Association Between Somatization and Nonmotor Symptoms Severity in People With Parkinson Disease

Polo-Morales, Aranza; Alcocer-Salas, Ángel; Rodríguez-Violante, Mayela; Pinto-Solís, Daniella; Solís-Vivanco, Rodolfo; Cervantes-Arriaga, Amín

doi:10.1177/0891988720901787

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…However, the results also showed that the somatization and fear scores of the SCL-90 scale were also higher than those of the general population, which has not been reported in previous studies (10,20,22,23). Somatization is generally related to physiological-pathological factors, psychological factors, and other reactions (24)(25)(26). The increase in somatization in SMA parents may be associated with increased stress, impaired sleep, anxiety, and depression when caring for children with SMA.…”

Section: Psychiatric Symptoms Of Sma Parentsmentioning

confidence: 55%

Analysis of scores of Symptom Checklist 90 (SCL-90) questionnaire of 182 parents of children with spinal muscular atrophy: a cross-sectional study

Du¹,

Dong²,

Miao³

et al. 2022

Transl Pediatr

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Background: Spinal muscular atrophy (SMA) is a hereditary disorder characterized by progressive muscle weakness and atrophy in children. However, less attention is paid to psychiatric symptoms of SMA parents.Attention to the psychiatric symptoms of parents of SMA children can improve the comprehensiveness of family support for SMA children, which is beneficial to the rehabilitation of SMA children. Here, we conducted a survey on the psychiatric symptoms of SMA parents and analyzed its relevant factors, with an attempt to inform the psychological support for SMA parents. Methods:The Symptom Checklist 90 (SCL-90) and a self-designed basic information (such as parent's gender, household area, place of residence, education background, etc.) questionnaire (in electronic questionnaire) were distributed to parents of SMA children aged 0-18 in a charity WeChat group sponsored by the Meier Advocacy & Support Center for SMA during the period from August 1 to August 31, 2021.Parents completed the electronic questionnaires by mobile phone or computer voluntarily. A total of 188 questionnaires were obtained, of which 182 were valid. Comparisons were performed with the SCL-90 adult norms as the standards. The potential correlations between the general data of SMA parents and children and abnormal factors in the SCL-90 for SMA parents were analyzed. Results:The SCL-90 factors somatization (1.56±0.80, P=0.002), depression (1.78±0.98, P<0.001), anxiety (1.58±0.87, P=0.007), fear (1.39±0.74, P=0.003), and sleep and eating problems (1.67±0.87, P=0.014) of SMA parents were significantly higher than the national norms. Place of residence was correlated with sleep and eating problems (r=0.158, P=0.033). Increasing age [odds ratio (OR) =1.012, P=0.014] and continuous homeliving status (OR =0.360, P=0.031) of SMA children increased the risk of depression in their parents, and the lack of rehabilitation management in SMA children increased the risk of anxiety of their parents (OR =0.409, P=0.038). Non-urban residence (OR =2.602, P=0.017) and poor physical health (OR =0.163, P=0.031) were the relevant factors for the increased risk of sleep and eating problems in SMA parents.Conclusions: SMA parents have a higher risk of developing psychiatric symptoms problems compared with the general population. Increasing age and the continuous home-living status of SMA children increase the risk of depression in their parents, and the lack of rehabilitation management increase the risk of anxiety in SMA parents.

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Section: Psychiatric Symptoms Of Sma Parentsmentioning

confidence: 55%

Analysis of scores of Symptom Checklist 90 (SCL-90) questionnaire of 182 parents of children with spinal muscular atrophy: a cross-sectional study

Du¹,

Dong²,

Miao³

et al. 2022

Transl Pediatr

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“…Third, patients with depression often report somatic symptoms ( 41 , 42 ). Likewise, it is already known that somatization in PD is associated with a higher NMSS total score ( 43 ). Accordingly, there is a higher probability that the somatic symptoms of PD patients with depression may overlap with other non-motor symptoms.…”

Section: Discussionmentioning

confidence: 87%

Longitudinal analysis of the Non-Motor Symptoms Scale in Parkinson's Disease (NMSS): An exploratory network analysis approach

et al. 2023

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IntroductionParkinson's disease (PD) is a multisystem neurodegenerative disorder characterized by motor and non-motor symptoms. In particular, non-motor symptoms have become increasingly relevant to disease progression. This study aimed to reveal which non-motor symptoms have the highest impact on the complex interacting system of various non-motor symptoms and to determine the progression of these interactions over time.MethodsWe performed exploratory network analyses of 499 patients with PD from the Cohort of Patients with Parkinson's Disease in Spain study, who had Non-Motor Symptoms Scale in Parkinson's Disease ratings obtained at baseline and a 2-year follow-up. Patients were aged between 30 and 75 years and had no dementia. The strength centrality measures were determined using the extended Bayesian information criterion and the least absolute shrinkage and selection operator. A network comparison test was conducted for the longitudinal analyses.ResultsOur study revealed that the depressive symptoms anhedonia and feeling sad had the strongest impact on the overall pattern of non-motor symptoms in PD. Although several non-motor symptoms increase in intensity over time, their complex interacting networks remain stable.ConclusionOur results suggest that anhedonia and feeling sad are influential non-motor symptoms in the network and, thus, are promising targets for interventions as they are closely linked to other non-motor symptoms.

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“…We collected clinical information from patients, including sex, age, course of the disease, education level, levodopa dose, Barthel index, Hoehn and Yahr stage, and Unified Parkinson’s Disease Rating Scale (UPDRS) parts I–III subscale scores [ 15 , 16 , 17 , 18 , 19 ].…”

Section: Methodsmentioning

confidence: 99%

Prediction of Cognitive Degeneration in Parkinson’s Disease Patients Using a Machine Learning Method

et al. 2022

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This study developed a predictive model for cognitive degeneration in patients with Parkinson’s disease (PD) using a machine learning method. The clinical data, plasma biomarkers, and neuropsychological test results of patients with PD were collected and utilized as model predictors. Machine learning methods comprising support vector machines (SVMs) and principal component analysis (PCA) were applied to obtain a cognitive classification model. Using 32 comprehensive predictive parameters, the PCA-SVM classifier reached 92.3% accuracy and 0.929 area under the receiver operating characteristic curve (AUC). Furthermore, the accuracy could be increased to 100% and the AUC to 1.0 in a PCA-SVM model using only 13 carefully chosen features.

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Association Between Somatization and Nonmotor Symptoms Severity in People With Parkinson Disease

Cited by 8 publications

References 32 publications

Analysis of scores of Symptom Checklist 90 (SCL-90) questionnaire of 182 parents of children with spinal muscular atrophy: a cross-sectional study

Analysis of scores of Symptom Checklist 90 (SCL-90) questionnaire of 182 parents of children with spinal muscular atrophy: a cross-sectional study

Longitudinal analysis of the Non-Motor Symptoms Scale in Parkinson's Disease (NMSS): An exploratory network analysis approach

Prediction of Cognitive Degeneration in Parkinson’s Disease Patients Using a Machine Learning Method

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