Predicting the Persistence of Insomnia Symptoms during the COVID-19 Pandemic.

OBJECTIVE: The goal of this study is to evaluate the factors associated with vulnerability and course of insomnia longitudinally in the COVID-19 pandemic and examine differences between: (a) those who never demonstrated clinical insomnia symptoms, (b) those who demonstrated clinically elevated insomnia symptoms at 1 or 2 time points, and (c) those who demonstrated clinically elevated insomnia symptoms at all 3 time points. METHODS: Participants (≥18 years old) completed measures of insomnia (ISI), depression (PHQ-8), anxiety (GAD-7), and pre-sleep arousal (PSAS) at 3 time points (baseline, 1 month, and 3 months). Data were analyzed using univariable odds ratios and multivariable multicategory logistic regression to determine demographic, psychological, and behavioral predictors of insomnia persistence. RESULTS: A total of 129 participants completed all 3 assessments (70 female, age M = 44 years, SD = 16). We found that 40% (N = 51) never had insomnia symptoms, 33% (N = 42) reported transient insomnia symptoms (1 or 2 time points), and 28% (N = 36) reported persistent insomnia symptoms (all 3 time points). From the multivariable multicategory logistic analyses, pre-sleep arousal, gender, and income were significant predictors of insomnia persistence. CONCLUSIONS: Findings indicate elevated insomnia symptoms were persistent in a substantial number of individuals throughout the pandemic. Results suggest additional insomnia and psychological interventions are needed to improve sleep and mental health.

Sleep Technology Intervention to Target Cardiometabolic Health (STITCH): a randomized controlled study of a behavioral sleep extension intervention compared to an education control to improve sleep duration, blood pressure, and cardiometabolic health among adults with elevated blood pressure/hypertension.

BACKGROUND: Short sleep duration, defined as < 7 h sleep on weeknights, affects 40% of the US adult population, contributing to the increased risk for cardiometabolic diseases, decreased safety, and poorer mental health. Despite the prevalence of short sleep duration, few studies have tested interventions to extend sleep duration. The objective of this study is to test the effects of a behavioral sleep extension intervention on sleep duration, blood pressure, and other measures of cardiometabolic health among adults with elevated blood pressure or hypertension. METHODS: This is a single-blind, randomized controlled trial to determine the impact of a behavioral sleep extension intervention on sleep duration and cardiometabolic health among individuals with short sleep duration (< 7 h per night) and elevated blood pressure or hypertension (SBP 120-150 mmHg or DBP 80-90 mmHg). After completing the screening, participants will be randomly assigned to either a sleep coaching (intervention) or health education (control) group. The participants will have weekly contact for either coaching or education for 8 weeks (intervention period) followed by monthly coaching or education for the next 2 months (maintenance period). Participants will complete assessment visits, actigraphy, and 24-h ambulatory blood pressure recording at baseline/screening, 8 weeks, and 6 and 12 months. The primary outcome is sleep duration at 8 weeks, and the secondary outcome is blood pressure at 8 weeks. DISCUSSION: The results of this study will determine the effects of behavioral sleep extension on sleep and cardiometabolic health among adults with short sleep duration and elevated BP/hypertension. The results will inform the feasibility and efficacy of behavioral sleep extension and provide information needed for future multi-site effectiveness studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04766424. Registered on 21 February 2021.

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study.

OBJECTIVE: Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D. METHODS: Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters. RESULTS: Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]). CONCLUSION: Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research. DATA AVAILABILITY STATEMENT: Data are available upon a reasonable request to the corresponding author.

The thief of (bed)time: Examination of the daily associations between bedtime procrastination and multidimensional sleep health.

