Variance In Sleep Quality Research Articles

Factors related to sleep quality in hospitalized antepartum women: A cross-sectional study.

This study investigated the sleep quality and its psychological correlates among hospitalized antepartum women. A cross-sectional correlation study design and convenience sampling were conducted in the gynecological ward of a medical center in northern Taiwan. A total of 101 hospitalized antepartum women were recruited. A self-administered structured questionnaire including demographic profiles, State-Trait Anxiety Inventory (STAI), Antepartum Hospital Stressors Inventory (AHSI), and Pittsburgh Sleep Quality Index (PSQI) was used for the study. Bivariate and multiple linear regressions were used to analyze the data. A majority of the participants had poor sleep quality (82.8%), based on the global PSQI score. Sleep quality correlated with age, marital and employment status, parity, method of conception, multiple gestation, history of pregnant complications, anxiety symptom and hospital stressors which explained 21% of the variance in sleep quality. This study found a high prevalence of poor sleep quality in hospitalized antepartum women. Anxiety symptom was a significant predictor of sleep quality. Healthcare providers should be encouraged to assess sleep and emotional status in antepartum women during hospitalization and provide them appropriate interventions to improve sleep and reduce anxiety symptoms and hospital stressors.

Factors associated with sleep quality in patients undergoing cardiac surgery: A longitudinal study.

Poor sleep quality is associated with multiple factors in cardiac surgery patients. To examine the trajectory of sleep quality and its associated factors over 3 months in Taiwanese patients undergoing cardiac surgery. A longitudinal study. This study enrolled 95 patients undergoing cardiac surgery in northern Taiwan. Sleep quality was measured using the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale before surgery, at discharge, and at 1 month and 3 months postsurgery. The majority of participants reported poor sleep quality before cardiac surgery (76.8%) and at discharge (81.6%), and they showed significant improvements in sleep quality at 1 month (B = -0.93, p = .023) and 3 months postsurgery (B = -1.50, p < .001). Significant daytime sleepiness was reported by 25.3% of patients before cardiac surgery, and this proportion significantly decreased at 3 months postsurgery (B = -2.59, p < .001). The significant predictors of sleep quality in cardiac surgery patients were symptom distress, sleep medications, occupation, left ventricular ejection fraction, ACE-I drugs and potassium ions, which explained 53.7% of the total variance in sleep quality. Having a nap habit was an independent predictor of daytime sleepiness in cardiac surgery patients, which could explain 3.7% of the total variation. Poor sleep quality was common in patients undergoing cardiac surgery and was associated with multiple factors, including symptom distress, cardiac function, medications, and psychosocial and environmental factors. Poor sleep quality was observed in cardiac surgical patients before surgery and at discharge postsurgery. Patient education on symptom management, medication adherence and sleep hygiene are suggested to improve sleep quality in patients undergoing cardiac surgery.

The Effect of Sleep Enhancement Educational Program on Maternal Sleep Quality for Nulliparous Pregnant Women: A Randomized-Controlled Trial.

Pregnancy is a critical period during which women usually do not prefer taking medication. Therefore, non-pharmacological and safe methods are needed to improve sleep quality during pregnancy. This study aims to identify whether an educational program on sleep enhancement for pregnant women has any effect on maternal sleep quality. This was a randomized-controlled trial. Pregnant women (N = 181) were divided into two groups, an intervention group (n = 90) and a control group (n = 91). A two-session educational program for the enhancement of sleep quality was provided to the intervention group, whereas solely the routine practices of the hospital were put in place for the control group. The intervention group had a significantly lower mean Pittsburgh Sleep Quality Index score, and accordingly, better sleep quality than the control group. Participation in the education program was significantly related to sleep quality and accounted for 6% of the total variance in sleep quality (R2 = 0.055) (p < 0.001). It was concluded that the educational program on sleep enhancement implemented to improve the sleep quality of pregnant women enhanced maternal sleep quality. URL: clinicaltrials.gov . NCT04262349.

