Mobile Intervention to Improve Sleep and Functional Health of Veterans With Insomnia: Randomized Controlled Trial

Mi Sleep Coach Mobile App to Address Insomnia Symptoms Among Cancer Survivors: Single-Arm Feasibility Study

BACKGROUND

Rates of sleep disturbance among survivors of cancer are more than 3 times higher than the general population. Causes of sleep disturbance among survivors are many and multifaceted, including anxiety and fear related to cancer diagnosis and treatments. Cognitive behavioral therapy for insomnia (CBT-I) is considered a first-line treatment for insomnia; However, a lack of access to trained professionals and limited insurance coverage for CBT-I services has limited patient access to these effective treatments. Evidence supports digital delivery of CBT-I (dCBT-I), but there is only limited evidence to support its use among survivors of cancer. Broad adoption of smartphone technology provides a new channel to deliver dCBT-I, but no prior studies have evaluated mobile dCBT-I interventions for survivors. To address the need for accessible and efficacious CBT-I for survivors of cancer, the Mi Sleep Coach program was developed to adapt CBT-I for delivery to survivors of cancer as a self-directed mobile health app.

OBJECTIVE

This single-arm feasibility study assessed the adherence, attrition, usefulness, and satisfaction of the Mi Sleep Coach app for insomnia.

METHODS

A 7-week, single-arm study was conducted, enrolling adult survivors of breast, prostate, or colon cancer reporting sleep disturbances.

RESULTS

In total, 30 participants were enrolled, with 100% completing the study and providing data through week 7. Further, 9 out of 10 app features were found to be useful by 80% (n=24) to 93% (n=28) of the 30 participants. Furthermore, 27 (90%) participants were satisfied with the Mi Sleep Coach app and 28 (93%) would recommend the use of the Mi Sleep Coach app for those with insomnia. The Insomnia Severity Index showed a decrease from baseline (18.5, SD 4.6) to week 7 (10.4, SD 4.2) of 8.1 (P<.001; Cohen d=1.5). At baseline, 25 (83%) participants scored in the moderate (n=19; 15-21) or severe (n=6; 22-28) insomnia range. At week 7, a total of 4 (13%) patients scored in the moderate (n=4) or severe (n=0) range. The number of patients taking prescription sleep medications decreased from 7 (23%) at baseline to 1 (3%; P<.001) at week 7. The number of patients taking over-the-counter sleep medications decreased from 14 (47%) at baseline to 9 (30%; P=.03) at week 7.

CONCLUSIONS

The Mi Sleep Coach app demonstrated high levels of program adherence and user satisfaction and had large effects on the severity of insomnia among survivors of cancer. The Mi Sleep Coach app is a promising intervention for cancer-related insomnia, and further clinical trials are warranted. If proven to significantly decrease insomnia in survivors of cancer in future randomized controlled clinical trials, this intervention would provide more survivors of cancer with easy access to evidence-based CBT-I treatment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04827459; https://clinicaltrials.gov/study/NCT04827459.

Efficacy of an Internet-Delivered Intervention for Improving Insomnia Severity and Functioning in Veterans: Randomized Controlled Trial

BACKGROUND

Despite a growing evidence base that internet-delivered cognitive behavioral therapy for insomnia (iCBT-I) is associated with decreased insomnia severity, its efficacy has been minimally examined in veterans.

OBJECTIVE

The objective of this study was to evaluate the efficacy of an unguided iCBT-I (Sleep Healthy Using the Internet [SHUTi]) among veterans.

METHODS

We conducted a single-blind, randomized controlled trial in Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn veterans eligible for Veterans Health Administration care. Participants were randomly assigned (1:1) to receive SHUTi (a self-guided and interactive program) or an Insomnia Education Website (IEW) that provided nontailored and fixed insomnia information. Web-based assessments were administered at baseline, postintervention, 6 months postintervention, and 1 year postintervention. The primary outcome was self-reported insomnia severity (Insomnia Severity Index [ISI]). Secondary outcomes were self-reported mental and physical health functioning (Veterans RAND 36-item Health Survey). Exploratory outcomes comprised sleep diary parameters.

