scholarly journals The relationship between fatigability and sleep quality in people with multiple sclerosis

2016 ◽  
Vol 2 ◽  
pp. 205521731668277 ◽  
Author(s):  
Mayis Aldughmi ◽  
Jessie Huisinga ◽  
Sharon G Lynch ◽  
Catherine F Siengsukon

Background Perceived fatigue and fatigability are constructs of multiple sclerosis (MS)-related fatigue. Sleep disturbances lead to poor sleep quality, which has been found to be associated with perceived fatigue in people with MS (PwMS). However, the relationship between fatigability and sleep quality is unknown. Objective To explore the relationship between physical and cognitive fatigability with self-reported and objective measures of sleep quality in PwMS. Methods Fifty-one ambulatory PwMS participated in the study. Physical fatigability was measured by percent-change in meters walked on the six-minute walk test (6MWT) and in force exerted on a repeated maximal hand grip test. Cognitive fatigability was measured using response speed variability on the continuous performance test. Self-report sleep quality was measured using the Pittsburgh Sleep Quality Index, and objective sleep quality was measured using 1 week of actigraphy. Results Components of the Pittsburgh Sleep Quality Index and several actigraph parameters were significantly associated with physical fatigability and cognitive fatigability. However, controlling for depression eliminated the association between the sleep outcomes and cognitive fatigability and attenuated the association between the sleep outcomes and physical fatigability. Conclusion Poor sleep quality is related to fatigability in MS but depression appears to mediate these relationships.

Author(s):  
Thalyta Cristina Mansano-Schlosser ◽  
Maria Filomena Ceolim

ABSTRACT Objectives: to analyze the factors associated with poor sleep quality, its characteristics and components in women with breast cancer prior to surgery for removing the tumor and throughout the follow-up. Method: longitudinal study in a teaching hospital, with a sample of 102 women. The following were used: a questionnaire for sociodemographic and clinical characterization, the Pittsburgh Sleep Quality Index; the Beck Depression Inventory; and the Herth Hope Scale. Data collection covered from prior to the surgery for removal of the tumor (T0) to T1, on average 3.2 months; T2, on average 6.1 months; and T3, on average 12.4 months. Descriptive statistics and the Generalized Estimating Equations model were used. Results: depression and pain contributed to the increase in the score of the Pittsburgh Sleep Quality Index, and hope, to the reduction of the score - independently - throughout follow-up. Sleep disturbances were the component with the highest score throughout follow-up. Conclusion: the presence of depression and pain, prior to the surgery, contributed to the increase in the global score of the Pittsburgh Sleep Quality Index, which indicates worse quality of sleep throughout follow-up; greater hope, in its turn, influenced the reduction of the score of the Pittsburgh Sleep Quality Index.


2018 ◽  
Vol 25 (9) ◽  
pp. 1176-1186 ◽  
Author(s):  
Alexandro Andrade ◽  
Guilherme Torres Vilarino ◽  
Sofia Mendes Sieczkowska ◽  
Danilo Reis Coimbra ◽  
Guilherme Guimarães Bevilacqua ◽  
...  

This study investigated the relationship between sleep quality and fibromyalgia symptoms in 326 patients. The Pittsburgh Sleep Quality Index was used to assess the presence of sleep disorders. Multivariate analysis of variance was performed to determine the influence of fibromyalgia symptoms on sleep quality. The prevalence of sleep disorders was 92.9 percent. Patients reported generalized pain (88.3%), memory failure (78.5%), moodiness (59%), excessive anxiety (77.5%), and concentration difficulties (69.1%). Patients with more symptoms reported poor sleep quality ( p < .05; d = .74), and the total Pittsburgh Sleep Quality Index score correlated with the number of symptoms ( p < .01). Sleep quality has an important association with fibromyalgia symptoms.


2018 ◽  
Vol 15 (3) ◽  
pp. 210-219 ◽  
Author(s):  
Onala Telford ◽  
Clarissa J Diamantidis ◽  
Hayden B Bosworth ◽  
Uptal D Patel ◽  
Clemontina A Davenport ◽  
...  

