Mobile Phone Interventions for Sleep Disorders and Sleep Quality: Systematic Review

Examining bi-directional links between loneliness, social connectedness and sleep from a trait and state perspective

Greater loneliness as well as a lack of social connectedness have often been associated with poorer sleep. However, the temporal dynamics and direction of these associations remain unclear. Aim of the current study was to examine bi-directional associations between loneliness/social connectedness and sleep in 48 stress-exposed medical students during their first medical internship, considered a period of heightened stress. We obtained trait-level questionnaire data on loneliness and global sleep completed before and during the internship as well as state-level diary- and wearable-based data on daily changes in social connectedness and sleep collected twice over the period of seven consecutive days, once before and once during the internship. Bi-directional associations among greater loneliness and higher daytime dysfunction on trait-level were identified. In addition, several uni-directional associations between loneliness/social connectedness and sleep were found on trait- and state-level. In sum, findings of this study point at a bi-directional relation among loneliness/social connectedness and sleep, in which variables seem to reciprocally influence each other across longer-term periods as well as on a day-to-day basis.

Effectiveness of mobile applications in improving insomnia symptoms among adults from multi-community: A systematic review and meta-analysis

OBJECTIVE/BACKGROUND

To clarify whether mobile sleep applications alleviate insomnia symptoms among adults from multi-community.

PATIENTS/METHODS

A literature search was conducted using the PubMed, Cochrane, PsycINFO, and Web of Science databases for articles related to mobile technology and sleep interventions published between database inceptions and March 27, 2023. We pooled relevant data using a random-effects model, and a meta-analysis was performed using a web version of the Cochrane Review Manager. The effect size was estimated and reported as the combined overall effect (weighted average). Forest plots were created, and the Cochrane risk-of-bias tool and Newcastle-Ottawa Scale were used to evaluate studies.

RESULTS

After an initial screening and full-text reviews, seven studies were identified with a total of 10,139 participants (females n = 8844, 87.2 %) recruited from multi-community and not diagnosed with sleep disorders or taking medications. These studies included one cross-sectional study investigating mindfulness meditation apps and six randomized-controlled trials (RCTs), including one with sleep-feedback messaging, one comparing sleep applications with or without a wearable device, and four with multicomponent interventions based on cognitive theory and subsequent behavioral change techniques. In a meta-analysis of three cognitive behavior therapy (CBT)-based RCTs, the intervention group showed statistically significant improvements in insomnia symptoms according to the Pittsburgh Sleep Quality Index but with high heterogeneity, while two CBT-based RCTs showed no significant improvements in the Insomnia Severity Index with low heterogeneity.

CONCLUSIONS

A small body of evidence supports the use of CBT-based sleep applications to improve insomnia symptoms among adults from multi-community.

Sleep Health Analysis Through Sleep Symptoms in 35,808 Individuals Across Age and Sex Differences: Comparative Symptom Network Study

BACKGROUND

Sleep health is a multidimensional construct that includes objective and subjective parameters and is influenced by individual sleep-related behaviors and sleep disorders. Symptom network analysis allows modeling of the interactions between variables, enabling both the visualization of relationships between different factors and the identification of the strength of those relationships. Given the known influence of sex and age on sleep health, network analysis can help explore sets of mutually interacting symptoms relative to these demographic variables.

OBJECTIVE

This study aimed to study the centrality of symptoms and compare age and sex differences regarding sleep health using a symptom network approach in a large French population that feels concerned about their sleep.

METHODS

Data were extracted from a questionnaire provided by the Réseau Morphée health network. A network analysis was conducted on 39 clinical variables related to sleep disorders and sleep health. After network estimation, statistical analyses consisted of calculating inferences of centrality, robustness (ie, testifying to a sufficient effect size), predictability, and network comparison. Sleep clinical variable centralities within the networks were analyzed by both sex and age using 4 age groups (18-30, 31-45, 46-55, and >55 years), and local symptom-by-symptom correlations determined.

RESULTS

Data of 35,808 participants were obtained. The mean age was 42.7 (SD 15.7) years, and 24,964 (69.7%) were women. Overall, there were no significant differences in the structure of the symptom networks between sexes or age groups. The most central symptoms across all groups were nonrestorative sleep and excessive daytime sleepiness. In the youngest group, additional central symptoms were chronic circadian misalignment and chronic sleep deprivation (related to sleep behaviors), particularly among women. In the oldest group, leg sensory discomfort and breath abnormality complaint were among the top 4 central symptoms. Symptoms of sleep disorders thus became more central with age than sleep behaviors. The high predictability of central nodes in one of the networks underlined its importance in influencing other nodes.

CONCLUSIONS

The absence of structural difference between networks is an important finding, given the known differences in sleep between sexes and across age groups. These similarities suggest comparable interactions between clinical sleep variables across sexes and age groups and highlight the implication of common sleep and wake neural circuits and circadian rhythms in understanding sleep health. More precisely, nonrestorative sleep and excessive daytime sleepiness are central symptoms in all groups. The behavioral component is particularly central in young people and women. Sleep-related respiratory and motor symptoms are prominent in older people. These results underscore the importance of comprehensive sleep promotion and screening strategies tailored to sex and age to impact sleep health.

The Effect of Physical Activity on Sleep Quality Among Chinese College Students: The Chain Mediating Role of Stress and Smartphone Addiction During the COVID-19 Pandemic

Purpose

During the period of COVID-19 pandemic, the social restrictions and isolation exerted a significant impact on the sleep quality of Chinese college students. This study aims to delve into the influence of physical activity on the sleep quality of college students as well as the mediating roles of stress and smartphone addiction.