RESULTS

Of the 231 randomized participants (mean age 39.3, SD 7.8 years; 170/231, 73.5% male sex; 26/231, 11.3% Black; 172/231, 74.5% White; 10/231, 4.3% multiracial; and 17/231, 7.4% other; 36/231, 15.6% Hispanic) randomized between April 2018 and January 2019, a total of 116 (50.2%) were randomly assigned to SHUTi and 115 (49.8%) to the IEW. In intent-to-treat analyses, SHUTi participants experienced significantly larger ISI decreases compared with IEW participants at all time points (generalized η2 values of 0.13, 0.12, and 0.10, respectively; all P<.0001). These corresponded to estimated larger differences in changes of -3.47 (95% CI -4.78 to -2.16), -3.80 (95% CI -5.34 to -2.27), and -3.42 (95% CI -4.97 to 1.88) points on the ISI for the SHUTi group. SHUTi participants experienced significant improvements in physical (6-month generalized η2=0.04; P=.004) and mental health functioning (6-month and 1-year generalized η2=0.04; P=.009 and P=.005, respectively). Significant sleep parameter improvements were noted for SHUTi (all P<.05), though the pattern and magnitude of these reductions varied by parameter. No adverse events were reported.

CONCLUSIONS

Self-administered iCBT-I was associated with immediate and long-term improvements in insomnia severity. Findings suggest that leveraging technology to meet insomnia treatment demands among veterans may be a promising approach.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03366870; https://clinicaltrials.gov/ct2/show/NCT03366870.

Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data

BACKGROUND

Patient-generated health data are important in the management of several diseases. Although there are limitations, information can be obtained using a wearable device and time-related information such as exercise time or sleep time can also be obtained. Fitbits can be used to acquire sleep onset, sleep offset, total sleep time (TST), and wakefulness after sleep onset (WASO) data, although there are limitations regarding the depth of sleep and satisfaction; therefore, the patient's subjective response is still important information that cannot be replaced by wearable devices.

OBJECTIVE

To effectively use patient-generated health data related to time such as sleep, it is first necessary to understand the characteristics of the time response recorded by the user. Therefore, the aim of this study was to analyze the characteristics of individuals' time perception in comparison with wearable data.

METHODS

Sleep data were acquired for 2 weeks using a Fitbit. Participants' sleep records were collected daily through chatbot conversations while wearing the Fitbit, and the two sets of data were statistically compared.

RESULTS

In total, 736 people aged 30-59 years were recruited for this study, and the sleep data of 543 people who wore a Fitbit and responded to the chatbot for more than 7 days on the same day were analyzed. Research participants tended to respond to sleep-related times on the hour or in 30-minute increments, and each participant responded within the range of 60-90 minutes from the value measured by the Fitbit. On average for all participants, the chat responses and the Fitbit data were similar within a difference of approximately 15 minutes. Regarding sleep onset, the participant response was 8 minutes and 39 seconds (SD 58 minutes) later than that of the Fitbit data, whereas with respect to sleep offset, the response was 5 minutes and 38 seconds (SD 57 minutes) earlier. The participants' actual sleep time (AST) indicated in the chat was similar to that obtained by subtracting the WASO from the TST measured by the Fitbit. The AST was 13 minutes and 39 seconds (SD 87 minutes) longer than the time WASO was subtracted from the Fitbit TST. On days when the participants reported good sleep, they responded 19 (SD 90) minutes longer on the AST than the Fitbit data. However, for each sleep event, the probability that the participant's AST was within ±30 and ±60 minutes of the Fitbit TST-WASO was 50.7% and 74.3%, respectively.

CONCLUSIONS

The chatbot sleep response and Fitbit measured time were similar on average and the study participants had a slight tendency to perceive a relatively long sleep time if the quality of sleep was self-reported as good. However, on a participant-by-participant basis, it was difficult to predict participants' sleep duration responses with Fitbit data. Individual variations in sleep time perception significantly affect patient responses related to sleep, revealing the limitations of objective measures obtained through wearable devices.

Patient Engagement and Provider Effectiveness of a Novel Sleep Telehealth Platform and Remote Monitoring Assessment in the US Military: Pilot Study Providing Evidence-Based Sleep Treatment Recommendations

BACKGROUND

Sleep problems are common and costly in the US military. Yet, within the military health system, there is a gross shortage of trained specialist providers to address sleep problems. As a result, demand for sleep medicine care far exceeds the available supply. Telehealth including telemedicine, mobile health, and wearables represents promising approaches to increase access to high-quality and cost-effective care.

OBJECTIVE

The purpose of this study was to evaluate patient engagement and provider perceived effectiveness of a novel sleep telehealth platform and remote monitoring assessment in the US military. The platform includes a desktop web portal, native mobile app, and integrated wearable sensors (ie, a commercial off-the-shelf sleep tracker [Fitbit]). The goal of the remote monitoring assessment was to provide evidence-based sleep treatment recommendations to patients and providers.