OBJECTIVES: Sleep insufficiency is associated with increased risk of morbidity and mortality. Bedtime procrastination, or the needless and voluntary delay in sleep, is a sleep-related behavior which may interfere with sleep health. The objective of this study is to comprehensively examine the daily associations among bedtime procrastination and measures of sleep regularity, satisfaction, timing, efficiency, and duration. METHODS: Two hundred and eighty young adult participants (79% female; Mage=24.4) completed daily sleep diaries and measures of bedtime procrastination and sleep restoration over 14days, in addition to measures of chronotype. Multilevel models were constructed to examine the associations between bedtime procrastination and sleep health. RESULTS: Greater bedtime procrastination was associated with poorer sleep health, including poorer self-reported sleep restoration, later sleep timing, less efficient sleep, and shorter sleep duration. These associations were significant at both within- and between-person levels, and persisted after statistically adjusting for individuals' chronotypes. CONCLUSIONS: This study offers bedtime procrastination as a putative mechanism for poor sleep health and finds that the associated risk of poor sleep from bedtime procrastination is independent of chronotype. Results presented here suggest that bedtime procrastination may be a relevant behavior in the development or maintenance of sleep and sleep-related disorders.

A daily examination of executive functioning and chronotype in bedtime procrastination.

STUDY OBJECTIVES: Bedtime procrastination, or delays in bedtime not attributable to external obligations, is a behavioral tendency that undermines sleep and is conceptualized as a consequence of poor self-regulation. Prior studies investigating the mechanistic role of self-regulation in bedtime procrastination relied on cross-sectional methods and self-reported self-regulation. The present study examined the association between bedtime procrastination and both objective and self-reported executive functioning (EF) as indices of self-regulation, as well as the moderating role of chronotype, using methods that examined these associations at the daily level. METHODS: A total of 273 young adult participants (78% female; Mage = 24.4) completed daily measures of objective EF (i.e., Stroop task), self-reported EF (i.e., self-reported cognitive, behavioral, and emotional regulation difficulties), and bedtime procrastination over 14 days, in addition to measures of chronotype. Multilevel models were constructed to examine the associations between bedtime procrastination and EF, as well as EF-chronotype interactions. RESULTS: Poorer daily objective EF and self-reported behavioral regulation were associated with greater same-night bedtime procrastination. Additionally, poorer subjective cognitive and emotional regulation were associated with greater average bedtime procrastination across 14 days. Later chronotypes reported greater bedtime procrastination than early chronotypes. CONCLUSIONS: The present study provides support for the association between EF and bedtime procrastination, but finds no evidence for the moderating role of chronotype in this association. Results suggest that some EF processes may be more relevant to bedtime procrastination than others. Current findings have implications for assessment and intervention for this consequential sleep-relevant behavioral tendency.

Sleep medicine provider perceptions and attitudes regarding consumer sleep technology.

STUDY OBJECTIVES: This study assessed perceptions and attitudes of sleep medicine providers regarding consumer sleep technology (CST). METHODS: A convenience sample of n = 176 practicing sleep medicine and behavioral sleep medicine experts was obtained using social media and the American Academy of Sleep Medicine directory. Providers completed a questionnaire that assessed perceptions and attitudes about patient use of CST in the clinical setting. RESULTS: The sample included both adult and pediatric psychologists, physicians, and advanced practice providers from a variety of health settings. Providers reported 36% (3%-95%) of patients used CST, and the most common devices seen by providers were wrist-worn devices followed by smartphone apps. The most common perceived patient motivations for frequent use were to measure sleep and self-discovery. Across sleep disorders, clinicians did not endorse frequent CST use; the highest reported use was for assisting patients in the completion of sleep diaries. Overall devices were rated as somewhat accurate and neutral regarding helpfulness. In qualitative responses, providers associated CST use with increased patient engagement but increased orthosomnia and misperceptions about sleep. CONCLUSIONS: CST is frequently encountered in the sleep medicine clinic, and providers view CST as somewhat accurate but neither helpful nor unhelpful in clinical practice. Although providers viewed these devices as useful to drive patient engagement/awareness and track sleep patterns, providers also viewed them as a contributor to orthosomnia and misperceptions about sleep. CITATION: Addison C, Grandner MA, Baron KG. Sleep medicine provider perceptions and attitudes regarding consumer sleep technology. J Clin Sleep Med. 2023;19(8):1457-1463.

Circadian Timing, Information processing and Metabolism (TIME) study: protocol of a longitudinal study of sleep duration, circadian alignment and cardiometabolic health among overweight adults.

