Sleep Quality, Well-Being and Mental Health among Adults

Objective: Although college students are at heightened risk for sleep disturbances, healthy sleep is associated with positive physical, cognitive, psychological, and academic benefits for this group. The goals of the current study were to (1) describe sleep health in an undergraduate college sample and (2) examine the role of a class activity using self-determination theory to promote better sleep health in this group. Methods: A cohort study was conducted using data drawn from class activities conducted in two undergraduate Introduction to Psychology courses. Students were undergraduates at a mid-Atlantic public university in the United States. Total sample size was N = 224 (intervention class [n = 98], and the control class [n = 127]). Both the intervention and control classes completed the RU SATED sleep health questionnaire at the beginning and the end of the semester. The intervention class also completed a self-determination activity focused on sleep health mid-semester. Both the RU SATED questionnaires and the self-determination activities were completed via in-class responder technology. Data were de-identified and downloaded from the responder technology at the end of the semester. Mixed methods were used for data analysis including quantitative analyses and a qualitative approach using a phenomenological, inductive, and reflexive qualitative method whereby themes were allowed to emerge from the data. Results: Overall, almost 25% of the students reported never or rarely obtaining healthy sleep on average. The majority (76%) said they sometimes have healthy sleep and no students reported usually or always obtaining healthy sleep. The components of sleep health the entire sample scored highest on were timing (sleeping between 2 and 4 AM), sleep duration (between 7 and 9 h), and staying awake during the day. The areas they scored the lowest on were maintaining regular bed and wake times, spending less than 30 min awake at night, and feeling satisfied with their sleep. Qualitatively, the most frequently obtained sleep health behaviors of the intervention class were rhythmicity, prioritizing sleep, timing of sleep, and tech hygiene. The intervention class had significantly better sleep health across the entire semester and significantly better daytime alertness post-intervention. The most commonly chosen sleep health behaviors to change were sleep hygiene, tech hygiene, and stimulus control. Conclusion: We examined the classroom environment as a venue for promoting sleep health among college students. Given the popularity of Introduction to Psychology courses, this class is a promising avenue to deliver sleep health promotions to a large number of students. The implementation of a self-determination framework, as part of sleep health promotion, shows potential for creating a person-centered, strengths-based approach to health behavior change within this population. Full article

The objective was to examine insomnia and insomnia-related care within a regional network of Department of Veterans Affairs (VA) facilities since the VA roll-out of cognitive behavioral therapy for insomnia (CBT-I) in 2011. A retrospective analysis of VA electronic health records (EHR) data from 2011 to 2019 was conducted. The annual and overall prevalence of four insomnia indicators was measured: diagnoses, medications, consultations for assessment/treatment, and participation in CBT-I. Also examined were sociodemographic and clinical differences among veterans with and without an insomnia indicator, as well as differences among the four individual insomnia indicators. The sample included 439,887 veterans, with 17% identified by one of the four indicators; medications was most common (15%), followed by diagnoses (6%), consults (1.5%), and CBT-I (0.6%). Trends over time included increasing yearly rates for diagnoses, consults, and CBT-I, and decreasing rates for medications. Significant differences were identified between the sociodemographic and clinical variables across indicators. An evaluation of a large sample of veterans identified that prescription sleep medications remain the best way to identify veterans with insomnia. Furthermore, insomnia continues to be under-diagnosed, per VA EHR data, which may have implications for treatment consistent with clinical practice guidelines and may negatively impact veteran health. Full article

Objective: Perfectionism is consistently identified as a predisposing and perpetuating factor for a wide range of mental health conditions and disorders. Given the unique cognitive, emotional, and physiological characteristics associated with perfectionism, perfection could have serious implications for a critical health behavior—our sleep. The current study examines the links between perfectionism and sleep health with the goal of identifying potential sleep-related beliefs as underlying mechanisms. Methods: Participants were 417 undergraduate students at a large, public university in the mid-Atlantic United States. Participants completed a one-time online survey with the Almost Perfect Scale-Revised, the Dysfunctional Beliefs about Sleep Scale, Perceived Competence Scale about their sleep, and the RU SATED sleep health scale. Results: A two-step structural equation modeling strategy was used. Greater perfectionism discrepancies predicted greater dysfunctional beliefs about sleep ($\beta$ = 0.45) and worse perceived sleep competence ($\beta$ = −0.33). Moreover, greater dysfunctional beliefs and worse perceived sleep competence predicted worse sleep health ($\beta$ = −0.23 and 0.59, respectively). Dysfunctional beliefs and perceived sleep competence significantly mediated the effect of maladaptive perfectionism on sleep health ($\beta$ = −0.302). Discussion: Dysfunctional beliefs and sleep competence emerged as mechanisms through which maladaptive perfectionism may function as a barrier to healthy sleep. Although prior research positions perfectionism as a primary correlate of poor sleep, the current study identifies the role of beliefs about sleep as the pathway from perfectionism to poorer sleep health. The results highlight the importance of addressing both maladaptive beliefs about sleep as well as beliefs about one’s own sleep competency with undergraduate students with higher maladaptive perfectionism. Full article