Materials and Methods

A cohort of 274 eligible college students (146 males and 128 females) were selected for the investigation. The International Physical Activity Questionnaire Short Form, Stress Perception Scale, Smartphone Addiction Scale, and Pittsburgh Sleep Quality Index were employed to assess the levels of physical activity, stress, smartphone addiction, and sleep quality among college students. For data analysis, descriptive statistics, correlation analysis, and chained mediation effect tests were performed sequentially.

Results

The findings revealed: (1) a significant negative correlation between physical activity and stress, smartphone addiction, and sleep quality among college students (r = -0.216, p < 0.001; r = -0.224, p < 0.001; r = -0.259, p < 0.001); (2) independent mediating roles of stress and smartphone addiction in the relationship between physical activity and sleep quality; and (3) chained mediating effects of stress and smartphone addiction in the association between physical activity and sleep quality.

Conclusion

This study deepens our comprehension of how physical activity augments the quality of slumber, concurrently emphasizing that mitigating stress levels and alleviating smartphone addiction constitute effective strategies for preventing sleep issues among college students.

Sleep mHealth Applications and Behavior Change Techniques Evaluation

OBJECTIVES

Mobile health apps may be an effective way to increase sleep management skills. Although little has been documented about the content and quality of available sleep management apps, providers often make app recommendations to help with sleep self-management. The objective of this study was to systematically evaluate the content and quality of commercially available sleep apps.

METHODS

Following a systematic search of the Apple App and Google Play stores, 56 sleep management apps were evaluated. App content was evaluated using the taxonomy of behavior change techniques (BCTs), and app quality was assessed using the Mobile App Rating Scale.

RESULTS

Sleep management apps included 0-15 BCTs (M = 6.89) and 0-9 sleep BCTs (M = 4.87). App quality ranged from 2.51 to 4.80 (M = 3.78) out of 5.00. Sleepiest Sleep Sounds Stories, ShutEye: Sleep Tracker, and Mintal Tracker: Sleep Recorder included the highest number of sleep BCTs and highest quality scores.

CONCLUSIONS

While the content and quality of sleep management apps is variable, the findings are promising as many apps included a high number of BCTs and high quality. Although evidence of efficacy through randomized controlled trials is necessary to establish efficacy, this review can aid in app selection in the interim.

Effects of digital sleep interventions on sleep and psychological health during the COVID-19 pandemic: A systematic review and meta-analysis

BACKGROUND

Various digital sleep interventions have been implemented to address sleep and psychological complications during the coronavirus disease 2019 (COVID-19) pandemic. However, the characteristics and effectiveness of digital sleep interventions on sleep and psychological outcomes for people with sleep problems during the COVID-19 pandemic are unknown.

METHODS

The protocol of this systematic review and meta-analysis was registered on PROSPERO (ID: CRD42022325662), seven databases were searched from December 2019 to June 2023. Reference lists from digital sleep reviews were also identified and selected. Two reviewers independently screened eligible articles and extracted data. Quality appraisal was undertaken by two independent reviewers using the Cochrane Risk-of-Bias Tools. Data synthesis was conducted using fixed- or random-effects model based on the results of the heterogeneity test.

RESULTS

A total of 20 studies were identified, including nine randomised controlled trials (RCTs) and 11 non-RCTs, involving 3860 participants. Meta-analyses showed that digital sleep interventions significantly improve sleep quality, insomnia, and depression during the COVID-19 pandemic. Subgroup analysis showed that interventions of more than four weeks, healthcare workers as participants, and relaxation therapies may have the advantage of improving sleep quality. Most non-RCTs supported the efficacy of digital sleep interventions on sleep and psychological health.

CONCLUSION

Digital sleep interventions during the COVID-19 pandemic had significant effectiveness in improving sleep and psychological outcomes for people with sleep problems. More structured and personalised digital sleep interventions should be designed, and other diverse digital technologies could be used to improve sleep and psychological disorders.

Mobile phone addiction and mental health: the roles of sleep quality and perceived social support

As a global phenomenon, mobile phone addiction has become an increasingly common issue among Chinese university students. Although previous research explored the link between mobile phone addiction and mental health, the possible mechanism underlying the above association is unclear. We administered a cross-sectional survey to 585 participants from two universities in Kunming, southwest China, from October 2021 to January 2022. Our results suggested that mobile phone addiction was negatively associated with mental health, and sleep quality partially mediated the relationship between mobile phone addiction and mental health. Furthermore, perceived social support positively moderated the direct effect of sleep quality on mental health, as well as the indirect effect of mobile phone addiction on mental health. These findings provide a new insight into the underlying mechanism by which mobile phone addiction affects university students' mental health. The results emphasize a necessary task for administrators, health workers, and family members to attach importance to the overuse of mobile phones among university students.

Quality appraisal of spatial epidemiology and health geography research: A scoping review of systematic reviews

A scoping review of peer-reviewed literature was conducted to understand how systematic reviews assess the methodological quality of spatial epidemiology and health geography research. Fifty-nine eligible reviews were identified and included. Variations in the use of quality appraisal tools were found. Reviews applied existing quality appraisal tools with no adaptations (n = 32; 54%), existing quality appraisal tools with adaptations (n = 9; 15%), adapted tools or methods from other reviews (n = 13; 22%), and developed new quality appraisal tools for the review (n = 5; 8%). Future research should focus on developing and validating a quality appraisal tool that evaluates the spatial methodology within studies.

eHealth-Based Psychosocial Interventions for Adults With Insomnia: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Worldwide, insomnia remains a highly prevalent public health problem. eHealth presents a novel opportunity to deliver effective, accessible, and affordable insomnia treatments on a population-wide scale. However, there is no quantitative integration of evidence regarding the effectiveness of eHealth-based psychosocial interventions on insomnia.