BACKGROUND: Both short sleep duration and circadian rhythm misalignment are risk factors for metabolic dysfunction, but the underlying mechanisms are unknown. The goal of this study is to examine how sleep duration and circadian alignment predict changes in cardiometabolic risk factors over a 12-month period, and test cognitive function and hedonic eating tendencies as potential mechanisms. METHODS: We will recruit a sample of 120 working aged adults with BMI 25-35 kg/m2 (overweight to class I obesity). The protocol includes 5 visits over a 12-month period. Study visits include wrist actigraphy to measure sleep behaviors, 24-h diet recalls, dim light melatonin collection, a computerized neurobehavioral assessment, eating in the absence of hunger task, and frequently sampled IV glucose tolerance test. DISCUSSION: The results of the TIME study will advance the understanding of how both short sleep duration and circadian misalignment contribute to behavioral aspects of obesity and metabolic dysfunction. TRIAL REGISTRATION: ClinicalTrials.Gov, NCT04759755 , registered retrospectively February 13, 2021.

Sleep optimization to improve glycemic control in adults with type 1 diabetes: study protocol for a randomized controlled parallel intervention trial.

BACKGROUND: Despite improvements in treatment regimens and technology, less than 20% of adults with type 1 diabetes (T1D) achieve glycemic targets. Sleep is increasingly recognized as a potentially modifiable target for improving glycemic control. Diabetes distress, poor self-management behaviors, and reduced quality of life have also been linked to sleep variability and insufficient sleep duration. A significant gap of knowledge exists regarding interventions to improve sleep and the effects of sleep optimization on glycemic control in T1D. The purpose of this study is to determine the efficacy of a T1D-specific sleep optimization intervention (Sleep-Opt) on the primary outcomes of sleep variability, sleep duration, and glycemic control (A1C); other glycemic parameters (glycemic variability, time-in-range [TIR]); diabetes distress; self-management behaviors; quality of life; and other patient-reported outcomes in adults with T1D and habitual increased sleep variability or short sleep duration. METHODS: A randomized controlled parallel-arm study will be employed in 120 adults (aged 18 to 65 years) with T1D. Participants will be screened for habitual sleep variability (> 1 h/week) or insufficient sleep duration (< 6.5 h per night). Eligible subjects will be randomized to the Sleep-Opt intervention group or healthy living attention control group for 12 weeks. A 1-week run-in period is planned, with baseline measures of sleep by actigraphy (sleep variability and duration), glycemia (A1C and related glycemic measures: glycemic variability and TIR using continuous glucose monitoring), and other secondary outcomes: diabetes distress, self-management behaviors, quality of life, and additional patient-reported outcomes. Sleep-Opt is a technology-assisted behavioral sleep intervention that we recently developed that leverages the rapidly increasing public interest in sleep tracking. Our behavioral intervention employs four elements: a wearable sleep tracker, didactic content, an interactive smartphone application, and brief telephone counseling. The attention control group will participate in a healthy living information program. Baseline measures will be repeated at midpoint, program completion, and post-program (weeks 6, 12, and 24, respectively) to determine differences between the two groups and sustainability of the intervention. DISCUSSION: A better understanding of strategies to improve sleep in persons with T1D has the potential to be an important component of diabetes. TRIAL REGISTRATION: Clinical Trial Registration: NCT04506151 .

Rationale and study protocol for We-PAP: a randomized pilot/feasibility trial of a couples-based intervention to promote PAP adherence and sleep health compared to an educational control.