Predicting Sleep Quality Based on Migraine Headaches and Rumination in Women with Panic Attacks

Objective: The present study aimed to predict sleep quality based on migraine headaches and rumination in women with panic attacks. Methods: This applied and descriptive-correlational study included a sample of women who visited psychological clinics in the city of Isfahan. Using convenience sampling, 210 participants were selected. Data were collected using the Pittsburgh Sleep Quality Index (1989), Ahvaz Migraine Headache Symptoms Questionnaire (1997), and the Rumination-Reflection Questionnaire by Trapnell and Campbell (1999). For data analysis, simultaneous multiple regression was performed using SPSS version 21. Findings: The findings indicated that migraine headaches and rumination could explain 30.5% of the variance in sleep quality among patients with panic attacks. Specifically, with each standard deviation increase in migraine headache and rumination scores, there was a corresponding increase of 0.532 and 0.371 standard deviations in sleep quality scores, respectively (P &lt; 0.01). Conclusion: Based on the results, migraine headaches and rumination can predict sleep quality in patients with panic attacks.

Anxiety, depression, and sleep quality among breast cancer patients in North China: Mediating roles of hope and medical social support.

Sleep disorders are highly prevalent among breast cancer patients and have a detrimental impact on their quality of life. This study aims to investigate the serial multiple mediating roles of social support and hope in the relationship between anxiety, depression, and sleep quality in breast cancer patients. A cross-sectional study was conducted in China from October 2021 to February 2022. A total of 315 breast cancer patients were assessed using self-reported questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), Medical Outcomes Study Social Support Survey (MOS-SSS), Herth Hope Index (HHI), and Hospital Anxiety and Depression Scale (HADS). Mediation analysis was performed using the R Statistical Software. Sleep quality exhibited a negative correlation with hope and medical social support (P < 0.01), and a positive correlation with anxiety and depression (P < 0.01). Anxiety and depression accounted for 18.8% and 12.8% of the variance in sleep quality, respectively. Bootstrap analyses of the anxiety-medical social support-hope-sleep quality pathway indicated the presence of direct effects [B = 0.331, 95%CI (0.215, 0.493)] and indirect effects of anxiety on sleep quality mediated solely by medical social support [B = 0.054, 95%CI (0.015, 0.108)] and hope [B = 0.041, 95%CI (0.018, 0.073)], as well as combined effects [B = 0.012, 95%CI (0.004, 0.025)]. Similarly, the depression-medical social support-hope-sleep quality pathway revealed direct effects [B = 0.235, 95%CI (0.104, 0.372)] and indirect effects of depression on sleep quality mediated solely by medical social support [B = 0.078, 95%CI (0.016, 0.150)] and hope [B = 0.049, 95%CI (0.018, 0.086)], as well as combined effects [B = 0.017, 95%CI (0.004, 0.034)]. This research validates the hypothesis that medical social support and hope serve as mediators between anxiety, depression, and sleep quality in breast cancer patients. Interventions targeting anxiety, depression, medical social support, and hope have the potential to effectively enhance sleep quality.

Sleep quality, social rhythms, and depression among people living with HIV: a path analysis based on social zeitgeber theory.

People living with HIV frequently report sleep disturbances. The social zeitgeber theory, which proposes that stressful life events can interfere with sleep and even depression by destabilizing daily routines, provides new insights into identifying predictors of sleep disturbances and improving sleep in people living with HIV. To explain the pathways affecting sleep quality in people living with HIV based on social zeitgeber theory. A cross-sectional study was conducted to assess sleep quality, social rhythms, depression, social support, and coping styles from December 2020 to February 2021. The hypothetical model was tested and respecified by performing path analysis and a bias-corrected bootstrapping method using IBM AMOS 24 software. The report of this study followed the STROBE checklist. A total of 737 people living with HIV participated in the study. The final model presented a good fit (goodness of fit = 0.999, adjusted goodness of fit index = 0.984, normed fit index = 0.996, comparative fit index = 0.998, Tucker-Lewis index = 0.988, root mean square error of approximation = 0.030, chi-squared/degree of freedom = 1.646), explaining 32.3% of the variance in sleep quality among people living with HIV. Lower social rhythm stability was directly associated with poorer sleep quality, and depression mediated the relationship between social rhythms and sleep quality. Social support and coping styles affected sleep quality through social rhythms and depression. The cross-sectional study design precludes making assumptions about causality among factors. This study validates and extends the applicability of the social zeitgeber theory in the HIV context. Social rhythms have direct and indirect effects on sleep. Social rhythms, sleep, and depression is not simply linked in a cascading sequence but is theoretically linked in a complex way. More studies are needed to explore the predictors of social rhythms, and interventions for stabilizing social rhythms have the potential to alleviate sleep disturbances and depression in people living with HIV.

