scholarly journals The relationship between Pittsburgh Sleep Quality Index subscales and diabetes control

2018 ◽  
Vol 15 (3) ◽  
pp. 210-219 ◽  
Author(s):  
Onala Telford ◽  
Clarissa J Diamantidis ◽  
Hayden B Bosworth ◽  
Uptal D Patel ◽  
Clemontina A Davenport ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Diabetes Control ◽  
Poor Sleep ◽  
Medication Nonadherence ◽  
Mediating Factor ◽  
The Impact ◽  
The Relationship

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.

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
Keyword(s):  
Multiple Sclerosis ◽  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Performance Test ◽  
Pittsburgh Sleep Quality Index ◽  
Self Report ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
The Relationship

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.

scholarly journals Factors associated with poor sleep quality in women with cancer

2017 ◽  
Vol 25 (0) ◽  
Author(s):  
Thalyta Cristina Mansano-Schlosser ◽  
Maria Filomena Ceolim
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Factors Associated ◽  
Scale Data

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.

scholarly journals The impact of COVID-19 pandemic in the quality of sleep by Pittsburgh Sleep Quality Index: A systematic review

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 ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Health Professionals ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Eligibility Criteria ◽  
Different Populations ◽  
The Impact

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.

Stressed and Not Sleeping: Poor Sleep and Psychological Stress in Elite Athletes Prior to the Rio 2016 Olympic Games

2021 ◽  
pp. 1-8
Author(s):  
Shona L. Halson ◽  
Renee N. Appaneal ◽  
Marijke Welvaert ◽  
Nirav Maniar ◽  
Michael K. Drew
Keyword(s):  
Sleep Quality ◽  
Psychological Stress ◽  
Perceived Stress ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Olympic Games ◽  
Pittsburgh Sleep Quality Index ◽  
Elite Athletes ◽  
Poor Sleep ◽  
Stress Scale

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.

The relationship between sleep quality and fibromyalgia symptoms

2018 ◽  
Vol 25 (9) ◽  
pp. 1176-1186 ◽  
Author(s):  
Alexandro Andrade ◽  
Guilherme Torres Vilarino ◽  
Sofia Mendes Sieczkowska ◽  
Danilo Reis Coimbra ◽  
Guilherme Guimarães Bevilacqua ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Sleep Quality ◽  
Sleep Disorders ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Memory Failure ◽  
D 74 ◽  
The Relationship

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.

scholarly journals Sleep Quality in Semi-Professional Male Basketball Players in Bermuda

2021 ◽  
Author(s):  
Sharmella Roopchand-Martin
Keyword(s):  
Sleep Quality ◽  
Epworth Sleepiness Scale ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Basketball Players ◽  
Ethical Approval ◽  
The Mean

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.

scholarly journals The Relationship between Mindfulness and Sleep Quality is Mediated by Emotion Regulation

2020 ◽  
Vol 1 (2) ◽  
pp. 42-66
Author(s):  
Garrett Talley ◽  
John Shelley-Tremblay
Keyword(s):  
Emotion Regulation ◽  
Sleep Quality ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Self Report ◽  
Impact Of Event Scale ◽  
Event Scale ◽  
Acting With Awareness ◽  
The Impact ◽  
The Relationship

Background: Sleep is critical to a person’s overall physical and mental health. The current study investigated the relationship between mindfulness and sleep quality, to determine if this relationship is influenced by emotion regulation and perceived stress. Method: Three hundred sixty-seven undergraduate students responded to five self-report measures, (1) The Cognitive and Affective Mindfulness Scale (CAMS-R), (2) The Impact of Event Scale (IES-R), (3) The Five Facet Mindfulness Questionnaire (FFMQ), (4) The Emotion Regulation Questionnaire (ERQ), and (5) The Pittsburgh Sleep Quality Index (PSQI). Results: Results revealed (1) sleep quality was predicted by the presence of hyperarousal, acting with awareness, and the CAMS-R, (2) the Impact of Event Scale was moderately positively correlated with a person’s global score on the Pittsburgh Sleep Quality Index, and (3) the relationship between mindfulness and sleep quality was mediated by hyperarousal. Conclusions: Together, our findings suggest that higher levels of intrusive thoughts, avoidance, and hyperarousal are correlated with lower overall sleep quality, and the use of mindfulness techniques such as acting with awareness and being non-reacting to negative thoughts or hyperarousal may help predict an individual’s sleep quality.