Objectives Data suggest that poor sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) contributes to suboptimal diabetes control. How the subscales comprising the PSQI individually relate to diabetes control is poorly understood. Methods In order to explore how PSQI subscales relate to diabetes control, we analyzed baseline data from a trial of a telemedicine intervention for diabetes. We used multivariable modeling to examine: (1) the relationship between the global PSQI and hemoglobin A1c (HbA1c); (2) the relationships between the 7 PSQI subscales and HbA1c; and (3) medication nonadherence as a possible mediating factor. Results Global PSQI was not associated with HbA1c ( n = 279). Only one PSQI subscale, sleep disturbances, was associated with HbA1c after covariate adjustment; HbA1c increased by 0.4 points for each additional sleep disturbances subscale point (95%CI 0.1 to 0.8). Although the sleep disturbances subscale was associated with medication nonadherence (OR 2.04, 95%CI 1.27 to 3.30), a mediation analysis indicated nonadherence does not mediate the sleep disturbances-HbA1c relationship. Discussion The sleep disturbances subscale may drive the previously observed relationship between PSQI and HbA1c. The mechanism for the relationship between sleep disturbances and HbA1c remains unclear, as does the impact on HbA1c of addressing sleep disturbances.


Author(s):  
Sharmella Roopchand-Martin

Objectives: This study sought to determine the quality of sleep using the Pittsburgh Sleep Quality Index (PSQI), the presence of sleepiness using the Epworth Sleepiness Scale (ESS) and the association between sleep quality and sleepiness in basketball players in Bermuda. Methods: Once ethical approval was granted, players were recruited from the Bermuda Basketball Association League. All participants completed the PSQI and the ESS questionnaires based on their recollection of events as they occurred over the previous 30 days. Their responses were analysed using the IBM SPSS version 19 for Windows. Results: A total of 71 subjects, mean age 24.96 ± 3.19 years, participated in this study. The mean PSQI score was 7.8 ± 4.7 (scores of 5 or more indicate poor sleep quality). Thirty percent of players rated their sleep quality as fairly bad to very bad. The mean sleepiness score was 7.35 ± 4.17 and over 60% of persons surveyed had more than normal levels of sleepiness. There was a significant correlation between sleep quality and sleepiness; 0.61 (p < 0.01), as well as a correlation between age and Global PSQI which had a score of 0.31 (p < 0.01). Conclusion: Basketball players in Bermuda are experiencing less than optimal sleep. Insomnia was among the most popular self-reported cause of sleep disturbances. Further research is required in this population, exploring causal factors for poor sleep quality. Key words: Athletes, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Sleep Quality.


2020 ◽  
Vol 7 (48) ◽  
pp. 2862-2866
Author(s):  
Pradeep Rangasamy ◽  
Ajay Thangaraj ◽  
Premkumar Kamatchinathan ◽  
Ananthavijay Karnan ◽  
Maikandaan Chandrasekar Janaganbose ◽  
...  

