Comparing the Symptomatology of Post-stroke Depression with Depression in the General Population: A Systematic Review
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Published:2023-09-05
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Volume:
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ISSN:1040-7308
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Container-title:Neuropsychology Review
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language:en
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Short-container-title:Neuropsychol Rev
Author:
Blake J. J.ORCID, Gracey F., Whitmore S., Broomfield N. M.
Abstract
AbstractPrevious research into the phenomenological differences of post-stroke depression (PSD) has typically focused on comparisons of symptom profiles between stroke and non-stroke population controls. This systematic review aimed to synthesize these findings with results from other methodological approaches that contribute to an understanding of phenomenological differences. Articles were identified via a systematic search of seven databases and additional manual searching. A narrative synthesis approach was adopted because of the high methodological heterogeneity. Twelve articles comparing the symptomatology of depression between stroke and non-stroke controls were included. Three distinct methodological approaches, relevant to the aim, were identified: comparisons of profiles among groups with similar overall depression severity, comparisons of the strengths of correlations between a symptom and depression, and comparisons of latent symptom severity. The symptomatology of depression was generally similar between the groups, including somatic symptoms, despite the hypothesized interference of comorbid physical stroke effects. Despite high heterogeneity, there was a tentative indication that post-stroke depression manifests with comparatively less severe/prevalent anhedonia. Possible mechanisms for the observed similarities and differences are explored, including suggestions for future research.
Publisher
Springer Science and Business Media LLC
Subject
Neuropsychology and Physiological Psychology
Reference86 articles.
1. Acciarresi, M., Bogousslavsky, J., & Paciaroni, M. (2014). Post-stroke fatigue: Epidemiology, clinical characteristics and treatment. European Neurology, 72(5–6), 255–261. https://doi.org/10.1159/000363763 2. Adams, K. B., Matto, H. C., & Sanders, S. (2004). Confirmatory factor analysis of the geriatric depression scale. The Gerontologist, 44(6), 818–826. https://doi.org/10.1093/geront/44.6.818 3. Aizenstein, H. J., Baskys, A., Boldrini, M., Butters, M. A., Diniz, B. S., Jaiswal, M. K., Jellinger, K. A., Kruglov, L. S., Meshandin, I. A., Mijajlovic, M. D., Niklewski, G., Pospos, S., Raju, K., Richter, K., Steffens, D. C., Taylor, W. D., & Tene, O. (2016). Vascular depression consensus report – A critical update. BMC Medicine, 14(1), 1–16. https://doi.org/10.1186/S12916-016-0720-5 4. Aizenstein, H. J., Khalaf, A., Walker, S. E., & Andreescu, C. (2014). Magnetic resonance imaging predictors of treatment response in late-life depression. Journal of Geriatric Psychiatry and Neurology, 27(1), 24–32. https://doi.org/10.1177/0891988713516541 5. Alexopoulos, G. S., Meyers, B. S., Young, R. C., Campbell, S., Silbersweig, D., & Charlson, M. (1997). “Vascular depression” hypothesis. In Archives of General Psychiatry, 54(10), 915–922. https://doi.org/10.1001/archpsyc.1997.01830220033006
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