BACKGROUND: Obstructive sleep apnea (OSA) is a serious health condition that affects approximately 30-50% of older adults and contributes to risk for cardiometabolic disorders and dementia. Despite the well-documented role of partners in treatment seeking and adherence to positive airway pressure (PAP), treatments for OSA have nearly exclusively focused on the patient and current treatments for OSA do not address co-existing sleep problems such as insomnia that are prevalent in both patients with OSA and their partners. Therefore, the goal of this study is to develop and test a novel couples-based sleep health intervention to promote adherence to PAP and improve sleep health of the couple. METHODS: We are conducting a two-arm, parallel group, single blind, randomized controlled pilot/feasibility trial to compare our novel couples-based sleep health intervention (We-PAP) to an information control group (IC). We-PAP is based on a transdiagnostic model and uses a dyadic approach including increasing effective partner support, communication skills, and couple-level goal-setting. We-PAP involves 3 sessions and delivered via telehealth in weekly sessions. The IC includes standardized patient educational materials. Both groups receive the usual follow-up with their medical team. The study involves assessments at pre-treatment, post-intervention (approximately 1 month after starting PAP and completing We-PAP sessions or IC) and 3 months after starting PAP. Our main outcomes are feasibility and acceptability ratings. Secondary outcomes include comparing We-PAP to IC for PAP adherence, sleep quality (self-report and objective) and cognitive measures. DISCUSSION: We-PAP is the first couples-based transdiagnostic sleep health intervention for patients with OSA and their partners. Results of this study will be used to inform the design of a subsequent fully powered clinical trial. If successful, this intervention could significantly advance current clinical practice in the treatment of OSA and sleep health more comprehensively in older adults. Moreover, this intervention may be useful for improving sleep in other aging populations with multiple sleep and other health problems, including patients with chronic illnesses or those at risk for Alzheimer's disease and their caregivers. TRIAL REGISTRATION: NCT04759157 . Date of registration: February 8, 2021. URL of trial registry record.

Sleep, Diet, Physical Activity, and Stress during the COVID-19 Pandemic: A Qualitative Analysis.

The COVID-19 pandemic has changed routines and habits, raising stress and anxiety levels of individuals worldwide. The goal of this qualitative study was to advance the understanding of how pandemic-related changes affected sleep, diet, physical activity (PA), and stress among adults. We conducted semi-structured, qualitative interviews with 185 participants and selected 33 interviews from a represented sample based on age, race, and gender for coding and analysis of themes. After coding for thematic analysis, results demonstrated four primary themes: sleep, diet, PA, and stress. Sleep sub-themes such as poorer sleep quality were reported by 36% of our participants, and 12% reported increased an frequency of vivid dreams and nightmares. PA was decreased in 52% of our participants, while 33% experienced an increase and 15% experienced no change in PA. Participants also reported having an improved diet, mostly among women. Stress was elevated in 79% of our participants and was more likely to be discussed by women. Many participants reported how stress was involved in precipitating health behavior change, especially for sleep. Increased stress was also linked to elevated anxiety and depression among participants. The results of this qualitative study demonstrate how managing stress could have a beneficial effect on promoting health behaviors and mental health during the COVID-19 pandemic and beyond.

Behavioral interventions to extend sleep duration: A systematic review and meta-analysis.

The goal of this study was to examine the effects of behavioral sleep extension interventions on sleep duration outcomes in children and adults ≥ age 12. We conducted a systematic literature review, article extraction and meta-analysis. Our search yielded 42 studies from 14 countries. The majority of studies (n = 19) enrolled adults, 10 studies enrolled college students, 13 enrolled children (high school or middle school aged). Results from the meta-analysis demonstrated behavioral sleep extension resulted in a significantly higher sleep duration as compared to control group or baseline, with pooled standardized mean difference (SMD) that was similar for both two-arm 0.80 (95 % CI 0.28 to 1.31; p < 0.01; I2 = 99.2%) and one-arm studies 0.75 (95% CI 0.39 to 1.11; p < 0.01; I2 = 86%), and there was significant heterogeneity among both study types. Subgroup analyses revealed that studies with direct interventions on sleep duration (i.e., specified the sleep schedule) had larger effects compared to indirect methods (coaching, educational approaches) and a greater number of curriculum components was associated with smaller effects. Results of this review demonstrate that sleep extension studies are effective at extending sleep in a variety of populations but improving the description of intervention methods and use of more rigorous study designs will improve the quality and reproducibility of this area of research.

The relationship between sleep and physical activity: the moderating role of daily alcohol consumption.

