Pain assessment of individuals with Parkinson's disease - Université de Lorraine
Conference Papers Year : 2021

Pain assessment of individuals with Parkinson's disease

Abstract

Parkinson's disease (PD) is a chronic neurodegenerative disorder that commonly affects older people. Pain is one of the most common non-motor symptoms in this population, and it is very important to be constantly monitored and evaluated. However, there is a scarcity of questionnaires that effectively address the impact of pain in this population, and many instruments superficially assess this symptom. Then, the aim of this study was to remotely apply the Portuguese version of an already validated pain assessment questionnaire (MPI) in individuals with PD, and, with factor analysis, adjust/validate the questionnaire for this population and assess the level of pain perception felt by the respondents. The questionnaire was answered by 309 individuals with PD, 251 of whom reported the presence of pain. Factor analysis and descriptive statistics were used to analyze the data. The factor analysis (FA) suggested the exclusion of 2 items, and the grouping of the questions into 2 factors: affectability and severity of pain, and self-control and energy. The value of Cronbach's alpha was higher than that considered adequate, indicating high internal consistency of the instrument. A model to calculate the final scores of the respondents was established and, according to this model, it was observed that the individuals that made up the sample presented a high perception of pain, since many scored high scores. In summary, the evaluated questionnaire in is a complete pain assessment tool, and easily applied remotely to individuals with PD.
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Dates and versions

hal-03793080 , version 1 (30-09-2022)

Identifiers

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Luanne Cardoso Mendes, Isabela Alves Marques, Angela Abreu Rosa de Sá, Camille Marques Alves, Rodrigo Ramos Rosa, et al.. Pain assessment of individuals with Parkinson's disease. Seventeenth International Symposium on Medical Information Processing and Analysis, Nov 2021, Campinas, France. pp.61, ⟨10.1117/12.2606296⟩. ⟨hal-03793080⟩
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