Does self-compassion explain variance in sleep quality in women experiencing hot flushes?

ObjectivesWith poor sleep highly prevalent during the menopause transition, there is a need to better understand modifiable psychological resources that may be associated with improved sleep. Hence, we investigated whether self-compassion can explain variance in self-reported sleep quality in midlife women, over and above vasomotor symptoms. MethodsThis cross-sectional study (N = 274) used questionnaire data from self-report measures of sleep, hot flushes and night sweats, hot flush interference, and self-compassion, with analyses conducted using sequential (hierarchical) regression. ResultsPoor sleep, as measured by the Pittsburgh Sleep Quality Index, was prevalent and significantly worse in the subsample of women with hot flushes and night sweats, g = 0.28, 95 % CI [0.04, 0.53]. The interference of hot flushes in everyday life (β = 0.35, p < .01), but not their frequency, predicted self-reported sleep quality. Once self-compassion was added to the model it was the only predictor of poor sleep (β = −0.32, p < .01). When positive self-compassion and self-coldness were considered separately, the effect on sleep quality appeared to be attributable to self-coldness scores alone (β = 0.29, p < .05). ConclusionsSelf-compassion may have a stronger relationship with self-reported sleep quality in midlife women than vasomotor symptoms. Future intervention-based research could test the efficacy of self-compassion training for midlife women experiencing sleep disturbances, as this may be an important and modifiable psychological resilience factor.

A theoretical model of college students' sleep quality and health-related quality of life.

Poor sleep confers significant morbidities and is highly prevalent among college students in the United States. This research assessed sleep quality and its association with health-related quality of life (HRQOL). Further, because sleep quality research often lacks a theoretical foundation, we applied atheoretical model using selected constructs from the Theory of Planned Behavior (TPB) and Health Belief Model (HBM). A random, stratified sample of undergraduate students participated in an online survey (N = 494). Structural equation modeling assessed the association between theoretical constructs, sleep quality, and HRQOL. The final model fit was acceptable, with ~ 20% of the variance in sleep quality explained by the theoretical constructs and control variables. HBM constructs were indirectly and negatively related to sleep quality, mediated through behavioral intention, and also positively and directly associated with behavioral intention. Behavioral intention was strongly and negatively associated with sleep quality. Approximately 31% of the variance in HRQOL was explained by poor sleep quality, behavioral intention, and gender. Poor sleep was most strongly associated with reduced HRQOL. HBM constructs and behavioral intention from TPB were significantly associated with poor sleep quality, and poor sleep was significantly related to poor HRQOL.

Risk Perception, Perception of Collective Efficacy and Sleep Quality in Chinese Adults during COVID-19 Pandemic in Hong Kong: A Cross-Sectional Study.