STUDY OBJECTIVES: Studies have demonstrated a daily, bidirectional relationship between sleep and physical activity. However, little is known about how other health behaviors, such as alcohol consumption affect this relationship. This study examined how daily and average alcohol consumption affects the relationships between sleep and physical activity. METHODS: Participants included 70 men and women, ages 18-50 with sleep duration >6.5 hours. Participants wore an actigraph, physical activity monitor and recorded number of alcoholic drinks by daily food logs for 7 days. Results were analyzed using multi-level models to evaluate the 7-day average (i.e. between-person effects) and daily effects (i.e. within-person effects) simultaneously. RESULTS: Those with more average (7 day) minutes of vigorous physical activity had less wake after sleep onset (WASO). Furthermore, a higher number of alcoholic drinks was associated with longer sleep duration and higher WASO over 7 days. Days with a higher number of alcoholic drinks were associated with higher WASO and sleep fragmentation that night. Alcohol intake moderated the average (7 days) and daily relationships between sleep and physical activity such that high average (7 days) WASO was associated with shorter average total physical activity duration, but only for those with higher alcohol intake. In addition, longer physical activity duration during the day was associated with lower sleep fragmentation that night, but only for those with lower alcohol intake. CONCLUSIONS: These data demonstrate that in a naturalistic setting, alcohol intake negatively impacts sleep and diminishes the benefits of physical activity on sleep.

The Society of Behavioral Sleep Medicine (SBSM) COVID-19 Task Force: Objectives and Summary Recommendations for Managing Sleep during a Pandemic.

OBJECTIVE/BACKGROUND: As a response to clinical observations that the pervasive stress and social/environmental disruptions from the 2020 COVID-19 pandemic have also impacted sleep, the Society of Behavioral Sleep Medicine (SBSM) convened the COVID-19 Task Force with goals to identify and disseminate information that could be useful in addressing sleep concerns during this crisis. Participants Members of the SBSM COVID-19 Task Force. Results/Conclusions Herein is a summary of the resources developed by the SBSM COVID-19 Task force, which includes links to online materials developed for use by providers and patients, as well as brief descriptions of key recommendations by the Task Force for specific sleep conditions (e.g., acute insomnia, nightmares) and vulnerable populations (e.g., parents, essential/healthcare workers, older adults).

Technology Assisted Behavior Intervention to Extend Sleep Among Adults With Short Sleep Duration and Prehypertension/Stage 1 Hypertension: A Randomized Pilot Feasibility Study.

STUDY OBJECTIVES: Short sleep duration contributes to hypertension, yet few behavioral sleep extension interventions have been developed. The goal of our study was to evaluate the feasibility and preliminary efficacy of a technology assisted sleep extension intervention among individuals with prehypertension/stage 1 hypertension on sleep, blood pressure and patient reported outcomes. METHODS: Adults aged 30-65 with 24h ambulatory blood pressure (ABP) > 120/80 mmHg and average weekday sleep duration < 7 h/night were randomized 2:1 to a 6-week technology assisted intervention versus a self-management control group. The intervention included a wearable sleep tracker, smartphone application, weekly didactic lessons and brief telephone coaching. The control group was instructed to maintain their current sleep schedule. Data were analyzed using descriptive statistics and nonparametric statistics to evaluate differences in between groups as well as prepost changes within each group. We also conducted bivariate correlations to evaluate predictors of change in sleep and ABP. RESULTS: A total of 16 adults were randomized into the study (11 intervention, 5 control group, 8 women, mean age 45.8 years, standard deviation 9.8 years.) Results at 6-week follow-up demonstrated greater improvement in the intervention group for total sleep time (P = .027), reductions in 24-hour systolic blood pressure (P = .013) and diastolic blood pressure (P = .026), improvements in sleep disturbance (P = .003) and sleep-related impairment (P = .008). Participants in the intervention group completed 90% of the coaching sessions and rated the enjoyment of the intervention as 4 or 5 out of 5. CONCLUSIONS: Technology assisted sleep extension intervention is feasible and well liked in this population. Results demonstrate the potential for this intervention to improve sleep duration, quality and 24-hour ABP.

Predictors of Intervention Interest Among Individuals With Short Sleep Duration.

