A multiplicity of approaches to characterize geriatric depression and its outcomes
PURPOSE OF REVIEWResearch in geriatric depression has always had a multidisciplinary bent, particularly in methods used to characterize depression. Understanding diagnosis, psychiatric comorbidities, and course continues to be a goal of clinical researchers. Those interested in cognitive neuroscienc...
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Veröffentlicht in: | Current opinion in psychiatry 2009-11, Vol.22 (6), p.522-526 |
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Sprache: | eng |
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Zusammenfassung: | PURPOSE OF REVIEWResearch in geriatric depression has always had a multidisciplinary bent, particularly in methods used to characterize depression. Understanding diagnosis, psychiatric comorbidities, and course continues to be a goal of clinical researchers. Those interested in cognitive neuroscience and basic neuroscience have more recently trained their sights on late-life depression. This review identifies recent progress in the characterization of geriatric depression using a variety of methodologies.
RECENT FINDINGSDepression in the elderly remains underdetected and underdiagnosed, particularly in nonmental health settings. Studies of the impact of psychiatric comorbidities and of the negative outcomes of depression in older adults demonstrate that geriatric depression is a serious medical condition that not only affects mood but can also lead to functional and cognitive decline. Advances in neuroimaging technology have demonstrated structural and functional changes in the brains of older depressed patients. With the advent of brain banks in neuropsychiatry, we are now seeing postmortem neuroanatomical studies that seek to extend findings from clinical practice and from neuroimaging research.
SUMMARYClinicians should become more aware of advances in detection of depression, the effect of psychiatric comorbidities, the poor mood and cognitive outcomes associated with late-life depression and should keep abreast of recent neuroimaging and neuroanatomical findings. |
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ISSN: | 0951-7367 1473-6578 |
DOI: | 10.1097/YCO.0b013e32832fcd93 |