Background: Only a few studies have studied the link between risk perception and sleep in the context of the COVID-19 pandemic. The purpose of our study is to propose and test a theoretical model to understand the relationships between COVID-19 risk appraisals—risk perception and perception of collective coordinated defense (PCCD) in particular—and subjective sleep quality in Chinese adults in Hong Kong during the COVID-19 pandemic. COVID-19-related fear and rumination were examined as potential mediators of the relationships. Methods: Data were collected using a self-report online questionnaire from a convenience sample of 224 Chinese adults during the fourth wave of the COVID-19 pandemic in Hong Kong. Results: Risk perception and PCCD were found to predict poor sleep quality. Mediation analysis showed that both fear and rumination mediated the relationship between risk perception and sleep quality, whereas only fear mediated the relationship between PCCD and sleep quality. The model was an excellent fit to the data and accounted for 44% of the variance in sleep quality in Chinese adults. This study indicated that both perception of high risks of contracting COVID-19 and anticipations of collective disease preventive efforts had adverse effects on subjective sleep quality via increasing COVID-19-related fear. Conclusions: These findings underscore the need for addressing sleep problems induced by psychological consequences of the pandemic. While policy makers often deliver public messaging campaigns that frame disease prevention as a collective goal, developing evidence-based coping strategies to combat COVID-19 adverse impacts on psychological health is equally important.

Demographic, clinical, and symptomatic correlates of subjective sleep quality in adults with multiple sclerosis

BackgroundThis study examined a comprehensive set of demographic, clinical, and symptomatic variables as correlates of subjective sleep quality in adults with multiple sclerosis (MS). MethodsParticipants with MS(N=485) completed the Pittsburgh Sleep Quality Index(PSQI), a demographics and clinical characteristics questionnaire, the Patient Determined Disease Steps Scale(PDDS), the Fatigue Severity Scale, and the Hospital Anxiety and Depression Scale. We conducted bivariate Spearman's rho (ρ) correlation analyses and multiple linear regression analysis for identifying variables associated with PSQI scores. ResultsParticipants had a mean (standard deviation) age of 55.4 (12.6) years and were mostly female (78%) with a median [interquartile range] PDDS of 2.0[3.0]. Higher levels of fatigue (ρ=0.32), more symptoms of anxiety (ρ=0.39) and depression (ρ=0.36), younger age (ρ=−0.12), lower income status (ρ=−0.13), shorter MS disease duration (ρ=−0.11), being in a minority group (ρ=0.09), and being unemployed (ρ=−0.10) were associated with worse sleep quality. There were no significant associations between gender, marital status, parental status, education level, disability status, or MS disease type and sleep quality. The overall regression model accounted for 26.3% of variance in sleep quality (F[8,229.8]=20.25) and there were significant coefficients for anxiety(β=0.25), fatigue(β=0.18), depression(β=0.16), and employment status(β=−0.12), but not disease duration, age, race, or income level. DiscussionParticipants with higher levels of anxiety, fatigue, and depression and who were unemployed reported worse sleep quality in our sample of adults with MS. These results may identify specific subgroups of the MS population that experience more sleep problems, and therefore are in greatest need for interventions designed to improve sleep impairment.

A Time to Sleep Well and Be Contented: Time Perspective, Sleep Quality, and Life Satisfaction.

A major aim of the present study was to examine the relationship between time perspective, i.e., habitual ways of relating to the past, present, and future, and sleep quality. A second aim was to test a model by which the expected negative relationship between deviation from a balanced time perspective (DBTP), a measure taking temporal biases across all three time frames into account, and life satisfaction was mediated by poor sleep quality. To these ends, a sample of young adults (N = 386) completed a version of the Zimbardo Time Perspective Inventory (S-ZTPI), Pittsburg Sleep Quality Index (PSQI), and the Satisfaction with Life Scale (SWLS). A measure of chronotype was in addition included for control purposes. Bivariate analyses revealed that the S-ZTPI subscales Past Negative, Future Negative and Present Fatalistic were associated with poorer sleep quality (higher PSQI scores), with significant associations in the opposite direction for Past Positive and Future Positive. However, DBTP was the strongest predictor of (poorer) sleep quality, suggesting that time perspective biases have an additive effect on sleep quality. Regression analyses with PSQI as the dependent variable and all six ZTPI subscales as the predictors indicated that time perspective accounted for about 20% of the variance in sleep quality (17% beyond chronotype), with Past Negative, Past Positive, and Future Negative as the unique predictors. The results additionally confirmed a strong relationship between DBTP and life satisfaction. Finally, data were consistent with the hypothesis that the association of DBTP and life satisfaction is mediated, in part, by sleep quality. Taken together, the results confirmed a substantial link between time perspective sleep-related problems, factors that may have a negative impact on life satisfaction.

