Comparing patients treated with CBT for insomnia with healthy sleepers and sleepers with past insomnia on dimensions of sleep health.

OBJECTIVES: To compare patients treated with cognitive behavioral therapy for insomnia (CBT-I) with healthy sleepers and individuals with past but not current insomnia on multidimensional sleep health. METHODS: The study evaluates CBT-I on six dimensions of sleep health (regularity, satisfaction, alertness, timing, efficiency, duration) in a sample of individuals with insomnia compared to two other unique sleep samples. Participants were in one of three groups: insomnia (CUR, n = 299), healthy sleeper (HS, n = 122), or past insomnia (PAST, n = 35). Daily diaries and validated measures were employed to capture six dimensions of sleep health. The CUR group received four 60-minute sessions of CBT-I every 2weeks, and sleep health indices were measured at baseline and post-treatment. The HS and PAST groups were measured only at baseline. RESULTS: Results of the pairwise t tests indicated improvements in sleep satisfaction, alertness (fatigue but not sleepiness), timing, efficiency, and duration (Cohen's d=0.22 to 1.55). ANCOVA models revealed significant differences in sleep health scores between treated insomnia patients and the other two sleep groups. Treated patients demonstrated less bedtime and risetime variability, in addition to lower napping duration. Overall, the study observed significant changes in various domains of sleep health after four sessions of cognitive behavioral therapy for insomnia; however, differences remain when compared to the other groups in the study. CONCLUSION: There may be ongoing sleep vulnerability in patients treated with cognitive behavioral therapy for insomnia though future inclusion of a control group would increase internal validity. Borrowing from transdiagnostic sleep modules may be helpful to support remaining deficits after cognitive behavioral therapy for insomnia.

Association between sleep health and intrinsic capacity among older adults in Taiwan.

Although the association between poor sleep quality and frailty has been previously reported, the relationship between sleep health and intrinsic capacity (IC) remains largely unknown. We aimed to examine the association between sleep health and IC among older adults. This was a cross-sectional study, and 1268 eligible participants completed a questionnaire collecting information on demographic, socioeconomic, lifestyle, sleep health, and IC. Sleep health was measured by the RU-SATED V2.0 scale. High, moderate, and low levels of IC were defined using the Integrated Care for Older People Screening Tool for Taiwanese. The ordinal logistic regression model estimated the odds ratio and corresponding 95% confidence interval. Low IC was significantly associated with age of 80 years or above, female, currently unmarried, uneducated, currently not working, financially dependent, and having emotional disorders. A one-point increase in sleep health was significantly associated with a 9% reduction in the odds of poor IC. An increase in daytime alertness was related to the greatest reduction in poor IC (aOR, 0.64; 95% CI, 0.52-0.79). In addition, the subitems sleep regularity (aOR, 0.77; 95% CI, 0.60-0.99), sleep timing (aOR, 0.80; 95% CI, 0.65-0.99), and sleep duration (aOR, 0.77; 95% CI, 0.61-0.96) were associated with a reduced OR of poor IC but with marginal statistical significance. Our findings showed that sleep health across multiple dimensions is related to IC, particularly daytime alertness in older adults. We suggest developing interventions to improve sleep health and prevent IC decline, which is crucial in causing poor health outcomes.

Six multidimensional sleep health facets in older adults identified with factor analysis of actigraphy: Results from the Einstein Aging Study.