BACKGROUND Sleep disturbances usually accompany osteoarthritis (OA) because of chronic pain. Poor sleep quality is related to many factors like pain, fatiguability, restless leg syndrome, immobility of joints, anxiety and depression. But the quality of the sleep in patients with osteoarthritis has been rarely studied. We wanted to assess the prevalence of sleep disturbances in OA patients, determine the sleep quality in osteoarthritis patients and evaluate the relationship between pains and sleep quality. METHODS 150 patients with osteoarthritis were selected through convenience sampling as per the inclusion and exclusion criteria. Pittsburgh Sleep Quality Index (PSQI) and Numerical Pain Rating Scale (NPRS) were applied. Data was analysed using SPSS. One sample T test and Pearson Correlation were applied to find the correlation between the pains and sleep quality. RESULTS A total of 86 (57 %) patients with osteoarthritis were found to have sleep disturbances and were assessed for sleep quality and pain level. This group contains 18 (20 %) males and 68 (80 %) females. A total of 62 (72 %) osteoarthritis patients including 14 males and 48 females were having poor sleep quality; 67 (78 %) patients had intolerable pain (NPRS > 7). Strong positive correlation (p-value < 0.001) was found between GPSQI and NPRS. CONCLUSIONS Patients with osteoarthritis with high NPRS values have poor sleep quality. There is significant association between pain and poor sleep quality. It will be highly useful for the patients with osteoarthritis if osteoarthritis treatment protocol includes assessment and management of poor sleep quality. As poor quality is an early indicator of majority of mental illnesses, psychiatric liaison services will be highly beneficial for patients with osteoarthritis. KEYWORDS Osteoarthritis, Pain, Sleep Quality, Numerical Pain Rating Scale (NPRS), Pittsburgh Sleep Quality Index (PSQI)


2020 ◽  
Vol 11 ◽  
Author(s):  
Jinru Liu ◽  
Lin Zhu ◽  
Conghui Liu

This study examined the mediating roles of both positive and negative affects in the relationship between sleep quality and self-control. A sample of 1,507 Chinese adults (37% men; mean age = 32.5 years) completed self-report questionnaires measuring sleep quality, positive and negative emotions, and self-control. Poor sleep quality was positively correlated with negative affect and negatively correlated with positive affect and self-control. Positive affect was positively correlated with self-control, while negative affect was negatively correlated with self-control. Both positive and negative affects significantly mediated the relationship between sleep quality and self-control. Improving individuals’ sleep qualities may lead to more positive emotions and less negative emotion, and these mood changes may increase resources for self-control. Regulating positive and negative affects may reduce the negative effects of poor sleep quality on self-control.


2020 ◽  
Vol 70 (6) ◽  
pp. 1640-44
Author(s):  
Syed Sakhawat Kazmi ◽  
Zahid Hassan ◽  
Waseem Alamgir ◽  
Asif Hashmat ◽  
Muhammad Ali Yousaf ◽  
...  

Objective: To determine the frequency of poor sleep quality among the patients of Parkinson’s disease (PD) and analyze its relationship with the socio-demographic factors.Study Design: Correlational study. Place and Duration of Study: Pak Emirates Military Hospital Rawalpindi, from Jan 2019 to Jun 2019. Methodology: One hundred and fifty patients of Parkinson’s disease were approached to participate in this study. Pittsburgh sleep quality index (PSQI) was the psychometric tool used to assess the study parameter for the patients. Age, gender, duration of illness, poly pharmacy and tobacco smoking were corelated with presence of poor quality of sleep among the patients of Parkinson’s disease. Results: Out of 150 patients of Parkinson’s disease screened through Pittsburgh sleep quality index, 85 (56.7%)showed the presence of poor sleep quality while 65 (43.3%) had good sleep quality. Mean age of the patients was 66.2 ± 4.648 years. After applying the logistic regression, we found that increasing age and longer duration of illness had significant association with the presence of poor sleep quality among the patients of Parkinson disease. Conclusion: Previously considered a pure motor disorder, Parkinsonism has a lot of other neuro-psychiatricmanifestations as well. Poor sleep quality turned out to be one of these non-motor problems associated with this chronic debilitating illness. Increasing age and longer duration of illness among these patients emerged asindependent risk factors for poor sleep quality in Parkinsonism.


2021 ◽  
Vol 26 (4) ◽  
pp. 1457-1466
Author(s):  
Luiz Felipe Ferreira de Souza ◽  
Laisa Liane Paineiras-Domingos ◽  
Maria Eduarda de Souza Melo-Oliveira ◽  
Juliana Pessanha-Freitas ◽  
Eloá Moreira-Marconi ◽  
...  