METHODS

Patients with sleep problems were recruited from the Internal Medicine clinic at Walter Reed National Military Medical Center. Patients completed intensive remote monitoring assessments over 10 days (including a baseline intake questionnaire, daily sleep diaries, and 2 daily symptom surveys), and wore a Fitbit sleep tracker. Following the remote monitoring period, patients received assessment results and personalized sleep education in the mobile app. In parallel, providers received a provisional patient assessment report in an editable electronic document format. Patient engagement was assessed via behavioral adherence metrics that were determined a priori. Patients also completed a brief survey regarding ease of completion. Provider effectiveness was assessed via an anonymous survey.

RESULTS

In total, 35 patients with sleep problems participated in the study. There were no dropouts. Results indicated a high level of engagement with the sleep telehealth platform, with all participants having completed the baseline remote assessment, reviewed their personalized sleep assessment report, and completed the satisfaction survey. Patients completed 95.1% of sleep diaries and 95.3% of symptom surveys over 10 days. Patients reported high levels of satisfaction with most aspects of the remote monitoring assessment. In total, 24 primary care providers also participated and completed the anonymous survey. The results indicate high levels of perceived effectiveness and identified important potential benefits from adopting a sleep telehealth approach throughout the US military health care system.

CONCLUSIONS

Military patients with sleep problems and military primary care providers demonstrated high levels of engagement and satisfaction with a novel sleep telehealth platform and remote monitoring assessment. Sleep telehealth approaches represent a potential pathway to increase access to evidence-based sleep medicine care in the US military. Further evaluation is warranted.

On the Efficacy of a CBT-I-Based Online Program for Sleep Problems: A Randomized Controlled Trial

There is an urgent need for easily accessible treatment options for sleep problems to reduce the current treatment gap in receiving cognitive behavioral therapy for insomnia (CBT-I). Using a randomized controlled trial, we evaluated the efficacy of a CBT-I-based online program on sleep. Fifty-three volunteers (21-71 years; MAge = 44.6 ± 12.5; 27 female) suffering from impaired sleep were randomly allocated either to the experimental group (EG, n = 27) or to an active control group (CG, n = 26). The EG participated in a 6-week CBT-I-based online program, while the CG received psychoeducation and sleep hygiene instructions. Sleep was assessed both objectively via ambulatory polysomnography (PSG) as well as subjectively via questionnaires at three time points (baseline, pre- and post-intervention). A one-month follow-up assessment was performed using questionnaires. The EG showed small but reliable improvements from pre- to post-intervention in PSG-derived wake after sleep onset (from 58.6 min to 42.5 min; p < 0.05) and sleep efficiency (from 86.0% to 89.2%; p < 0.05). Furthermore, subjective sleep quality (assessed via Pittsburgh Sleep Quality Index) improved significantly during intervention (p = 0.011) and follow-up (p = 0.015) in the EG alone. The Insomnia Severity Index decreased from pre- to post-intervention in both groups (EG: p = 0.003, CG: p = 0.008), while it further improved during follow-up (p = 0.035) in the EG alone. We show that a CBT-I-based online program can improve sleep not only subjectively but also objectively and can be a viable alternative when face-to-face interventions are not available.

A scoping review of sleep education and training for nurses

BACKGROUND

Shift work and resulting sleep impairment among nurses can increase their risk for poor health outcomes, occupational injuries, and errors due to sleep deficiencies. While sleep education and training for nurses has been recommended as part of a larger fatigue risk management system, little is known about training programs designed specifically for nurses.

OBJECTIVE

Investigate the literature for current sleep education or training programs specifically for shift working nurses, with intent to assess training content, delivery characteristics, and outcome measures.

DESIGN

A scoping review conducted October 2020 through September 2021.

METHODS

The bibliographic databases Cumulative Index of Nursing and Allied Health (CINAHL), Scopus, PubMed, and NIOSHTIC-2 were searched using words such as "nurse," "sleep hygiene," "shift work," and "education". Studies were included if they: 1) were original research; 2) discussed sleep education, training, or sleep hygiene interventions; 3) included a study population of nurses engaging in shift work; 4) focused on sleep as a primary study measure; 5) were written in English language; and 6) were published in 2000 or later.