STUDY OBJECTIVES: Over one-third of the United States population sleeps less than the recommended 7 hours a night, which increases risk for chronic diseases. The aim of this study was to evaluate the acceptability of sleep extension interventions and preferences in sleep extension interventions among adults with short sleep duration. METHODS: Participants aged 18 to 65 years with self-reported sleep duration ≤ 6.5 hours completed an online survey including reported sleep behaviors, barriers to adequate sleep, interest in sleep extension interventions, and a sleep disturbance questionnaire. Data were analyzed using chi-square and binary logistic regression. RESULTS: Participants (n = 92; 61 females; mean age = 45.6 years, standard deviation = 13.5) reported an average sleep duration of 5:49 (standard deviation = 0:49). More than half of the participants reported current health comorbidities (64%), including insomnia (n = 12, 13%) and sleep apnea (n = 9, 10%). Many participants (38%) reported sleep disturbance. The most common barrier to adequate sleep included insomnia or other sleep problems (55%). Most respondents (84%) indicated an interest in increasing sleep duration. Of the treatment options suggested, most (84% of those interested) were interested in a wrist-worn device. Participants with insomnia or other sleep disorders were more likely to be interested in extending sleep, (χ² = 12.86, P < .001) and in a wrist-worn device (χ² = 5.24, P = .022). Higher Patient-Reported Outcomes Measurement Information System sleep disturbance t scores were also associated with interest in monitoring sleep with a wrist-worn device (b = .18, P < .001). CONCLUSIONS: Sleep extension interventions using wearable technology are attractive to individuals with short sleep duration, particularly those with greater sleep disturbance and comorbid sleep disorders. CITATION: Adkins EC, DeYonker O, Duffecy J, Hooker SA, Baron KG. Predictors of intervention interest among individuals with short sleep duration. JClin SleepMed. 2019;15(8):1143-1148.

Sleep-related attitudes, beliefs, and practices among an urban-dwelling African American community: a qualitative study.

OBJECTIVES: Short sleep duration and poor sleep quality are more prevalent among African Americans (AAs) and may be a modifiable risk factor for cardiometabolic disorders. However, research is limited about sleep-related attitudes, beliefs, and practices among AAs. Our objective was to evaluate these practices and beliefs surrounding sleep among urban-dwelling AAs. DESIGN: Qualitative study comprised of five 90-minute focus groups using a semistructured interview guide. SETTING: Five churches located on the west side of Chicago. PARTICIPANTS: Adults (N = 43) ages 25-75 years. MEASUREMENTS: Transcripts were voice recorded, transcribed, and then coded for content analysis using NVivo 12 Pro to capture themes in the discussions. RESULTS: Most participants (86%) reported sleeping less than the recommended 7 or more hours. The discrepancy between actual and desired sleep duration was nearly 3 hours per night. Participants reported that sleep is essential for mental and physical health. Napping and consuming caffeine were frequently reported techniques for coping with lack of sleep. Noise, physical discomfort, and stress were reported as barriers to sleep, and participants reported using TV and other electronics to cope with racing thoughts or worry. Many participants were diagnosed with or knew someone with obstructive sleep apnea, but few participants had been diagnosed with insomnia or were aware of nonpharmacologic insomnia treatments. CONCLUSION: A cycle of stress/disruptive environment, stress, rumination at night, and coping by use of electronics and daytime napping may perpetuate sleep disparities in this community. Results suggest that sleep-related interventions should include stress reduction and environmental improvements in addition to the typical sleep hygiene-related behavioral recommendations.

Feeling validated yet? A scoping review of the use of consumer-targeted wearable and mobile technology to measure and improve sleep.

The objectives of this review were to evaluate the use of consumer-targeted wearable and mobile sleep monitoring technology, identify gaps in the literature and determine the potential for use in behavioral interventions. We undertook a scoping review of studies conducted in adult populations using consumer-targeted wearable technology or mobile devices designed to measure and/or improve sleep. After screening for inclusion/exclusion criteria, data were extracted from the articles by two co-authors. Articles included in the search were using wearable or mobile technology to estimate or evaluate sleep, published in English and conducted in adult populations. Our search returned 3897 articles and 43 met our inclusion criteria. Results indicated that the majority of studies focused on validating technology to measure sleep (n = 23) or were observational studies (n = 10). Few studies were used to identify sleep disorders (n = 2), evaluate response to interventions (n = 3) or deliver interventions (n = 5). In conclusion, the use of consumer-targeted wearable and mobile sleep monitoring technology has largely focused on validation of devices and applications compared with polysomnography (PSG) but opportunities exist for observational research and for delivery of behavioral interventions. Multidisciplinary research is needed to determine the uses of these technologies in interventions as well as the use in more diverse populations including sleep disorders and other patient populations.

