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Demographic and clinical predictors of trait impulsivity in Parkinson’s disease patients
Journal article   Open access   Peer reviewed

Demographic and clinical predictors of trait impulsivity in Parkinson’s disease patients

M. Riley, M. Bakeberg, M. Byrnes, A. Jefferson, S. Ghosh, R. Stell, F.L. Mastaglia, D. Hince and R.S. Anderton
Parkinson's Disease, Vol.2018, pp.1-7
2018
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Abstract

Background. Impulsive behaviour has become increasingly recognised as a neuropsychiatric complication of Parkinson’s disease (PD). Thought to be a product of compromised cognitive control, the spectrum of impulsive behaviours in PD ranges from cognitive disinhibition to impulse control disorders (ICDs). Objective. At present, there are no indicators for trait impulsivity in PD. The objective of the current study was to identify demographic and clinical predictors of susceptibility to trait impulsivity in a cohort of PD patients. Methods. The current study assessed impulsivity using the Barratt Impulsiveness Scale 11 (BIS-11) in a cohort of 87 PD patients. General linear models (GLMs) were used to identify clinical and demographic variables predictive of heightened BIS-11 second-order attentional and nonplanning subscale scores. Results. Male gender, no history of smoking, postsecondary education, and heightened disease severity were predictive of increased BIS-11 attentional scores (p <0.05). Similarly, male gender, after secondary education, and disease severity were predictive of increased BIS-11 nonplanning scores (p <0.05). Contrary to previous reports, dopaminergic medication use was not a significant determinant of either BIS-11 subscale scores. Conclusions. Several demographic and clinical variables including male gender, no history of past smoking, after secondary education, and elevated disease severity are associated with impulsivity in PD.

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Collaboration types
Domestic collaboration
Citation topics
1 Clinical & Life Sciences
1.52 Neurodegenerative Diseases
1.52.67 Parkinson's Disease
Web Of Science research areas
Clinical Neurology
ESI research areas
Clinical Medicine
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