45 research outputs found
Beyond factor analysis: Multidimensionality and the Parkinsonās Disease Sleep Scale-Revised
Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinsonās disease (PD). The Parkinsonās Disease Sleep Scale (PDSS) and its variants (the Parkinsonās disease Sleep Scale-Revised; PDSS-R, and the Parkinsonās Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments
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Parkinson's disease and REM sleep behavior disorder result in increased non-motor symptoms
Objective: Rapid eye movement (REM)-sleep behavior disorder (RBD) is often comorbid with Parkinson's disease (PD). The current study aimed to provide a detailed understanding of the impact of having RBD on multiple non-motor symptoms (NMS) in patients with PD. Methods: A total of 86 participants were evaluated for RBD and assessed for multiple NMS of PD. Principal component analysis was utilized to model multiple measures of NMS in PD, and a multivariate analysis of variance was used to assess the relationship between RBD and the multiple NMS measures. Seven NMS measures were assessed: cognition, quality of life, fatigue, sleepiness, overall sleep, mood, and overall NMS of PD. Results: Among the PD patients, 36 were classified as having RBD (objective polysomnography and subjective findings), 26 as not having RBD (neither objective nor subjective findings), and 24 as probably having RBD (either subjective or objective findings). RBD was a significant predictor of increased NMS in PD while controlling for dopaminergic therapy and age (p=0.01). The RBD group reported more NMS of depression (p=0.012), fatigue (p=0.036), overall sleep (p=0.018), and overall NMS (p=0.002). Conclusion: In PD, RBD is associated with more NMS, particularly increased depressive symptoms, sleep disturbances, and fatigue. More research is needed to assess whether PD patients with RBD represent a subtype of PD with different disease progression and phenomenological presentation. Ā© 2014 Elsevier B.V
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Parkinson's disease and REM sleep behavior disorder result in increased non-motor symptoms
Objective: Rapid eye movement (REM)-sleep behavior disorder (RBD) is often comorbid with Parkinson's disease (PD). The current study aimed to provide a detailed understanding of the impact of having RBD on multiple non-motor symptoms (NMS) in patients with PD. Methods: A total of 86 participants were evaluated for RBD and assessed for multiple NMS of PD. Principal component analysis was utilized to model multiple measures of NMS in PD, and a multivariate analysis of variance was used to assess the relationship between RBD and the multiple NMS measures. Seven NMS measures were assessed: cognition, quality of life, fatigue, sleepiness, overall sleep, mood, and overall NMS of PD. Results: Among the PD patients, 36 were classified as having RBD (objective polysomnography and subjective findings), 26 as not having RBD (neither objective nor subjective findings), and 24 as probably having RBD (either subjective or objective findings). RBD was a significant predictor of increased NMS in PD while controlling for dopaminergic therapy and age (p=0.01). The RBD group reported more NMS of depression (p=0.012), fatigue (p=0.036), overall sleep (p=0.018), and overall NMS (p=0.002). Conclusion: In PD, RBD is associated with more NMS, particularly increased depressive symptoms, sleep disturbances, and fatigue. More research is needed to assess whether PD patients with RBD represent a subtype of PD with different disease progression and phenomenological presentation. Ā© 2014 Elsevier B.V
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Sleep, fatigue, depression, and circadian activity rhythms in women with breast cancer before and after treatment: A 1-year longitudinal study
Purpose: Sleep disturbance, fatigue and depression are common complaints in patients with cancer, and often contribute to worse quality of life (QoL). Circadian activity rhythms (CARs) are often disrupted in cancer patients. These symptoms worsen during treatment, but less is known about their long-term trajectory. Methods: Sixty-eight women with stage I-III breast cancer (BC) scheduled to receive ā„4 cycles of chemotherapy, and age-, ethnicity-, and education-matched normal, cancer-free controls (NC) participated. Sleep was measured with actigraphy (nocturnal total sleep time [nocturnal TST] and daytime total nap time [NAPTIME]) and with the Pittsburgh Sleep Quality Index (PSQI); fatigue with the Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF); depression with the Center of Epidemiological Studies-Depression (CES-D). CARs were derived from actigraphy. Several measures of QoL were administered. Data were collected at three time points: before (baseline), end of cycle 4 (cycle 4), and 1 year post-chemotherapy (1 year). Results: Compared to NC, BC had longer NAPTIME, worse sleep quality, more fatigue, more depressive symptoms, more disrupted CARs, and worse QoL at baseline (all p values <0.05). At cycle 4, BC showed worse sleep, increased fatigue, more depressive symptoms, and more disrupted CARs compared to their own baseline levels and to NC (all p values <0.05). By 1 year, BC's fatigue, depressive symptoms, and QoL returned to baseline levels but were still worse than those of NC, while NAPTIME and CARs did not differ from NC's. Conclusion: Additional research is needed to determine if beginning treatment of these symptoms before the start of chemotherapy will minimize symptom severity over time. Ā© Springer-Verlag 2014