Technology-Assisted Behavioral Intervention to Extend Sleep Duration: Development and Design of the Sleep Bunny Mobile App.

BACKGROUND: Despite the high prevalence of short sleep duration (29.2% of adults sleep <6 hours on weekdays), there are no existing theory-based behavioral interventions to extend sleep duration. The popularity of wearable sleep trackers provides an opportunity to engage users in interventions. OBJECTIVE: The objective of this study was to outline the theoretical foundation and iterative process of designing the "Sleep Bunny," a technology-assisted sleep extension intervention including a mobile phone app, wearable sleep tracker, and brief telephone coaching. We conducted a two-step process in the development of this intervention, which was as follows: (1) user testing of the app and (2) a field trial that was completed by 2 participants with short sleep duration and a cardiovascular disease risk factor linked to short sleep duration (body mass index [BMI] >25). METHODS: All participants had habitual sleep duration <6.5 hours verified by 7 days of actigraphy. A total of 6 individuals completed initial user testing in the development phase, and 2 participants completed field testing. Participants in the user testing and field testing responded to open-ended surveys about the design and utility of the app. Participants in the field testing completed the Epworth Sleepiness Scale and also wore an actigraph for a 1-week baseline period and during the 4-week intervention period. RESULTS: The feedback suggests that users enjoyed the wearable sleep tracker and found the app visually pleasing, but they suggested improvements to the notification and reminder features of the app. The 2 participants who completed the field test demonstrated significant improvements in sleep duration and daytime sleepiness. CONCLUSIONS: Further testing is needed to determine effects of this intervention in populations at risk for the mental and physical consequences of sleep loss.

Phase Relationship between DLMO and Sleep Onset and the Risk of Metabolic Disease among Normal Weight and Overweight/Obese Adults.

Circadian misalignment is hypothesized to contribute to increased diabetes and obesity among shift workers and individuals with late sleep timing. Accordingly, the goal of our study was to identify-among normal and overweight/obese adults-associations between circadian timing (dim light melatonin onset; DLMO) and circadian misalignment (the interval between DLMO and sleep onset) with metabolic disease risk. This was a secondary analysis of data from a larger study. Participants ages 18 to 50 years without depression, diabetes, or shift work, with sleep duration 6.5 h or more, completed the following evaluations: 7 days of wrist actigraphy, circadian timing assessment (DLMO), and a fasting blood draw to measure glucose and insulin and calculate the Homeostatic Model of Assessment-Insulin Resistance (HOMA-IR). Data were analyzed using correlation and regression analyses controlling for age, sex, DLMO, and sleep duration. Analyses were conducted for the entire sample ( n = 54) and stratified by normal weight ( n = 36) and overweight/obese groups ( n = 18). Mean age was 26.4 years (SD = 7.1 years). Average sleep duration was 436.2 min (SD = 55.1 min), DLMO was 2250h (SD = 01:31), and interval between DLMO and sleep onset was 2 h 18 min (SD = 53 min). Average BMI was 24.3 kg/m2 (SD = 4.5 kg/m2). Circadian timing and interval between DLMO and sleep onset were not associated with glucose, insulin, or HOMA-IR in the main analyses. Among overweight/obese participants, a shorter interval between DLMO and sleep onset was associated with higher insulin ( B[SE] = -5.12 [2.24], p = 0.04) and HOMA-IR ( B[SE] = -1.32 [0.57], p = 0.04). Results of our multivariable model indicated that among overweight/obese participants, insulin was 5.1 pmol/L higher and HOMA was 1.3 µU/mL higher for every hour closer that sleep onset was to DLMO. The strengths of this study include the use of objective measures of circadian timing, but results should be considered hypothesis generating due to the small sample size and use of subgroup analyses.