RESULTS

Search results included 17,237 articles. After duplicates were removed, 14,620 articles were screened. Nine articles were found to meet established criteria. All studies included sleep hygiene content in the training programs, with five studies adding psychological and/or behavior change motivation training to support change in nurse sleep habits. Three studies added specific training for nurses and for managers. Delivery modes included in-person training of various lengths and frequency, mobile phone application with daily engagement, an online self-guided presentation, and daily reading material coupled with audio training. Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale were the outcome measures most frequently used. Although studies demonstrated improved sleep measures, most were pilot studies testing feasibility.

CONCLUSION

Although there is a paucity of studies focused on sleep education and training for shift working nurses, we found the inclusion of sleep hygiene content was the only common characteristic of all nine studies. The variability in training content, delivery methods, and outcome measures suggests further research is needed on what constitutes effective sleep education and training for nurses.

Understanding the research on tracking, diagnosing, and intervening in sleep disorders using mHealth apps: Bibliometric analysis and systematic reviews

Objectives

In solving the global challenge of sleep disorders, Mobile Health app is one of the important means to monitor, diagnose, and intervene in sleep disorders. This study aims to (1) summarize the status and trends of research in this field; (2) assess the production and usage of sleep mHealth apps; (3) calculate the conversion rate of grants that the proportion of newly developed apps from being funded and developed to published on application stores.

Methods

Using bibliometric and content analysis methods, based on "Research Paper-Product Output-Product Application" chain and considering the "Research Grants" of articles, we conducted a systematic review of eight databases, to identify relevant studies over the last decade.

Results

Over the past decade, 1399 authors published 313 papers in 182 journals and conferences. The number of publications increased with an average annual growth of 41.6%. The current focus area is research using cognitive behavioral therapy to intervene in sleep. Sleep-staging tracking is a shortcoming of this field. A total 368 sleep mHealth apps (233 newly developed and 135 existing) were examined in 313 papers; 323 grants supported 178 articles (56.9%). Only 12 of the newly developed apps are used in the real world, resulting in a 9% grant conversion rate.

Conclusions

In the last decade, the field of tracking, diagnosing, and intervening in sleep disorders using mHealth apps has shown a trend of rapid development. However, the conversion rate of products from being funded and developed for use by end-users is low.

Veteran Acceptance of Sleep Health Information Technology: a Mixed-Method Study

Sleep disturbances, including chronic insomnia and sleep apnea, are major concerns for US veterans, with rising rates and detrimental effects on physical, mental, and social well-being. Sleep disturbances in veterans are also underdiagnosed and undertreated for reasons that include limited sleep clinician availability, long wait times, and the time commitment for treatment. Greater use of sleep health information technologies could improve access to assessment and treatment of sleep disturbances. However, the assessment of acceptance of these technologies among veterans is still ongoing. This mixed-method study combines data from two separate but similar randomized controlled trials to assess acceptance of sleep health information technologies for veterans with chronic insomnia. Sleep health information technologies included in these trials were the following: (1) a WatchPAT sleep monitor for home-based sleep assessment, including detection of sleep apnea, and (2) the VA mobile app Cognitive Behavioral Therapy for Insomnia (CBT-i Coach), which supports self-management of insomnia. The combined sample of 37 veterans receiving care within one New England VA medical center completed a six-week trial using both health information technology tools. Participants completed a survey and interview at the end of the 6 weeks. Overall, participants found the tools acceptable, easy to use, and useful and reported they would use them in the future. Thus, these sleep health information technologies appear to provide an acceptable remote option for assessing and managing sleep issues for veterans. ClinicalTrials.gov NCT02392000; http://clinicaltrials.gov/ct2/show/NCT02392000 and ClinicalTrials.gov NCT03305354; https://clinicaltrials.gov/ct2/show/NCT03305354.

Daily physical activity and sleep in veterans: the role of insomnia severity

Physical activity (PA) is suggested as an easily accessible adjunctive lifestyle intervention for insomnia. It is not clear if PA is equally beneficial across different levels of insomnia severity. The current study examined the relationship between daily PA (steps) and sleep (duration, efficiency, and quality) across the spectrum of insomnia severity. Multilevel models estimated day-to-night relationships between PA and sleep, and if insomnia severity moderated these relationships. Days with greater PA were associated with nights with longer sleep duration. This was moderated by insomnia severity; PA was associated with longer sleep that night in participants with mild insomnia and associated with less sleep in those with severe insomnia. PA was not associated with sleep efficiency or quality. PA is potentially an easily accessible and impactful intervention to promote sleep duration in participants who are experiencing less severe sleep disturbance. More complex, resource-intensive interventions may be needed as insomnia severity increases.