Depressive symptoms and functional status are associated with sleep quality after stroke

ABSTRACT Objective: To investigate the sleep state and determine whether variables, such as age, functional status, walking capacity, fatigue, depressive symptoms, and quality of life were associated with sleep quality of individuals with chronic stroke. Methods: For this exploratory study, the dependent variable was sleep quality, which was measured by the Pittsburgh Sleep Quality Index (PSQI). Step-wise multiple linear regression analysis was employed to identify which of the independent variables, that is, age, functional status (Modified Rankin Scale-mRS), walking capacity (6-minute Walk Test), fatigue (Fatigue Severity Scale), depressive symptoms (Geriatric Depression Scale-GDS), and quality of life (EuroQol) were associated with sleep quality. Results: Ninety participants, 55 (61%) men, who had a mean age of 61 (SD 12) years and a mean time since the onset of the stroke of 58.2 (SD 58.7) months, were included. Sleep quality was significantly associated with depressive symptoms and functional status. Together, they explained 30% of the variance in the PSQI scores (p < .0001). The GDS scores alone explained 22% (F = 25.76; p < .0001) of the variance in sleep quality (PSQI). When mRS scores were included in the model, the explained variance increased to 30% (F = 20,38; p < .0001). Conclusion: Depressive symptoms and functional status, which are both potentially modifiable factors, were associated with the sleep quality of individuals with chronic stroke. It is important to consider the assessment of sleep quality in the context of stroke rehabilitation.

Sleep Quality in Autism from Adolescence to Old Age.

Background: Sleep problems are common in autism from early childhood. Although research suggests that poor sleep continues at least into early middle age, the pattern of sleep problems has rarely b...

0212 Questionnaire Assessment of Intraindividual Variability in Sleep: Inconsistent Sleep Can Be Worse Than Short Average Sleep

Abstract Introduction The consequences of short sleep are well-documented, but recent evidence indicates that night-to-night consistency in sleep may be just as important. For the current work, we developed an intraindividual variability in sleep (IIV) questionnaire to make IIV measurement possible in single-time-point studies. We investigated whether self-reported IIV explained unique variance in sleep quality and health beyond average total sleep time (TST), focusing on a critical transition period (first semester of college) in which high variability was predicted. Methods First-semester college students (N=126, Mage=18.28, 75.40% females) completed an IIV questionnaire in which participants indicated their average sleep duration, then estimated how much their sleep duration deviated from their average duration for each day of a typical week. We quantified IIV as the mean day-to-day change in sleep. Participants also completed standard questionnaires on global sleep quality, social jetlag, daytime sleepiness, depression, and stress. Results Participants reported substantial IIV in their sleep durations (M=1.77 hours, SD=0.86) that was largely distinguishable from measures of social jetlag (r=.25) and average TST (r=-.18). Patterns of IIV differed across race/ethnicities: in white/Asian students, IIV was strongly associated with social jetlag (r=-.44) whereas in underrepresented minority students, IIV and social jetlag were separate constructs (r=-.03), suggesting that fluctuations in the latter group occur across all days of the week. Greater IIV was associated with significantly worse global sleep quality (r=.24, p=.01), stress (r=.20, p=.03), and depression, r=.20, p=.03). These associations were significant after adjusting for average TST, and only marginally reduced when controlling for social jetlag. Conclusion IIV in sleep/wake patterns can be captured using a questionnaire, and such measurement provides unique explanatory power to understanding sleep quality and mental health. Future research is needed to compare IIV questionnaire data to actigraphy data and to understand the underlying mechanisms by which inconsistent sleep detrimentally affects individuals. Support National Science Foundation (NSF 1920730)

Testing the relationship between health values consistent living and health-related behavior