Sleep health, operationalized as a multidimensional construct consisting of sleep regularity, satisfaction, alertness, timing, efficiency, and duration, is an emerging concept in the field of sleep medicine which warrants further investigation. The purpose of the present study was to: (1) compare sleep health across the lifespan, (2) determine lifestyle factors associated with sleep health, and (3) examine whether lifestyle factors associated with sleep health varied between and within age groups. Participants consisted of 3284 individuals (Mean age = 42.70; 45% male) who participated in a cross-sectional online survey of sleep and health. Sleep health was measured using the RU-SATED scale, while demographic and lifestyle factors (e.g., daily social media use, sedentary activity, fast food consumption, etc.) were all self-reported. Sleep health was the highest among older adults (M = 8.09) followed by middle-aged (M = 7.65) and younger adults (M = 7.16). Across age groups, fast-food consumption, daily regularity, and daily TV, social media, or internet use were all negatively correlated with sleep health (ps < 0.05). Few differences in the association between lifestyle factors and sleep health across age groups were found. Overall, these findings may help to inform sleep health promotion efforts by targeting the most pertinent lifestyle factors for promoting sleep health. Full article

While the COVID-19 has dramatically altered our lifestyle and sleep practices, the links between sleep, individual characteristics, personal experiences and mental health during the pandemic require further examination. This cross-sectional, multi-methods study examined differences in language used to describe personal experiences, and mental health, based on sleep quality during the early stages of the pandemic. N = 1745 participants (mean age 42.97 ± 14.46 years) from 63 countries responded to the survey. Sleep quality was assessed using the Pittsburgh Sleep Quality Index and mental health was examined using the Patient Health Questionnaire-9, the State Trait Anxiety Inventory, the Perceived Stress Scale and the UCLA-Loneliness Scale. Quantitative analysis of qualitative, language content of personal experiences was conducted using free-text responses and comments to a question on the survey. Almost 50% of the participants reported poor sleep quality, which was linked to a more negative emotional tone and greater mentions of money or finance related words. Good sleepers reported more positive emotional tone in their experiences. Greater reports of clinical state anxiety, moderate depression and moderate stress were observed in poor sleepers, even after accounting for demographics and pandemic-related factors such as loneliness, financial concerns and risk of contracting COVID-19 disease. Results from this study highlight an urgent need for sleep-related public health interventions. Practitioner education, sleep screening for those with mental health conditions, and encouraging people to adopt digital tools may help to reduce the burden of poor sleep on mental health. While the pandemic itself is a stressful and uncertain time, improving sleep can support positive emotion regulation, improving mood and consequential action. Full article

Sleep valuation, the worth individuals place on sleep, is an understudied construct in the field of sleep medicine. This study introduced a Sleep Valuation Item Bank and explored how sleep valuation is related to sleep health and daytime functioning within a sample of college students. The participants in this study were 247 (85% white, 83% female) undergraduate students who completed an online survey that included questions from a Sleep Valuation Item Bank and questions about sleep and daytime functioning. Correlation and regression analyses were conducted to determine associations between sleep valuation, aspects of sleep health and daytime functioning. Mediation analyses were conducted to determine whether the sleep health variables explained the associations between sleep valuation and daytime functioning. In correlation analyses, sleep valuation was negatively associated with sleepiness and sleep quality. It was also associated with daytime functioning, including general mental and physical health, depression, and anxiety. In the regression analyses, daytime impairments including poorer physical and mental health, anxiety, and depression were associated with higher sleep valuation. Poorer sleep health, including greater sleepiness and lower sleep quality, explained these associations and were associated with higher sleep valuation. Thus, while daytime impairments, such as anxiety and depression, are related to sleep valuation, this relationship may be due in part to the sleep disturbance that often co-occurs with these impairments. Full article

Studies have explored how vitamin B12 status affects sleep among elders and children, but this remains to be investigated among young adults. We used the Pittsburgh Sleep Quality Index (PSQI) to assess the association between serum vitamin B12 and sleep among female college students in Saudi Arabia. In this cross-sectional study, we enrolled 355 participants (age (years), 20.7 ± 1.5; body mass index, 23.6 kg/m² ± 5.2) at King Saud University, Riyadh, Saudi Arabia. Fasting blood samples were analyzed regarding the serum vitamin B12 and blood lipids. Anthropometric, socio-demographic, clinical history, stress, physical activity, and dietary data were collected. We assessed the sleep statuses of the participants using the PSQI. Around 72% of the participants were “poor” sleepers (PSQI > 5). Subgroup analysis within the tertiles showed that participants with higher vitamin B12 in the second and third tertiles reported better scores for sleep quality (B ± SE = −12.7 ± 5.6, p = 0.03; B ± SE = −32.7 ± 16.4, p = 0.05, respectively) and also reported a lower use of sleep medication (B ± SE = −21.2 ± 9.9, p = 0.03, in the second tertile only), after adjusting for the waist–hip ratio and stress. However, sleep was not found to be directly associated with either serum vitamin B12 or dietary vitamin B12. In conclusion, the serum vitamin B12 results show that the participants with higher vitamin B12 in the second and third tertiles reported better scores on the sleep quality scale and a lower use of sleep medication. However, no such associations were observed with the overall PSQI. More studies with larger sample sizes are needed to establish a direct relationship between sleep and vitamin B12. Full article