OBJECTIVE

We aimed to evaluate the effectiveness of eHealth-based psychosocial interventions for insomnia and investigate the influence of specific study characteristics and intervention features on these effects.

METHODS

We searched PubMed, Embase, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials from database inception to February 16, 2021, for publications investigating eHealth-based psychosocial interventions targeting insomnia and updated the search of PubMed to December 6, 2021. We also screened gray literature for unpublished data. Eligible studies were randomized controlled trials of eHealth-based psychosocial interventions targeting adults with insomnia. Random-effects meta-analysis models were used to assess primary and secondary outcomes. Primary outcomes were insomnia severity and sleep quality. Meta-analyses were performed by pooling the effects of eHealth-based psychosocial interventions on insomnia compared with inactive and in-person conditions. We performed subgroup analyses and metaregressions to explore specific factors that affected the effectiveness. Secondary outcomes included sleep diary parameters and mental health-related outcomes.

RESULTS

Of the 19,980 identified records, 37 randomized controlled trials (13,227 participants) were included. eHealth-based psychosocial interventions significantly reduced insomnia severity (Hedges g=-1.01, 95% CI -1.12 to -0.89; P<.001) and improved sleep quality (Hedges g=-0.58, 95% CI -0.75 to -0.41; P<.001) compared with inactive control conditions, with no evidence of publication bias. We found no significant difference compared with in-person treatment in alleviating insomnia severity (Hedges g=0.41, 95% CI -0.02 to 0.85; P=.06) and a significant advantage for in-person treatment in enhancing sleep quality (Hedges g=0.56, 95% CI 0.24-0.88; P<.001). eHealth-based psychosocial interventions had significantly larger effects (P=.01) on alleviating insomnia severity in clinical samples than in subclinical samples. eHealth-based psychosocial interventions that incorporated guidance from trained therapists had a significantly greater effect on insomnia severity (P=.05) and sleep quality (P=.02) than those with guidance from animated therapists or no guidance. Higher baseline insomnia severity and longer intervention duration were associated with a larger reduction in insomnia severity (P=.004). eHealth-based psychosocial interventions significantly improved each secondary outcome.

CONCLUSIONS

eHealth interventions for insomnia are effective in improving sleep and mental health and can be considered a promising treatment for insomnia. Our findings support the wider dissemination of eHealth interventions and their further promotion in a stepped-care model. Offering blended care could improve treatment effectiveness. Future research needs to elucidate which specific intervention components are most important to achieve intervention effectiveness. Blended eHealth interventions may be tailored to benefit people with low socioeconomic status, limited access to health care, or lack of eHealth literacy.

Dose-response analysis of smartphone usage and self-reported sleep quality: a systematic review and meta-analysis of observational studies

STUDY OBJECTIVES

Several studies have recently reported on the association between smartphone usage and self-reported sleep quality. However, no systematic review or meta-analysis has yet been performed. We aimed to analyze the association between smartphone usage time and self-reported sleep quality.

METHODS

We searched for articles published up to January 13, 2022, using the Embase and Medline databases. All observational studies were eligible for inclusion. The Newcastle-Ottawa scale was used to evaluate the risk of bias within studies. We used restricted cubic spline analysis to perform a dose-response analysis.

RESULTS

Seventeen studies with a total of 36,485 participants were included. The pooled odds ratio was 2.28 (confidence interval [CI]: 1.81-2.89; P < .001) and heterogeneity was 80%. In the dose-response analysis conducted on 5 studies, the regression coefficient between daily smartphone usage time (hours/day) and poor sleep quality was 1.042 (1.027-1.058), which confirmed a significantly positive association.

CONCLUSIONS

Smartphone overuse was closely associated with poor self-reported sleep quality, sleep deprivation, and sleep latency prolongation. Further studies using a more structured method and high-quality evidence (cohort or case-control) should be conducted.

SYSTEMATIC REVIEW REGISTRATION

CRD42022303371.

CITATION

Chu Y, Oh Y, Gwon M, et al. Dose-response analysis of smartphone usage and self-reported sleep quality: a systematic review and meta-analysis of observational studies. J Clin Sleep Med. 2023;19(3):621-630.

Reduced Diarrhea Prevalence and Improvements in Handwashing with Soap and Stored Drinking Water Quality Associated with Diarrheal Disease Awareness Measured by Interactive Voice Response Messages in the CHoBI7 Mobile Health Program

The Cholera-Hospital-Based-Intervention-for-7-Days (CHoBI7) mobile health program promotes water, sanitation, and hygiene (WASH) behaviors through interactive voice response (IVR), voice, and text messages to reduce diarrheal diseases in Bangladesh. The objective of this study was to investigate the relationship between responses to CHoBI7 WASH IVR quiz messages and subsequent diarrhea and WASH behaviors. Fourteen CHoBI7 IVR quiz messages on handwashing with soap and treatment of stored water were sent to 517 households with 1,777 participants during the 12-month program period. IVR message responses were classified as correct answer, incorrect answer, no response (did not press 1 or 2), and failed (did not answer the phone). Diarrhea prevalence was assessed through self-reported monthly clinical surveillance visits. Handwashing with soap was assessed by a 5-hour structured observation, and stored water quality was defined by Escherichia coli concentration. Households that responded correctly to a CHoBI7 IVR quiz message had significantly lower odds of diarrhea for all age groups (adults and children) at the subsequent visit 1 month later (odds ratio [OR], 0.73; 95% CI, 0.54-0.98), and significantly greater odds of handwashing with soap after stool-related events (OR, 2.48; 95% CI, 1.12-5.49) and E. coli levels < 100 colony forming units (CFU)/100 mL (World Health Organization high-risk cutoff) in the stored household water (OR, 2.04; 95% CI, 1.25-3.33) compared with households that did not answer CHoBI7 IVR quiz calls. Correct responses to CHoBI7 IVR quizzes were associated with decreased diarrhea prevalence and improved stored drinking water quality and handwashing with soap behaviors at the subsequent visits. These findings suggest engagement in the CHoBI7 mobile health (mHealth) program and awareness of diarrheal disease prevention can reduce diarrhea and facilitate changes in WASH behaviors.

