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Prospective predictors of care partner burden and depression in Parkinson's disease.

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Title: Prospective predictors of care partner burden and depression in Parkinson's disease.
Authors: Whiteley, Nicole (AUTHOR), Pluim, Celina F. (AUTHOR), Split, Molly (AUTHOR), Cabrera Tuazon, Angelie (AUTHOR), Moore, Raeanne C. (AUTHOR), Irene Litvan (AUTHOR), Lessig, Stephanie (AUTHOR), Filoteo, J. Vincent (AUTHOR), Schiehser, Dawn M. (AUTHOR)
Source: International Journal of Geriatric Psychiatry. Sep2022, Vol. 37 Issue 9, p1-10. 10p.
Abstract: Objectives: Care partners who provide informal care to individuals with Parkinson's disease (PD) report higher levels of burden and depression; however, longitudinal research on these symptoms is scarce. The current study assessed changes in care partner burden and depression, and patient and care partner predictors of these symptoms over time. Such knowledge may provide important information for assessment and treatment of depression and burden in care partners of individuals with PD.Research Design and Methods: Participants were 88 PD patients without dementia and their self-identified care partner (n = 88). Care partners completed the Geriatric Depression Scale and Zarit Burden Interview. PD participants completed mood questionnaires and a motor exam at baseline and 2 year follow-up. Relationships among care partner burden and depression over time with patient and care partner predictors (i.e., demographic, mood, and disease characteristics) were assessed using correlations and regression analyses.Results: Care partner burden and depression significantly increased over an approximate 2 year period. Greater baseline disease severity predicted worsening of care partner burden (p = 0.028), while baseline patient depression predicted worsening of care partner depression (p = 0.002).Conclusions: Results highlight differential impacts of specific PD symptoms on worsening care partner burden compared to depression; increased PD disease severity predicts increased burden, while patient mood predicts worsening of depression over time. Targeting PD disease severity and mood symptoms may prevent the progression of care partner burden and depression. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Geriatric Psychiatry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Prospective predictors of care partner burden and depression in Parkinson's disease.
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  Data: <searchLink fieldCode="AR" term="%22Whiteley%2C+Nicole%22">Whiteley, Nicole</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pluim%2C+Celina+F%2E%22">Pluim, Celina F.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Split%2C+Molly%22">Split, Molly</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cabrera+Tuazon%2C+Angelie%22">Cabrera Tuazon, Angelie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Moore%2C+Raeanne+C%2E%22">Moore, Raeanne C.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Irene+Litvan%22">Irene Litvan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lessig%2C+Stephanie%22">Lessig, Stephanie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Filoteo%2C+J%2E+Vincent%22">Filoteo, J. Vincent</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schiehser%2C+Dawn+M%2E%22">Schiehser, Dawn M.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geriatric+Psychiatry%22">International Journal of Geriatric Psychiatry</searchLink>. Sep2022, Vol. 37 Issue 9, p1-10. 10p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: <bold>Objectives: </bold>Care partners who provide informal care to individuals with Parkinson's disease (PD) report higher levels of burden and depression; however, longitudinal research on these symptoms is scarce. The current study assessed changes in care partner burden and depression, and patient and care partner predictors of these symptoms over time. Such knowledge may provide important information for assessment and treatment of depression and burden in care partners of individuals with PD.<bold>Research Design and Methods: </bold>Participants were 88 PD patients without dementia and their self-identified care partner (n = 88). Care partners completed the Geriatric Depression Scale and Zarit Burden Interview. PD participants completed mood questionnaires and a motor exam at baseline and 2 year follow-up. Relationships among care partner burden and depression over time with patient and care partner predictors (i.e., demographic, mood, and disease characteristics) were assessed using correlations and regression analyses.<bold>Results: </bold>Care partner burden and depression significantly increased over an approximate 2 year period. Greater baseline disease severity predicted worsening of care partner burden (p = 0.028), while baseline patient depression predicted worsening of care partner depression (p = 0.002).<bold>Conclusions: </bold>Results highlight differential impacts of specific PD symptoms on worsening care partner burden compared to depression; increased PD disease severity predicts increased burden, while patient mood predicts worsening of depression over time. Targeting PD disease severity and mood symptoms may prevent the progression of care partner burden and depression. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Geriatric Psychiatry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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