Copenhagen, Denmark. pp. 1136–1145. Presented at. doi. DOI
Kutuzov A, Øvrelid L, Szymanski T, Velldal E. Diachronic word embeddings and semantic shifts: a survey. Proceedings of the 27th International Conference on Computational Linguistics; Aug 20-26, 2018; Santa Fe, New Mexico, United States. 2018. [07-09-2025]. pp. 1384–1397. Presented at. URL. Accessed.
Baes N. New York Times Article Corpus. GitHub. [08-07-2025]. https://github.com/naomibaes/NYT URL. Accessed.