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The 52 symptoms of major depression: Lack of content overlap among seven common depression scales
Abstract
Background Depression severity is assessed in numerous research disciplines, ranging from the social sciences to genetics, and used as a dependent variable, predictor, covariate, or to enroll participants. The routine practice is to assess depression severity with one particular depression scale, and draw conclusions about depression in general, relying on the assumption that scales are interchangeable measures of depression. The present paper investigates to which degree 7 common depression scales differ in their item content and generalizability.Methods A content analysis is carried out to determine symptom overlap among the 7 scales via the Jaccard index (0=no overlap, 1=full overlap). Per scale, rates of idiosyncratic symptoms, and rates of specific vs. compound symptoms, are computed.Results The 7 instruments encompass 52 disparate symptoms. Mean overlap among all scales is low (0.36), mean overlap of each scale with all others ranges from 0.27 to 0.40, overlap among individual scales from 0.26 to 0.61. Symptoms feature across a mean of 3 scales, 40% of the symptoms appear in only a single scale, 12% across all instruments. Scales differ regarding their rates of idiosyncratic symptoms (0-33%) and compound symptoms (22-90%).Limitations Future studies analyzing more and different scales will be required to obtain a better estimate of the number of depression symptoms; the present content analysis was carried out conservatively and likely underestimates heterogeneity across the 7 scales.Conclusion The substantial heterogeneity of the depressive syndrome and low overlap among scales may lead to research results idiosyncratic to particular scales used, posing a threat to the replicability and generalizability of depression research. Implications and future research opportunities are discussed.
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“Despite its medical importance MDD is poorly defined and diagnosed since its diagnosis is mostly based on data subjectively reported by the patients themselves (13–15) and lack of objective, clinically relevant outcome measure.”
From A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms (2023) · cites this paper as [14]
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Metadata
- Authors
- Fried, E. I.
- Affiliations
- University of Amsterdam (NL)
- Corresponding author
- Fried, Eiko I.
- ORCID
- Fried, Eiko I.
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 208
- Pages
- 191-197
- ISSN
- 0165-0327 (ISSN-L)
- OpenAlex
- W2537247270
- Cited by
- 649
- References
- 42
- Citations by year
- 2026: 73 · 2025: 77 · 2024: 93 · 2023: 75 · 2022: 87 · 2021: 84 · 2020: 78 · 2019: 46 · 2018: 22 · 2017: 12
- FWCI
- 37.96
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-01-01)
- Open access
- closed
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- major depressive disorder, depressive symptoms, depression rating scales, symptom overlap, scale heterogeneity, measurement invariance, replicability, generalizability, Jaccard similarity
- MeSH terms
- Depressive Disorder, Major, Major Depressive Disorder, Humans, Psychiatric Status Rating Scales, Reproducibility of Results
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