"Leave your smartphone out of bed": quantitative analysis of smartphone use effect on sleep quality

Smartphones have become an integral part of people's everyday lives. Smartphones are used across all household locations, including in the bed at night. Smartphone screens and other displays emit blue light, and exposure to blue light can affect one's sleep quality. Thus, smartphone use prior to bedtime could disrupt the quality of one's sleep, but research lacks quantitative studies on how smartphone use can influence sleep. This study combines smartphone application use data from 75 participants with sleep data collected by a wearable ring. On average, the participants used their smartphones in bed for 322.8 s (5 min and 22.8 s), with an IQR of 43.7-456. Participants spent an average of 42% of their time in bed using their smartphones (IQR of 5.87-55.5%). Our findings indicate that smartphone use in bed has significant adverse effects on sleep latency, awake time, average heart rate, and HR variability. We also find that smartphone use does not decrease sleep quality when used outside of bed. Our results indicate that intense smartphone use alone does not negatively affect well-being. Since all smartphone users do not use their phones in the same way, extending the investigation to different smartphone use types might yield more information than general smartphone use. In conclusion, this paper presents the first investigation of the association between smartphone application use logs and detailed sleep metrics. Our work also validates previous research results and highlights emerging future work.

Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market

Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

Non-ionizing radiation as possible carcinogen

The advent of wireless technologies has revolutionized the way we communicate. The steady upsurge in the use of mobile phone all over the world in the last two decades, while triggered economic growth, has caused substantial damage to the environment, both directly and indirectly. The electromagnetic radiation generated from mobile phones, radio-based stations, and phone towers, high-voltage power lines have been reported which leads to the variety of health scares such as the risk of cancer in human beings and adverse effects in animals, birds, etc. Though the usage of such radiation emitting from mobile phones has risen steeply, there is a lack of proper knowledge about the associated risks. The review provides the latest research evidence based both on in vitro studies, in vivo studies, and possible gaps in our knowledge. Moreover, the present review also summarizes available literature in this subject, reports and studies which will help to form guidelines for its exposure limits to the public.Abbreviations: Continuous Wave: CW; Code Division Multiple Access: CDMA; Global System for Mobile Communications: GSM; Peripheral Blood Mononuclear Cell: PBMC; Radiofrequency: RF; Radiofrequency radiation: RFR; Universal Mobile Telecommunications System: UMTS; Wideband Code Division Multiple Access: WCDMA; Specific Absorption Rate: SAR; National Toxicology Program: NTP; amplitude-modulated or amplitude-modulation: AM; Electromagnetic frequencies: EMF; confidence interval: CI; Gigahertz: GHz; odds ratio: OR; incidence ratio: IR; reactive oxygen species: ROS; specific absorption rate: SAR; International Agency of Research on Cancer: IARC; single-strand breaks: SSB; double-strand breaks: DSB (7,12-Dimethylbenz[a]anthracene): DMBA; Hour: h; international commission on non-ionizing radiation protection: ICNIRP; extremely low frequency: ELFl; microtesla: mT; Gigahertz: GHz; hertz: Hz; decibel: dB; kilometer: Km; Watt per square meter: W/m²; Hour: h; positron emission tomography: PET.

A scoping review of mobile apps for sleep management: User needs and design considerations

Sleep disorders are prevalent nowadays, leading to anxiety, depression, high blood pressure, and other health problems. Due to the proliferation of mobile devices and the development of communication technologies, mobile apps have become a popular way to deliver sleep disorder therapy or manage sleep. This scoping review aims to conduct a systematic investigation of mobile apps and technologies supporting sleep, including the essential functions of sleep apps, how they are used to improve sleep and the facilitators of and barriers to using apps among patients and other stakeholders. We searched articles (2010 to 2022) from Scopus, Web of Science, Science Direct, PubMed, and IEEE Xplore using the keyword sleep apps. In total, 1,650 peer-reviewed articles were screened, and 51 were selected for inclusion. The most frequently provided functions by the apps are sleep monitoring, measuring sleep, providing alarms, and recording sleep using a sleep diary. Several wearable devices have been used with mobile apps to record sleep duration and sleep problems. Facilitators and barriers to using apps were identified, along with the evidence-based design guidelines. Existing studies have proved the initial validation and efficiency of delivering sleep treatment by mobile apps; however, more research is needed to improve the performance of sleep apps and devise a way to utilize them as a therapy tool.

How are Consumer Sleep Technology Data Being Used to Deliver Behavioral Sleep Medicine Interventions? A Systematic Review

BACKGROUND

The rapid growth of consumer sleep technology demonstrates the population's interest in measuring sleep. However, the extent to which these devices can be used in the delivery of behavioral sleep interventions is currently unknown. The objectives of this systematic review were to evaluate the use of consumer sleep technology (wearable and mobile) in behavioral sleep medicine interventions, identify gaps in the literature and potential future directions.

