scholarly journals The Effect of Detoxification on Sleep: How Does Sleep Quality Change during Qualified Detoxification Treatment?

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Peter Neu ◽  
Yvonne Sofin ◽  
Heidi Danker-Hopfe

Aims. Sleep disturbances are common in addiction and withdrawal. This study examined the course of sleep quality in a population of alcohol dependent patients during qualified detoxification treatment in a psychiatric hospital. Methods. The Pittsburgh Sleep Quality Index (PSQI) was administered to 77 electively admitted alcohol dependent patients hospitalized for qualified detoxification treatment. Sleep quality was measured at admission and at discharge. Results. The prevalence of bad sleep as measured by a PSQI-score > 5 was 70.1% at admission. During detoxification, male and female patients were equally affected by sleep disturbances and improvement of sleep was not significantly different between males and females. The PSQI score at admission predicted the change of the PSQI score during qualified detoxification treatment. After inpatient detoxification, sleep disturbances persisted in 59.7% of the patients. Conclusions. Contrary to our expectations, the average patient’s sleep quality improved in our study after two weeks of detoxification treatment. Sleep disturbances nevertheless persisted in almost two-thirds of the patients. In the view of that finding, patients may require individual evaluation of sleep quality and insomnia-specific treatment in the course of detoxification therapy.

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.


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.


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.


2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1170-1170
Author(s):  
Pratibha Gupta ◽  
Matt Collins

Abstract Objectives Identify, compare sleep habit questionnaires for use in a study of college student's body compositions, and academic performances. Methods Decades of research supports the importance of proper sleep habits for college students for optimum academic performances and maintaining a healthy lifestyle. Instrument that can identify students who experience sleep disturbances and who do not get enough sleep is important in preventing obesity in college students during their college experience and afterwords. Some surveys were created for the clinical setting to determine if further diagnostics testing is necessary, while others were designed for use in academic research to be used individually, combined into composite measure of sleep or as covariates. Available instruments measure many different variables from day time sleepiness to chronotype and jet-lag. No single survey stands out as an all -encompassing sleep different aspect of sleep. No cross comparison of instruments measuring the same variable is therefore possible. Sleep survey is considered ensuring that the chosen survey was designed to measure the variables of interest. Following scales were used in the study: Standford Sleepiness Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Horne-Ostberg Moringness Eveningness Questionnaire, Munich Chronotype Questionnaire. Results Students not meeting public health recommendations for sleep quality and quantity were found to have a significantly lower grade point average and individuals with sleep disturbances and short sleep duration have a significantly higher incidence of obesity. Conclusions Each instrument was created to measure a specific but different aspect of sleep. When conducting research with these tools, another questionnaire may be necessary to provide data specifically about the the subject's sleep habits. The Pittsburgh Sleep quality index has seen through use both clinically and in research. However, it requires another questionnaires to provide data on other variables. Each questionnaire effectively measures the concept it was designed to measure. Therefore, the choice of appropriate instrument should be based on the question, “which survey measures the variable that I wish to measure?”, not which survey is the best? Funding Sources NIMHD BRIC Grant 2009–2013 Central State University.


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.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Flavie Waters ◽  
Neepa Naik ◽  
Daniel Rock

This study sought to examine the association between sleep, fatigue, and functional health in psychotic patients. Participants included 93 psychotic inpatients (n=67with schizophrenia) who completed the Chalder Fatigue Scale (ChFS), the Fatigue Symptom Inventory (FSI), the Pittsburgh Sleep Quality Index (PSQI), and the SF36 Health Survey. Patients were classified on the basis of their performance on sleep and fatigue measures: 60% reported significant levels of fatigue and 67% significant sleep disturbances. 28.4% reported both, suggesting that fatigue and sleep dysfunctions do not necessarily cooccur. A closer examination of patterns showed that fatigue was only related to qualitative aspects of sleep and not quantifiable aspects of sleep disturbances. The results also showed that functional health was the lowest in patients with high levels of fatigue, compared to patients with sleep problems only or patients with neither symptom. A regression analysis further showed that the size of the contribution of fatigue onto functional health was twice as much as that of sleep dysfunctions. In conclusion, the results show that (i) dissatisfaction with sleep—and not sleep itself—is related to fatigue symptoms and that (ii) fatigue is particularly detrimental to functional health, regardless of the presence of sleep dysfunctions.


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.


2022 ◽  
Vol 11 ◽  
pp. 266-269
Author(s):  
Omar Hamad Alkadhi ◽  
Ali A. Alomran ◽  
Nawaf S. Alrafee ◽  
Faisal A. Alaresh ◽  
Marzouq S. Alqahtani ◽  
...  

Objectives: The aim of this study was to investigate the effect of pain caused by orthodontic fixed appliances on sleep quality of participants using the Pittsburgh Sleep Quality Index (PSQI). Materials and Methods: A previously validated Arabic version of PSQI was electronically distributed through different social media platforms and in waiting areas of orthodontic offices. Eligibility criteria included healthy adults and adolescents with orthodontic fixed appliances and with no systemic conditions that may affect sleep. The cut-off point used to determine poor sleep quality was (>5). Results: Three hundred and eighteen participants were included in the final analysis (28.9% males and 71.1% females). Both males and females with orthodontic fixed appliances had poor sleep quality with (Mean = 6.48, SD = 2.85, P = 0.000) for males, and (Mean = 7.18, SD = 2.87, P = 0.000) for females. Comparing males and females, we found that females scored higher than males in both subjective sleep quality and PSQI global score. Conclusion: Individuals undergoing orthodontic treatment with fixed appliances have poor sleep quality. Females undergoing orthodontic treatment tend to have poorer sleep quality compared to males.


2000 ◽  
Vol 122 (4) ◽  
pp. 542-546
Author(s):  
Richard E. Gliklich ◽  
Farhan Taghizadeh ◽  
John W. Winkelman

The health status of 435 consecutive patients with sleep disturbances necessitating polysomnography was investigated. Patients underwent overnight polysomnography and health status assessment, including the Medical Outcomes Study SF-36 Health Survey and the Pittsburgh Sleep Quality Index. Based on a respiratory distress index (RDI) greater than 10 to define apnea, patients with apnea were significantly ( P < 0.05) more likely to be male, be older, and have higher body mass index and lower oxygen saturation levels than patients without apnea. Multiple domains of the SF-36 Health Survey and the Pittsburgh Sleep Quality Index were significantly worse ( P < 0.05) for this population when normative data were compared. Although few differences were observed between the apneic and nonapneic patients when a cutoff point for apnea was defined as an RDI greater than 10 or 20, increasing RDI was significantly associated with worsening physical functioning scores. Overall, decrements in health status measures were more strongly correlated with the number of oxygen desaturations below 85% than with increasing RDI. We conclude that patients with sleep disturbances demonstrate significant decrements in general and sleep-specific health status, but these decrements are more closely associated with oxygen desaturation than RDI.


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)


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