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Epidemiology and treatment of depression in patients with chronic medical illness
Open accessAbstract
There is a bidirectional relationship between depression and chronic medical disorders. The adverse health risk behaviors and psychobiological changes associated with depression increase the risk for chronic medical disorders, and biological changes and complications associated with chronic medical disorders may precipitate depressive episodes. Comorbid depression is associated with increased medical symptom burden, functional impairment, medical costs, poor adherence to self-care regimens, and increased risk of morbidity and mortality in patients with chronic medical disorders. Depression may worsen the course of medical disorders because of its effect on proinflammatory factors, hypothalamic-pituitary axis, autonomic nervous system, and metabolic factors, in addition to being associated with a higher risk of obesity, sedentary lifestyle, smoking, and poor adherence to medical regimens. Both evidence-based psychotherapies and antidepressant medication are efficacious treatments for depression. Collaborative depression care has been shown to be an effective way to deliver these treatments to large primary care populations with depression and chronic medical illness.
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“are associated with greater disability, barriers to treatment, and poorer self-management of disease or disability (Katon, 2011).”
From Attachment insecurity predicts outcomes in an ACT-CBT group therapy for adults in a physical rehabilitation centre (2022) · cites this paper as Katon, 2011
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“Depressed individuals may be at risk for functional decline due to poor self-care, including poor nutritional intake and disengagement from daily activities. (Katon 2011)”
From Successful aging: Advancing the science of physical independence in older adults (2015) · cites this paper as Katon 2011
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“sterile inflammatory diseases such as these also have a high comorbidity with MDDs (Katon, 2011).”
From Danger Signals and Inflammasomes: Stress-Evoked Sterile Inflammation in Mood Disorders (2017) · cites this paper as Katon, 2011
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Metadata
- Authors
- J. Katon, W.
- Affiliations
- Professor and Vice-Chair, Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington, USA
- Venue
- Dialogues in Clinical Neuroscience
- Publisher
- Informa UK Limited
- Published
- 2011-03-31
- Volume
- 13
- Issue
- 1
- Pages
- 7-23
- ISSN
- 1294-8322 (ISSN-L)
- 1958-5969
- PMC
- PMC3181964
- OpenAlex
- W2121530613
- Cited by
- 820
- References
- 146
- Citations by year
- 2026: 38 · 2025: 60 · 2024: 58 · 2023: 63 · 2022: 72 · 2021: 75 · 2020: 57 · 2019: 62 · 2018: 55 · 2017: 64 · 2016: 56 · 2015: 43 · 2014: 46 · 2013: 35 · 2012: 26
- FWCI
- 26.71
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Dialogues in Clinical Neuroscience (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (K08MH069741, K-24 MH069741)
- Topics
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- depression, chronic disease, comorbidities, bidirectional relationship, inflammation, hypothalamic-pituitary axis, autonomic nervous system, obesity, smoking, medication adherence, psychotherapy, antidepressants, collaborative care, primary care, functional disability, health care costs
- MeSH terms
- Chronic Disease, Depression, Diabetes Mellitus, Heart Diseases, Humans, Models, Biological, Physician-Patient Relations, Risk Factors, Self Care, Comorbidity
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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.
Statistics and arithmetic are recomputed, not judged.
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