METHODS

We completed a scoping review of studies conducted in adult populations that used consumer sleep tracking technology to deliver sleep-related interventions.

RESULTS

Our initial search returned 4,538 articles and 14 articles met our inclusion/exclusion criteria. Results demonstrated that wearable devices are being used for two main purposes: 1. To deliver treatment for insomnia and 2. Sleep monitoring as part of overall wellness programs. Half of the articles reviewed (n = 7) used consumer sleep technology in a cognitive behavioral therapy for insomnia. The majority of the studies reviewed (n = 10) were fully digital, without human intervention, and only two small studies evaluated interventions delivered with and without a sleep tracking device.

CONCLUSIONS

These studies demonstrate opportunities to utilize consumer sleep trackers in insomnia treatment and wellness programs, but most new and innovative interventions are in the early, feasibility stages. Future research is needed to determine how to leverage wearables to improve existing behavioral sleep treatments and determine how this technology can engage patients and reduce barriers to behavioral sleep medicine interventions.

On the usability of digital sleep interventions in sports

High sleep quality is highly related to better health and peak performance. Nowadays, multiple applications and platforms are available to track activity, to monitor heart rate, or to evaluate sleep quality. While activity tracking and heart rate monitoring are widely used, little is known about the potentials of digital tools to optimize sleep quality. Especially among athletes, who often suffer from reduced sleep quality because of full schedules and high competition performance pressure, interventions to maximize performance by optimizing recovery and sleep quality seem to be promising. In the present paper, we give an overview on existing research focusing on the potentials of digital interventions to enhance sleep quality among athletes. In particular, mindfulness-based digital interventions seem to be promising as they evidently foster high sleep quality and related health and performance patterns. Further, athletes can time- and cost-effectively integrate them into their daily routines. Future research is needed to empirically test the usability of digital features and suitable interventions to optimize sleep.

A feasibility study of a mobile app to treat insomnia

Insomnia is a major public health concern. Sleep restriction therapy (SRT) is an effective behavioral treatment but its delivery is impeded by a shortage of trained clinicians. We developed a mobile app delivering SRT to individuals with insomnia. This feasibility study employed a mixed-methods design to examine the engagement, acceptability, and potential efficacy of the mobile app. Fifteen participants diagnosed with insomnia disorder used the mobile app synchronized with a wearable device for 3 weeks. Those who persisted with the study (n = 12) found the mobile app to be highly acceptable and engaging, logging on average 19 nightly sleep diary entries across the 21 day period. Significant improvements were observed for sleep measures (insomnia severity and sleep efficiency) and daytime symptoms (fatigue and sleepiness). The results suggest that a mobile app delivering SRT to individuals with insomnia is engaging, acceptable, and potentially efficacious. Further, a full-scale effectiveness study is warranted.

Efficacy of an m-Health Physical Activity and Sleep Intervention to Improve Sleep Quality in Middle-Aged Adults: The Refresh Study Randomized Controlled Trial

BACKGROUND

Poor sleep health is highly prevalent. Physical activity is known to improve sleep quality but not specifically targeted in sleep interventions.

PURPOSE

To compare the efficacy of a combined physical activity and sleep intervention with a sleep-only intervention and a wait-list control, for improving sleep quality in middle-aged adults without a diagnosed sleep disorder.

METHODS

Three-arm randomized controlled trial (Physical Activity and Sleep Health (PAS), Sleep Health Only (SO), Wait-list Control (CON) groups; 3-month primary time-point, 6-month follow-up) of 275 (PAS = 110, SO = 110, CON = 55) inactive adults (40-65 years) reporting poor sleep quality. The main intervention component was a smartphone/tablet "app" to aid goal setting and self-monitoring physical activity and/or sleep hygiene behaviors (including stress management), and a pedometer for PAS group. Primary outcome was Pittsburgh Sleep Quality Index (PSQI) global score. Secondary outcomes included several self-reported physical activity measures and PSQI subcomponents. Group differences were examined stepwise, first between pooled intervention (PI = PAS + SO) and CON groups, then between PAS and SO groups.

RESULTS

Compared with CON, PI groups significantly improved PSQI global and subcomponents scores at 3 and 6 months. There were no differences in sleep quality between PAS and SO groups. The PAS group reported significantly less daily sitting time at 3 months and was significantly more likely to report ≥2 days/week resistance training and meeting physical activity guidelines at 6 months than the SO group.

CONCLUSIONS

PIs had statistically significantly improved sleep quality among middle-aged adults with poor sleep quality without a diagnosed sleep disorder. The adjunctive physical activity intervention did not additionally improve sleep quality.

CLINICAL TRIAL INFORMATION

Australian New Zealand Clinical Trial Registry: ACTRN12617000680369; Universal Trial number: U1111-1194-2680; Human Research Ethics Committee, Blinded by request of journal: H-2016-0267.

A Multiple Health Behavior Change, Self-Monitoring Mobile App for Adolescents: Development and Usability Study of the Health4Life App

Background

The link between chronic diseases and the Big 6 lifestyle risk behaviors (ie, poor diet, physical inactivity, smoking, alcohol use, sedentary recreational screen time, and poor sleep) is well established. It is critical to target these lifestyle risk behaviors, as they often co-occur and emerge in adolescence. Smartphones have become an integral part of everyday life, and many adolescents already use mobile apps to monitor their lifestyle behaviors and improve their health. Smartphones may be a valuable platform for engaging adolescents with interventions to prevent key chronic disease risk behaviors.