scholarly journals Assessment of Sleep Quality in Patients with Osteoarthritis

2020 ◽  
Vol 7 (48) ◽  
pp. 2862-2866
Author(s):  
Pradeep Rangasamy ◽  
Ajay Thangaraj ◽  
Premkumar Kamatchinathan ◽  
Ananthavijay Karnan ◽  
Maikandaan Chandrasekar Janaganbose ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Rating Scale ◽  
Pittsburgh Sleep Quality Index ◽  
Poor Sleep ◽  
Pain Rating ◽  
Poor Sleep Quality ◽  
Numerical Pain Rating Scale ◽  
Pain Rating Scale

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)

scholarly journals 0819 Objective Sleep Efficiency is Associated with Longitudinal Risk of High Depressive Symptoms in Pregnant Women

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A312-A312
Author(s):  
S Tsai ◽  
P Lee ◽  
C Gordon ◽  
E Cayanan ◽  
C Lee
Keyword(s):  
Depressive Symptoms ◽  
Sleep Quality ◽  
Pregnant Women ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Depression Scale ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Subjective Sleep

Abstract Introduction Sleep disturbances are one of the most frequent complaints identified during routine prenatal care visits. Sleep and mood disturbances are often intertwined, and depression in particular is a leading cause of disability and disease burden worldwide. The purpose of this study was to examine the predictive association of objective actigraphic and subjective sleep disturbances with depressive symptoms in pregnant women. Methods We recruited 204 first-trimester pregnant women from a large university-affiliated hospital. They provided baseline socio-demographic and health information, wore a wrist actigraph for 7 days, and completed the Pittsburgh Sleep Quality Index and Center for Epidemiologic Studies - Depression Scale and repeated this again in the second and third trimesters. Each data collection was scheduled at least 8 weeks apart. Unadjusted and multivariable adjusted odds ratios with 95% confidence intervals were used to evaluate sleep disturbances at 1st trimester and risk of high depressive symptoms at follow-up. Results A total of 121 (59.3%) women had actigraphic sleep efficiency of &lt; 85% and 92 (45.1%) had Pittsburgh Sleep Quality Index global scores &gt; 5 indicative of poor sleep quality. In multivariable adjusted models, 1st trimester objectively measured sleep efficiency &lt; 85% was associated with 2.65-, 3.86-, and 5.27-fold increased odds having risk of high depressive symptoms at 2nd trimester, 3rd trimester, and both 2nd and 3rd trimesters, respectively. No subjective sleep disturbance variables were significantly associated with risk of high depressive symptoms in multivariate adjusted models. Conclusion Objectively assessed poor sleep efficiency in the 1st trimester plays a crucial role in the development of both elevated and persistent high depressive symptoms in pregnancy. Future studies using objective sleep measurements and clinical diagnostic interviews are warranted to examine whether early interventions to improve sleep may help reduce high depressive symptom risk and lower depression rates in women during pregnancy. Support This study was funded by the Ministry of Science and Technology, Taiwan (MOST-101-2314-B-002-049-MY3).

scholarly journals Reliability and Validity of the Czech Version of the Pittsburgh Sleep Quality Index in Patients with Sleep Disorders and Healthy Controls

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Denisa Manková ◽  
Daniela Dudysová ◽  
Jan Novák ◽  
Eva Fárková ◽  
Karolina Janků ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Sleep Quality ◽  
Sleep Disorders ◽  
Internal Consistency ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Control Sample ◽  
Likelihood Method ◽  
Poor Sleep

Objectives. Psychometric properties of the Czech version of the Pittsburgh Sleep Quality Index (PSQI-CZ) have been evaluated only in patients with chronic insomnia, and thus, it is unclear whether PSQI-CZ is suitable for use in other clinical and nonclinical populations. This study was aimed at examining the validity and reliability of the PSQI-CZ and at assessing whether the unidimensional or multidimensional scoring of the instrument would be recommended. Methods. A total of 524 adult subjects from the Czech population participated in the study. The internal consistency of PSQI was evaluated using Cronbach’s alpha. The known-group validity was tested using the Kruskal-Wallis H test to verify the difference between patients with sleep disorders and healthy control sample. For testing the structural validity, a cross-validation approach was used with both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). For EFA, the maximum likelihood method with direct oblimin rotation and parallel analysis was used. Results. The internal consistency of PSQI-CZ items was moderate ( α = 0.75 ). Receiver operating characteristic (ROC) curve analysis showed high specificity (0.79) and moderate sensitivity (0.64) using an optimal cut-off score of 10. The EFA revealed a 3-factor structure with factors labelled as “sleep duration and efficiency,” “sleep disturbances and quality,” and “sleep latency.” The CFA showed that the emerged 3-factor model had a partly acceptable fit, which was better than other previously supported models. Conclusions. A high cut-off score of 10 is recommended to define poor sleep quality. Given the inconsistency of structural analyses, alternative scoring was not recommended. However, the individual components in addition to a total score should be interpreted when assessing sleep quality. We recommend editing and verifying the PSQI-CZ translation.

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