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Does emotion predict the course of major depressive disorder? A review of prospective studies
Abstract
Purpose. Emotional dysfunction is a hallmark of major depressive disorder (MDD). There has been wide interest in identifying the nature and significance of emotional deficits in MDD. Given the paramount goal of identifying etiological markers of MDD that can sharpen prevention and treatment efforts, researchers have pursued emotion as a functionally significant factor and predictor of clinical course in MDD. This review is the first to summarize the literature examining emotion as a predictor of the clinical course of MDD. Method. We conducted a systematic review of all published studies reporting on the prospective relationship between positive and negative emotionality (PE and NE) – measured at the state or trait level – and the longitudinal course of MDD in diagnosed adults. Physiological, behavioural, and subjective indices of emotion were considered. The primary analyses encompassed 28 research reports that included data from 3,798 participants and tested a total of 60 hypotheses. Results. Lower levels of PE predicted poorer MDD course with some consistency. Paradoxically, both lower levels of state NE and higher levels of trait NE predicted poorer MDD course. The relationships between emotionality and MDD course generally held even after initial depression symptom severity was taken into account. Conclusion. Emotion shows promise as a predictor of MDD course. Implications of these data for current theories of emotion and MDD, the apparently divergent relation between state and trait NE and course, and future directions to further clarify the functional significance of emotion in the context of MDD are discussed.
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“Importantly, these alterations in reward processing precede and potentially contribute to the etiology of depression in at-risk groups (Gotlib et al., 2010), and number of prospective studies have shown that self-reported anhedonia (less frequent and intense positive affect) is a strong predictor of subsequent increases in depression severity (Morris et al., 2009).”
From The role of inflammation in core features of depression: Insights from paradigms using exogenously-induced inflammation. (2018) · cites this paper as Morris et al., 2009
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Metadata
- Authors
- Morris, B. H., Bylsma, L. M., & Rottenberg, J.
- Affiliations
- University of South Florida (US)
- Corresponding author
- Rottenberg, Jonathan
- Venue
- British Journal of Clinical Psychology
- Publisher
- Wiley
- Published
- 2009-09
- Volume
- 48
- Issue
- 3
- Pages
- 255-273
- ISSN
- 0144-6657 (ISSN-L)
- 2044-8260
- OpenAlex
- W1980099020
- Cited by
- 134
- References
- 105
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 6 · 2023: 14 · 2022: 23 · 2021: 9 · 2020: 7 · 2019: 6 · 2018: 7 · 2017: 5 · 2016: 5 · 2015: 11 · 2014: 2 · 2013: 4 · 2012: 9
- FWCI
- 0.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Clinical Psychology (publishedVersion)
- PubMed (publishedVersion)
- Digital Commons - University of South Florida (University of South Florida) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- major depressive disorder, clinical course, positive affectivity, negative affectivity, emotional dysfunction
- MeSH terms
- Adult, Affective Symptoms, Depression, Major Depressive Disorder, Emotions, Humans, Longitudinal Studies, Patient Acceptance of Health Care, Personality Assessment, Prognosis, Prospective Studies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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