Objective

The aim of this paper is to describe the development, usability, and acceptability of the Health4Life app, a self-monitoring smartphone app for adolescents that concurrently targets the Big 6 lifestyle behaviors.

Methods

The development of the Health4Life app was an iterative process conducted in collaboration with adolescents and experts. The development process consisted of three stages: scoping the literature; end user consultations, which included a web-based survey (N=815; mean age 13.89, SD 0.89 years) and a focus group (N=12) among adolescents; and app development and beta testing. Following this development work, 232 adolescents were asked to rate the usability and acceptability of the app.

Results

The process resulted in a self-monitoring smartphone app that allows adolescent users to track and set goals for the Big 6 health behaviors, using in-app rewards and notifications to enhance engagement. The overall adolescent feedback was positive in terms of user-friendly design, content, relevance, and helpfulness. Commonly identified areas for improvement were to increase interactive features and display recorded health behaviors differently to improve interpretability.

Conclusions

The Health4Life app is a co-designed, self-monitoring smartphone app for adolescents that concurrently targets the Big 6 lifestyle behaviors. Adolescents rated the app as highly acceptable and usable. The app has the potential to efficiently and effectively modify important risk factors for chronic disease among young people and is currently being evaluated in a world-first trial of 6640 secondary school students in 71 schools across Australia.

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis

This study aimed to explore factors associated with poor quality of sleep in construction workers. This study was cross-sectional, correlational in design and used secondary data from fatigue instrument development study. We analyzed the data from 206 participants aged over 19 years who worked at construction sites for more than 6 months. We used multivariate binary logistic regression to identify the factors associated with poor quality of sleep. We classified the two sleep quality groups based on the Pittsburgh Sleep Quality Index (PSQI) score, and almost 63% of them were classified as the poor quality of sleep group. Based on multivariate binary logistic regression (Cox and Snell R2 = 0.317, Nagelkerke R2 = 0.429), the poor quality of sleep group tended to sleep for a shorter duration before the working day, and not only showed lower sleep latency and higher levels of daytime dysfunction and discomfort in daily life, but also had more chronic disease, depressive symptoms, and higher physical fatigue. Our study findings support that there are many modifiable factors associated with poor sleep and a high rate of poor quality of sleep occurred in construction workers. Thus, clinicians should consider providing diverse options for applying interventions to ensure better sleep, fatigue management, and depression prevention in construction workers after considering their unique characteristics.

Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review

Background

Mobile health (mHealth) apps offer a scalable option for treating sleep disturbances at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based mHealth apps.

Objective

The aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance.

Methods

A systematic search of studies published from the inception of databases through February 2020 was conducted using 5 databases (MEDLINE, Embase, Cochrane Library, PsycINFO, and CINAHL).

Results

A total of 6015 papers were identified using the search strategy. After screening, 15 papers were identified that examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. Most of these apps delivered cognitive behavioral therapy for insomnia (CBT-I, n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only 3 papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only 1 app had available evidence assessing all 4 implementation metrics (ie, acceptability, engagement, usability, and adherence). Most apps were prototype versions (n=5), with few matured apps. A total of 6 apps had supporting papers that provided a quantitative evaluation of clinical outcomes, but only 1 app had a supporting, adequately powered randomized controlled trial.

Conclusions

This is the first systematic review to synthesize and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardization and consistency in the use of best practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation.

Association between the pattern of mobile phone use and sleep quality in Northeast China college students

OBJECTIVES

Currently, mobile penetration is high amongst college students. The aims of this study were to investigate the characteristics of mobile phone use and to explore the influence of mobile phone use characteristics on sleep quality amongst college students.

METHODS

From December 2016 to January 2017, we collected mobile phone use characteristics and sleep quality data using the Pittsburgh Sleep Quality Index (PSQI) and standardised questionnaires that were answered by 4500 medical university students in Liaoning Province (actual response rate of 94%, n = 4234 college students). This study used the SPSS 21.0 software to establish the database and perform the statistical analysis.

RESULTS

One hundred percent of the college students had mobile phones and used mobile phones for entertainment (91%), work (51%), obtaining information (61%), and other purposes (23%). Additionally, there was a statistically significant difference in the PSQI score between students who held the phone at a distance of more than 10 cm from their eyes and those who held it a distance of less than 10 cm (P = 0.002). Multiple logistic regression analysis showed that the risk of poor sleep quality was 1.21-1.53 times higher for those who spent more than 5 h a day using their phones and 1.41-1.59 times higher for those who used their phones for more than half an hour before going to bed when the lights were off.

CONCLUSIONS

Daily cumulative mobile phone use and use with the lights off before sleep are associated with poorer sleep quality.

Radiofrequency radiation: A possible threat to male fertility

Radiofrequency exposure from man-made sources has increased drastically with the era of advanced technology. People could not escape from such RF radiations as they have become the essential part of our routine life such as Wi-Fi, microwave ovens, TV, mobile phones, etc. Although non-ionizing radiations are less damaging than ionizing radiations but its long term exposure effect cannot be avoided. For fertility to be affected, either there is an alteration in germ cell, or its nourishing environment, and RF affects both the parameters subsequently, leading to infertility. This review with the help of in vitro and in vivo studies shows that RF could change the morphology and physiology of germ cells with affected spermatogenesis, motility and reduced concentration of male gametes. RF also results in genetic and hormonal changes. In addition, the contribution of oxidative stress and protein kinase complex after RFR exposure is also summarized which could also be the possible mechanism for reduction in sperm parameters. Further, some preventative measures are described which could help in reverting the radiofrequency effects on germ cells.