The present study examined whether a domain-specific measure of health values consistent living would predict engagement in health-related behaviors above and beyond measures of values consistent living in general. Participants were 111 individuals aged 18 to 49 years (M = 21.41, SD = 3.721) who attended a single assessment session to complete the Values Wheel measure of health values consistent living, and questionnaire measures of general values consistent living and engagement in health behaviors. The findings indicated that neither dietary quality nor alcohol consumption were related to health or general values consistent living. Greater levels of physical activity were associated with greater commitment to valued action in general. Lower sleep disturbance was associated with greater commitment to valued action in general and greater health values consistent living. Health values consistent living did not predict incremental variance in sleep quality over and above commitment to valued action in general. The present findings suggest that assessing abstract values alone is not sufficient to predict specific behaviors. Findings are discussed with reference to the need to improve measures of values consistent living by increasing their specificity.

Vitamin D Deficiency and Sleep Quality in Minority Pregnant Women.

To examine if vitamin D deficiency was associated with poor sleep quality in a sample of African American and Hispanic pregnant women. We also examined if race moderates the relationship between serum 25(OH)D levels and sleep quality among participants in this sample. Using a cross-sectional design, a sample of 115 African American and Hispanic pregnant women were enrolled from a federally qualified health center in the Midwest. Women completed questionnaires and had blood drawn for serum 25(OH)D levels between 24- and 32 weeks gestation. The questionnaires included demographic characteristics, the Pittsburgh Sleep Quality Index, and dietary vitamin D and calcium intake. The overall regression model indicated that the predictors explained 17% of variance in sleep quality (F(5, 103) = 4.10, p = .002, R = 0.17). Serum 25(OH)D levels were significant predictors of sleep quality after controlling for covariates (i.e., race, maternal age, prepregnancy body mass index, gestational age at data collection). Race did not moderate the association between serum 25(OH)D levels and sleep quality among women in this sample. Pregnant women should be screened for vitamin D deficiency. Women who have vitamin D deficiency should be provided vitamin D supplementation. Vitamin D supplementation may be a simple solution to enhance sleep quality at this critical time in a woman's life.

Work-Related Predictors of Sleep Quality in Chinese Nurses: Testing a Path Analysis Model.

ABSTRACTBackgroundGood sleep is essential to human health. Insufficient quality sleep may compromise the wellness of nurses and even jeopardize the safety of patients. Although the contributors of sleep quality in nurses have been previously studied, the direct and indirect effects of modifiable work-related predictors remain uncertain.PurposeThe study was designed to explore the direct and indirect effects of modifiable work-related factors on sleep quality in Chinese nurses.MethodsA multistage sampling method was employed in this cross-sectional study to recruit 923 participants. An evidence-based predicting model was postulated and then subsequently tested and optimized using path analysis.ResultsThe final model fit the data well, with the involved predictors accounting for 34.1% of the variance in sleep quality of the participants. Shift work, job demands, exposure to hazards in work environments, chronic fatigue, and inter-shift recovery were identified as direct predictors, while whereas job satisfaction, job control, support at work, and acute fatigue were identified as indirect predictors.Conclusions/Implications for PracticeSleep quality in Chinese nurses is influenced directly and indirectly by various modifiable work-related factors. Interventions such as adjusting work shifts and reducing job burdens should be prioritized by administrative staff to ensure the sleep quality and clinical performance of Chinese nurses and to subsequently improve nursing care quality.

Perceived Stress and Sleep Quality in Midlife and Later: Controlling for Genetic and Environmental Influences

ABSTRACT Objective/Background Stress is a strong predictor for poor sleep quality. However, little is known about the mechanism of this association or the respective contribution of genetic and environmental factors. This study aims to investigate general distress as a mediator and cognitive/emotional control as a moderator in the stress–sleep relationship and estimate the influence of gene and environment in this mechanism using a national representative sample. Participants 1,255 middle-aged and elderly Americans and a subset of 296 twins. Methods The Pittsburgh Sleep Quality Index, the Perceived Stress Scale, the Mood and Anxiety Symptom Questionnaire and the Self-Control Scale assessed sleep quality, perceived stress, general distress, and emotional/cognitive control. Structural equation modeling was used to test the mediating and moderating effect. ACE models on MZ and DZ twins were used to separate the contribution of genetic and environmental factors. Finally, a co-twin design was nested in the SEM to control for the genetic and familial confounds in the stress–sleep relationship. Results General distress mediated the relationship between stress and sleep while emotional/cognitive control buffered the impact of stress on general distress. 7.69% of the variance in sleep quality was explained by genetic and familial factors and 8.26% was explained by individual-specific factors. Emotional/cognitive control only moderated the individual-specific association between stress and sleep. Conclusions Gene/family factors and individual factors explained an equivalent proportion of the stress–sleep relationship. The genetic and familial association between stress and sleep is more robust, whereas the individual-specific association can be buffered by regulation strategies.