OBJECTIVES: The concept of multi-dimensional sleep health, originally based on self-report, was recently extended to actigraphy in older adults, yielding five components, but without a hypothesized rhythmicity factor. The current study extends prior work using a sample of older adults with a longer period of actigraphy follow-up, which may facilitate observation of the rhythmicity factor. METHODS: Wrist actigraphy measures of participants (N = 289, Mage = 77.2 years, 67% females; 47% White, 40% Black, 13% Hispanic/Others) over 2 weeks were used in exploratory factor analysis to determine factor structures, followed by confirmatory factor analysis on a different subsample. The utility of this approach was demonstrated by associations with global cognitive performance (Montreal Cognitive Assessment). RESULTS: Exploratory factor analysis identified six factors: Regularity: standard deviations of four sleep measures: midpoint, sleep onset time, night total sleep time (TST), and 24-hour TST; Alertness/Sleepiness (daytime): amplitude, napping (mins and #/day); Timing: sleep onset, midpoint, wake-time (of nighttime sleep); up-mesor, acrophase, down-mesor; Efficiency: sleep maintenance efficiency, wake after sleep onset; Duration: night rest interval(s), night TST, 24-hour rest interval(s), 24-hour TST; Rhythmicity (pattern across days): mesor, alpha, and minimum. Greater sleep efficiency was associated with better Montreal Cognitive Assessment performance (ß [95% confidence interval] = 0.63 [0.19, 1.08]). CONCLUSIONS: Actigraphic records over 2 weeks revealed that Rhythmicity may be an independent factor in sleep health. Facets of sleep health can facilitate dimension reduction, be considered predictors of health outcomes, and be potential targets for sleep interventions.

The RU_SATED as a measure of sleep health: cross-cultural adaptation and validation in Chinese healthcare students.

BACKGROUND: The RU_SATED scale is a multidimensional instrument measuring sleep health, consisting of Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration dimensions. We adapted and validated the Chinese RU_SATED (RU_SATED-C) scale. METHODS: The RU_SATED-C scale was developed through a formal linguistic validation process and was validated in an observational longitudinal survey design. Healthcare students completed the RU_SATED scale, Sleep Quality Questionnaire, and Patient Health Questionnaire-4 among two sites of Hangzhou and Ningbo, China. Psychometric assessments included structural validity, longitudinal measurement invariance, convergent and divergent validity, internal consistency, and test-retest reliability. RESULTS: A total of 911 healthcare students completed the RU_SATED-C scale at baseline (Time 1, T1) and follow-up (Time 2, T2) with an average time interval of 7 days + 5.37 h. Confirmatory factor analysis (CFA) confirmed a single-factor model and resulted in an acceptable model fit. The two-factor model previously found in the Japanese version fit better than the one-factor model, whereas the one-factor model fit had a better fit than the two-factor model found in the English version. Longitudinal CFA resulted in negligible changes in fit indices for four forms of increasingly restrictive models and supported that a single-factor model was equivalent over time. The data also endorsed longitudinal measurement invariance among the two-factor models found in the English and Japanese samples. The RU_SATED-C scale total score displayed a moderately strong negative correlation with sleep quality; however, negligible associations were observed with anxiety and depression. Ordinal Cronbach's alpha and Ordinal McDonald's omega at T1 and T2 ranged from suboptimal to acceptable. The RU_SATED-C scale and all items were significantly correlated across time intervals. CONCLUSION: The RU_SATED-C scale is an easy-to-use instrument with potentially valid data for the measurement of multidimensional sleep health. Use of the RU_SATED-C scale can help raise awareness of sleep health and could pave the way for important efforts to promote healthy sleep.

The association between different sleep health dimensions and sex, age, education, circadian preference, and chronic insomnia: a representative population-based study.

Objectives: The aims were to explore multidimensional sleep health and the different dimensions of sleep health in the adult Norwegian population in relation to sex, age, education, circadian preference, and chronic insomnia. Methods: A representative sample of 1028 Norwegians, aged 18 + years completed a cross-sectional web-based survey. Sleep health was measured with the multidimensional RU_SATED scale, which assesses the dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration. Insomnia was assessed with the Bergen Insomnia Scale. Data were analyzed with chi-square tests, t-tests, one-way ANOVAs, and regression analyses, as appropriate. Response rate was 33.5%. Results: Sleep health was better in males, with increasing age, and with higher educational level, and was poorer in participants with evening preference and chronic insomnia, compared to their respective counterparts. When investigating the different sleep health dimensions, males scored better than females on satisfaction (adjusted odds ratio [aOR] = 0.69, 95% CI = 0.51 to 0.93), timing (aOR = 0.66, 95% CI = 0.49 to 0.88), and efficiency (aOR = 0.68, 95% CI = 0.52 to 0.89). Older age was associated with better scores on regularity and satisfaction, whereas young age was associated with better scores on alertness and duration. High educational level was associated with better scores on alertness, timing, and duration. Evening types scored worse than morning types on regularity (aOR = 0.27, 95% CI = 0.18 to 0.41), satisfaction (aOR = 0.37, 95% CI = 0.26 to 0.53), and timing (aOR = 0.36, 95% CI = 0.26 to 0.51). Participants with chronic insomnia scored worse than participants without insomnia on all six sleep health dimensions. Conclusions: Sleep health differed significantly in relation to sex, age, education, circadian preference, and chronic insomnia. However, specific group differences were not equally evident in all sleep health dimensions.