Poor sleep quality lessens general health quality and is related to physical and mental problems. Moreover, fatigue is one of the foremost common complaints in medical care and plays a role in the decreasing quality of life of the older population. For these reasons, the objective of this study was to examine the effect of high- and moderate-intensity interval training programs (HIIT vs. MIIT)—both consisting of twelve weeks of TRX training—on the sleep quality and fatigue levels of the elderly. A randomized controlled clinical trial (NCT03404830) was conducted. A total of 82 subjects were randomized to either a HIIT group (n = 28) that performed a main squat activity with a suspension system, comprising four four-minute intervals between 90–95% of the maximum heart rate (HR), an MIIT group (n = 27) with an intensity of 70% of the maximum HR, and a control group (CG) (n = 27) that continued their daily lifestyle. The two exercise groups trained twice a week for 12 weeks, with each session lasting 45 min. Sleep quality was measured using the Pittsburgh sleep quality index (PSQI), and fatigue was assessed using the fatigue severity scale (FSS). Outcomes were measured before the intervention and after the intervention period. Post-intervention sleep quality measurements revealed a statistically significant interaction regarding group × time (p < 0.005) and fatigue (p = 0.002). Specifically, fatigue decreased in the HIIT group between both measurement moments (p = 0.003). In addition, differences were obtained in the post-intervention measure between the HIIT and MIIT groups (p = 0.013) and HIIT and control (p = 0.029). Our analysis indicates that a population of the elderly showed improvements in sleep quality and fatigue after performing a high-intensity intervention using suspension training (TRX), with markedly better results in the HIIT group. Full article

This study explored the divergence in population-level estimates of insufficient sleep (<6 h) by examining the explanatory role of race/ethnicity and contrasting values derived from logistic and Poisson regression modeling techniques. We utilized National Health and Nutrition Examination Survey data to test our hypotheses among 20–85 year-old non-Hispanic Black and non-Hispanic White adults. We estimated the odds ratios using the transformed logistic regression and Poisson regression with robust variance relative risk and 95% confidence intervals (CI) of insufficient sleep. Comparing non-Hispanic White (10176) with non-Hispanic Black (4888) adults (mean age: 50.61 ± 18.03 years, female: 50.8%), we observed that the proportion of insufficient sleepers among non-Hispanic Blacks (19.2–26.1%) was higher than among non-Hispanic Whites (8.9–13.7%) across all age groupings. The converted estimated relative risk ranged from 2.12 (95% CI: 1.59, 2.84) to 2.59 (95% CI: 1.92, 3.50), while the estimated relative risks derived directly from Poisson regression analysis ranged from 1.84 (95% CI: 1.49, 2.26) to 2.12 (95% CI: 1.64, 2.73). All analyses indicated a higher risk of insufficient sleep among non-Hispanic Blacks. However, the estimates derived from logistic regression modeling were considerably higher, suggesting the direct estimates of relative risk ascertained from Poisson regression modeling may be a preferred method for estimating population-level risk of insufficient sleep. Full article

Individuals with mild cognitive impairment (MCI) are at high risk for dementia development. Sleep disturbance is often overlooked in MCI, although it is an important risk factor of cognitive decline. In the absence of a cure for dementia, managing the risk factors of cognitive decline in MCI is likely to delay disease progression. To develop interventions for sleep disturbance in MCI, its related factors should be explored. This study aimed to identify and compare the correlates of sleep disturbance in older adults with MCI and those in cognitively healthy older adults. A comparative cross-sectional study was adopted. Data were obtained from 219 Chinese community-dwelling older adults (female: 70.3%), which consisted of 127 older adults with MCI and 92 age-matched cognitively healthy controls. The candidate correlates of sleep disturbance included socio-demographic correlates, health-related factors, lifestyle-related factors and psychological factor. Descriptive, correlational and regression statistics were used for data analysis. The prevalence of sleep disturbance in MCI was 70.1% compared to that of 56.5% in cognitively healthy controls (p < 0.001). The multivariate analysis indicated that, in participants with MCI, depressive symptoms (Beta = 0.297, p = 0.001), comorbidity burden (Beta = 0.215, p = 0.012) and physical activity (Beta = −0.297, p = 0.001) were associated with sleep disturbance. However, in the cognitively healthy controls, only depressive symptoms (Beta = 0.264, p = 0.028) and comorbidity burden (Beta = 0.361, p = 0.002) were associated with sleep disturbance. This finding highlights that sleep disturbance is sufficiently prominent to warrant evaluation and management in older adults with MCI. Furthermore, the findings elucidate several important areas to target in interventions aimed at promoting sleep in individuals with MCI. Full article