Testing a mindfulness meditation mobile app for the treatment of sleep-related symptoms in adults with sleep disturbance: A randomized controlled trial

The objective of this randomized controlled trial was to test whether a commercially available, mindfulness meditation mobile app, (i.e., Calm app), was effective in reducing fatigue (primary outcome), pre-sleep arousal, and daytime sleepiness (secondary outcomes) in adults with sleep disturbance (Insomnia Severity Index Score >10) as compared to a wait-list control group. Associations between the use of the Calm app (i.e., adherence to the intervention) and changes in sleep quality was also explored in the intervention group only. Adults with sleep disturbance were recruited (N = 640). Eligible and consenting participants (N = 263) were randomly assigned to the intervention (n = 124) or a wait-list control (n = 139) group. Intervention participants were asked to meditate using the Calm app ≥10 minutes/day for eight weeks. Fatigue, daytime sleepiness, and pre-sleep arousal were assessed at baseline, mid- (4-weeks) and post-intervention (8-weeks) in both groups, whereas sleep quality was evaluated only in the intervention group. Findings from intent-to-treat analyses suggest the use of the Calm app for eight weeks significantly decreased daytime fatigue (p = .018) as well as daytime sleepiness (p = .003) and cognitive (p = .005) and somatic (p < .001) pre-sleep arousal as compared to the wait-list control group. Within the intervention group, use of the Calm app was associated with improvements in sleep quality (p < .001). This randomized controlled trial demonstrates that the Calm app can be used to treat fatigue, daytime sleepiness, and pre-sleep arousal in adults with sleep disturbance. Given that the Calm app is affordable and widely accessible, these data have implications for community level dissemination of a mobile app to improve sleep-related symptoms associated with sleep disturbance. Trial registration: ClinicalTrials.gov NCT04045275.

Use of the Consumer-Based Meditation App Calm for Sleep Disturbances: Cross-Sectional Survey Study

Background

Over 30% of Americans report regular sleep disturbance, and consumers are increasingly seeking strategies to improve sleep. Self-guided mindfulness mobile apps may help individuals improve their sleep. Despite the recent proliferation of sleep content within commercially available mindfulness apps, there is little research on how consumers are using these apps for sleep.

Objective

We conducted a cross-sectional survey among subscribers to Calm, a popular, consumer-based, mindfulness-based meditation app, and described and compared how good sleepers, poor sleepers, and those with self-reported insomnia use the app for sleep.

Methods

Participants who were paying subscribers of Calm and had used a sleep component of Calm in the last 90 days were invited to complete an investigator-developed survey that included questions about sleep disturbance and the use of Calm for sleep. Based on self-reports of sleep disturbances and of insomnia diagnosis, participants were categorized as “good sleepers,” “poor sleepers,” or “those with insomnia diagnosis.” Chi-square tests compared reasons for downloading the app and usage patterns across participants with and without sleep disturbance.

Results

There was a total of 9868 survey respondents. Approximately 10% of participants (1008/9868, 10.21%) were good sleepers, 78% were poor sleepers (7565/9868, 77.66%), and 11% reported a diagnosis of insomnia (1039/9868, 10.53%). The sample was mostly White (8185/9797, 83.55%), non-Hispanic (8929/9423, 94.76%), and female (8166/9578, 85.26%). The most common reasons for sleep disturbances were racing thoughts (7084/8604, 82.33%), followed by stress or anxiety (6307/8604, 73.30%). Poor sleepers and those with insomnia were more likely than good sleepers to have downloaded Calm to improve sleep (χ²₂=1548.8, P<.001), reduce depression or anxiety (χ²₂=15.5, P<.001), or improve overall health (χ²₂=57.6, P<.001). Respondents with insomnia used Calm most often (mean 5.417 days/week, SD 1.936), followed by poor sleepers (mean 5.043 days/week, SD 2.027; F₂=21.544, P<.001). The most common time to use Calm was while lying down to sleep (7607/9686, 78.54%), and bedtime use was more common among poor sleepers and those with insomnia (χ²₂=382.7, P<.001). Compared to good and poor sleepers, those with insomnia were more likely to use Calm after waking up at night (χ²₂=410.3, P<.001). Most participants tried to use Calm on a regular basis (5031/8597, 58.52%), but regular nighttime use was most common among those with insomnia (646/977, 66.1%), followed by poor sleepers (4040/6930, 58.30%; χ²₂=109.3, P<.001).

Conclusions

Of the paying subscribers to Calm who have used one of the sleep components, approximately 90% have sleep difficulties, and 77% started using Calm primarily for sleep. These descriptive data point to areas of focus for continued refinement of app features and content, followed by prospective trials testing efficacy of consumer-based meditation mobile apps for improving sleep.

Myofunctional Therapy App for Severe Apnea-Hypopnea Sleep Obstructive Syndrome: Pilot Randomized Controlled Trial

Background

Myofunctional therapy has demonstrated efficacy in treating sleep-disordered breathing. We assessed the clinical use of a new mobile health (mHealth) app that uses a smartphone to teach patients with severe obstructive sleep apnea–hypopnea syndrome (OSAHS) to perform oropharyngeal exercises.

Objective

We conducted a pilot randomized trial to evaluate the effects of the app in patients with severe OSAHS.

Methods

Forty patients with severe OSAHS (apnea–hypoxia index [AHI]>30) were enrolled prospectively and randomized into an intervention group that used the app for 90 sessions or a control group. Anthropometric measures, Epworth Sleepiness Scale (0-24), Pittsburgh Sleep Quality Index (0-21), Iowa Oral Performance Instrument (IOPI) scores, and oxygen desaturation index were measured before and after the intervention.