The validity and reliability of the Japanese version of RU-SATED.

OBJECTIVE: We developed a Japanese version of RU-SATED (RU-SATED-J), a simple self-rated scale for measurement of multidimensional sleep health, and examined its reliability and psychometric validity. METHOD: The RU-SATED-J was developed by a rigorous reverse translation process. It consists of six questions, each with three Likert-type response options. The total score (range 0-12) was calculated by summing the item scores. Psychometric characteristics were tested in an observational cross-sectional study involving factory workers in Japan (n = 177, mean age 42.8 ± 11.6 years, range 19-65 years). The distribution and reliability of the scale scores were examined in terms of Cronbach's alpha coefficient. The convergent and divergent validity of the scale score were assessed by examining the correlations of various factors with the Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS). RESULTS: The distribution of scores was left-skewed, with a mean of 8.21 ± 2.72 points, and range of 0-12. The internal reliability of the scale was α = 0.758. The total score showed a significant negative correlation with the ISS (rs = -0.542, P < 0.001) and the ESS (rs = -0.178, P = 0.018). Exploratory factor analysis (EFA) demonstrated a two-factor structure. Confirmatory factor analysis (CFA) showed that the goodness of fit of the higher-order factor model had a Root Mean Square Error of Approximation (RMSEA) of <0.001 and a Comparative Fit Index (CFI) of 1.00, confirming its factorial validity. CONCLUSION: The RU-SATED is a promising new instrument for measuring multi-dimensional sleep health perception among Japanese adults. Further general population studies using this Japanese version of the questionnaire should be considered.

Multidimensional sleep health domains in older men and women: an actigraphy factor analysis.

The multidimensional sleep health framework emphasizes that sleep can be characterized across several domains, with implications for developing novel sleep treatments and improved prediction and health screening. However, empirical evidence regarding the domains and representative measures that exist in actigraphy-assessed sleep is lacking. We aimed to establish these domains and representative measures in older adults by examining the factor structure of 28 actigraphy-derived sleep measures from 2,841 older men from the Osteoporotic Fractures in Men Sleep Study and, separately, from 2,719 older women from the Study of Osteoporotic Fractures. Measures included means and standard deviations of actigraphy summary measures and estimates from extended cosine models of the raw actigraphy data. Exploratory factor analyses revealed the same five factors in both sexes: Timing (e.g. mean midpoint from sleep onset to wake-up), Efficiency (e.g. mean sleep efficiency), Duration (e.g. mean minutes from sleep onset to wake-up), Sleepiness/Wakefulness (e.g. mean minutes napping and amplitude of rhythm), and Regularity (e.g. standard deviation of the midpoint). Within each sex, confirmatory factor analyses confirmed the one-factor structure of each factor and the entire five-factor structure (Comparative Fit Index and Tucker-Lewis Index ≥ 0.95; Root Mean Square Error of Approximation 0.08-0.38). Correlation magnitudes among factors ranged from 0.01 to 0.34. These findings demonstrate the validity of conceptualizing actigraphy sleep as multidimensional, provide a framework for selecting sleep health domains and representative measures, and suggest targets for behavioral interventions. Similar analyses should be performed with additional measures of rhythmicity, other age ranges, and more racially/ethnically diverse samples.

Examining and Promoting Sleep Health in the Undergraduate Classroom: A Mixed-Methods Approach.

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.