Unique Predictors of Sleep Quality in Junior Athletes: The Protective Function of Mental Resilience, and the Detrimental Impact of Sex, Worry and Perceived Stress.

Since athletic development and functioning are heavily dependent on sufficient recuperation, sleep in athletes is becoming a topic of increasing interest. Still, existing scientific evidence points to inadequate sleep in athletes, especially in females. This may be due to the fact that sleep is vulnerable to disturbances caused by stress and cognitive and emotional reactions to stress, such as worry and negative affect, which may exacerbate and prolong the stress response. Such disturbing factors are frequently experienced by junior athletes aiming for performance development and rise in the rankings, but may be damaging to athletic progression. Based on limited research in non-athletic samples, mental resilience may protect individuals against the detrimental effects of stress on sleep. Therefore, the present study aimed to investigate the extent to which sex, mental resilience, emotional (negative affect) and cognitive (worry) reactions to stress, and perceived stress, uniquely contributed to sleep quality in a cross-sectional study including 632 junior athletes. A multiple hierarchical linear regression showed that females had poorer sleep quality than males, while the mental resilience sub-components Social Resources and Structured Style were positively associated with sleep quality, providing a protective function and thus preventing sleep quality from deteriorating. Simultaneously, worry, as well as perceived stress, were negatively associated with sleep quality. Together, the independent variables explained 28% of the variance in sleep quality. A dominance analysis showed that perceived stress had the largest relative relationship with sleep quality. Based on these results, close attention should be paid to athletes’ abilities to manage worry and perceived stress, and the potential of mental resilience as a protective factor that could prevent sleep from deteriorating. The latter might be especially relevant for female athletes. Since performance margins are progressively becoming smaller and smaller, every improvement that adequate sleep can provide will be beneficial in terms of improved functioning and athletic performance.

Predictors of psychological distress and sleep quality in former family caregivers of people with dementia

Objectives: The stress-related psychological symptoms experienced by informal family caregivers do not always improve or resolve after the death of the care recipient. The purpose of this study was to explore the independent associations of sociodemographic variables, personality and coping, environmental variables, and caregiver guilt with the sleep quality and psychological distress of former family caregivers of individuals with dementia following care recipient's death.Method: A cross-sectional, correlational study was conducted with a sample of 171 former family caregivers of people with dementia. Participants completed an online survey comprised of six instruments and demographic items. Caregiver personal variables (e.g. personality and coping), environmental variables, guilt, psychological distress (depressive and anxiety symptoms), and sleep quality were evaluated using psychometrically validated measures.Results: In bivariate analysis, post-caregiving guilt was significantly associated with depressive and anxiety symptoms (p < 0.01). After controlling for covariates, dysfunctional coping and neuroticism explained 32% of the variance in depressive symptoms (R2 = .52, ΔR2 = .32, F(5, 165) = 36.24, p < .001) and 24% of the variance in anxiety symptoms (R2 = .41, ΔR2 = .24, F(5, 165) = 22.65, p < .001), while dysfunctional coping, pre-loss depression, and extraversion accounted for 16% of the variance in sleep quality (R2 = .30, ΔR2 = .16, F(6, 164) = 11.44, p < .001).Conclusion: This study demonstrates the critical role of personal variables, including personality traits, coping strategies, and pre-loss depression, in explaining psychological distress and sleep quality in this sample of former dementia caregivers.