Abstract This article aims to evaluate the sleep quality in individuals during the COVID-19 pandemic by Pittsburgh Sleep Quality Index (PSQI). Searches were conducted in the PubMed, Embase, Web of Science, and PEDro databases, on May 22, 2020. In the publications, 208 articles were found and, considering the eligibility criteria, 10 articles were included at the end, showing the effects on sleep quality during the pandemic, in populations hospitalized, quarantined, and in frontline health professionals. The PSQI measured sleep disorders and a higher score indicated poor sleep quality. Nine articles were classified with evidence level IV and one as level III-2. Eight studies present a “serious” risk of bias and two in “moderate”. The studies investigated different populations and described the results as “poor” sleep quality, considering the PSQI on quarantined individuals and frontline health professionals as the most committed. A poor sleep quality was found in the populations evaluated in the selected publications, probably, due to the COVID-19 to contribute as a risk factor for mental health. Psychological interventions must be made to minimize the consequences through social support and social capital.


Author(s):  
Shona L. Halson ◽  
Renee N. Appaneal ◽  
Marijke Welvaert ◽  
Nirav Maniar ◽  
Michael K. Drew

Purpose: Psychological stress is reported to be an important contributor to reduced sleep quality and quantity observed in elite athletes. The purpose of this study was to explore the association between psychological stress and sleep and to identify if specific aspects of sleep are disturbed. Methods: One hundred thirty-one elite athletes (mean [SD], male: n = 46, age 25.8 [4.1] y; female: n = 85, age 24.3 [3.9] y) from a range of sports completed a series of questionnaires in a 1-month period approximately 4 months before the 2016 Rio Olympic Games. Questionnaires included the Pittsburgh Sleep Quality Index; Recovery-Stress Questionnaire; Depression, Anxiety, and Stress Scale (DASS 21); and Perceived Stress Scale (PSS). Results: Regression analysis identified the PSS and DASS stress as the main variables associated with sleep. A PSS score of 6.5 or higher was associated with poor sleep. In addition, a PSS score lower than 6.5 combined with a DASS stress score higher than 4.5 was also associated with poor sleep. Univariate analyses on subcomponents of the Pittsburgh Sleep Quality Index confirmed that PSS is associated with lower sleep quality (t99 = 2.40, P = .018), increased sleep disturbances (t99 = 3.37, P = .001), and increased daytime dysfunction (t99 = 2.93, P = .004). DASS stress was associated with increased sleep latency (t94 = 2.73, P = .008), increased sleep disturbances (t94 = 2.25, P = .027), and increased daytime dysfunction (t94 = 3.58, P = .001). Conclusions: A higher stress state and higher perceived stress were associated with poorer sleep, in particular increased sleep disturbances and increased daytime dysfunction. Data suggest that relatively low levels of psychological stress are associated with poor sleep in elite athletes.


2017 ◽  
Vol 28 (3) ◽  
pp. 356-373 ◽  
Author(s):  
Masomeh Norozi Firoz ◽  
Vida Shafipour ◽  
Hedayat Jafari ◽  
Seyed Hamzeh Hosseini ◽  
Jamshid Yazdani - Charati

This descriptive correlational study was aimed at determining the relationship of hemodialysis shift with sleep quality and depression in 310 hemodialysis patients. Demographic and Clinical Questionnaires, the Pittsburgh sleep quality index, and Beck’s Depression Inventory were used to ascertain the aforementioned relationship. Among the patients, 59.6% reported poor sleep quality and 44.8% reported experiencing depression. Results show that these conditions were significantly related to many factors. Although dialysis shift was not significantly related to sleep quality and depression, sleep quality was found significantly associated with age, female gender, illiteracy, unemployment, residence in rural areas, diabetes, addiction to sedatives, and phosphorus levels. A significant relationship was also found between depression and phosphorus levels. Logistic regression predicted age, gender, illiteracy, unemployment, residence in rural areas, and addiction to sedatives as factors for poor sleep quality. A body mass index (BMI) above 30, decreased urea, and increased phosphorus were predicted as factors for increased depression.


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