Results

After the intervention, 28 patients remained. No significant changes were observed in the control group; however, the intervention group showed significant improvements in most metrics. AHI decreased by 53.4% from 44.7 (range 33.8-55.6) to 20.88 (14.02-27.7) events/hour (P<.001). The oxygen desaturation index decreased by 46.5% from 36.31 (27.19-43.43) to 19.4 (12.9-25.98) events/hour (P=.003). The IOPI maximum tongue score increased from 39.83 (35.32-45.2) to 59.06 (54.74-64.00) kPa (P<.001), and the IOPI maximum lip score increased from 27.89 (24.16-32.47) to 44.11 (39.5-48.8) kPa (P<.001). The AHI correlated significantly with IOPI tongue and lip improvements (Pearson correlation coefficient −0.56 and −0.46, respectively; both P<.001). The Epworth Sleepiness Scale score decreased from 10.33 (8.71-12.24) to 5.37 (3.45-7.28) in the app group (P<.001), but the Pittsburgh Sleep Quality Index did not change significantly.

Conclusions

Orofacial exercises performed using an mHealth app reduced OSAHS severity and symptoms, and represent a promising treatment for OSAHS.

Trial Registration

Spanish Registry of Clinical Studies AWGAPN-2019-01, ClinicalTrials.gov NCT04438785; https://clinicaltrials.gov/ct2/show/NCT04438785

Effects of a wearable technology-based physical activity intervention on sleep quality in breast cancer survivors: the ACTIVATE Trial

INTRODUCTION

Physical activity interventions can improve sleep quality in breast cancer survivors. This paper examines the effects of the ACTIVATE Trial, a wearable-based physical activity intervention (Garmin Vivofit2® coupled with behavioral feedback, goal setting, and health coaching) on sleep outcomes.

METHODS

Post-primary treatment, inactive, postmenopausal breast cancer survivors were recruited and randomized to primary intervention or waitlist. Wrist-worn actigraphy (sleep onset latency, SOL; total sleep time, TST; sleep efficiency, SE; wake after sleep onset, WASO; and number of awakenings, NWAKE) and questionnaire-derived sleep measures (Pittsburgh Sleep Quality Index) were assessed at baseline (T1), 12 weeks (end of primary intervention and start of waitlist intervention, T2), and at 24 weeks (T3).

RESULTS

Eighty-three women (mean age = 62 years) were randomized; trial retention was 94% at T2 and 87% at T3. At T2, primary intervention participants had greater improvements in WASO (- 5.7 min, 95% CI - 11.7 to - 0.2) and NWAKE compared with the waitlist arm (- 2.0, 95% CI - 3.6 to - 0.4). At T3, within-group improvements were observed for SE (both groups), WASO (both groups), NWAKE (primary intervention group only), total PSQI score (primary intervention group), and sleep efficacy (primary intervention group).

CONCLUSIONS

The intervention reduced actigraphy-measured sleep disturbances. Within-group analyses suggest that improvements in sleep quality are sustained over a longer duration, and there may be similar benefits from an abridged intervention (wearable device only). Actigraphy-measured effects appeared stronger in participants who were poor sleepers at study entry.

IMPLICATIONS FOR CANCER SURVIVORS

Wearable technology can increase physical activity and improve sleep for breast cancer survivors.

Process evaluation for the delivery of a water, sanitation and hygiene mobile health program: findings from the randomised controlled trial of the CHoBI7 mobile health program

OBJECTIVE

The Cholera-Hospital-Based Intervention for 7-days (CHoBI7) mobile health (mHealth) program delivers mobile messages to diarrhoea patient households promoting water treatment and handwashing with soap. The randomised controlled trial (RCT) of the CHoBI7 mHealth program demonstrated this intervention was effective in significantly reducing diarrhoea and stunting amoung young children. The objective of this study was to assess the implementation of the CHoBI7 mHealth program in delivering mHealth messages during this RCT.

METHODS

517 diarrhoea patient households with 1777 participants received weekly text, voice and interactive voice response (IVR) messages from the CHoBI7 mHealth program over the 12-month program period. The program process evaluation indicators were the following: the percentage of CHoBI7 mHealth messages received and fully listened to by program households (program fidelity and dose), and household members reporting receiving and sharing an mHealth message from the program in the past two weeks (program reach).

RESULTS

Ninety two percent of text messages were received by program households. Eighty three percent of voice and 86% of IVR messages sent were fully listened to by at least one household member. Eighty one percent of IVR quiz responses from households were answered correctly. Program households reported receiving a CHoBI7 mHealth message in the past two weeks at 79% of monthly household visits during the 12-month program. Seventy seven percent of participants reported sharing a program message with a spouse, 55% with a neighbour and 49% with a child during the program period.

CONCLUSION

There was high fidelity, dose and reach of mobile messages delivered for the CHoBI7 mHealth program. This study presents an approach for process evaluation that can be implemented to evaluate future mHealth programs.

The future of sleep health: a data-driven revolution in sleep science and medicine

In recent years, there has been a significant expansion in the development and use of multi-modal sensors and technologies to monitor physical activity, sleep and circadian rhythms. These developments make accurate sleep monitoring at scale a possibility for the first time. Vast amounts of multi-sensor data are being generated with potential applications ranging from large-scale epidemiological research linking sleep patterns to disease, to wellness applications, including the sleep coaching of individuals with chronic conditions. However, in order to realise the full potential of these technologies for individuals, medicine and research, several significant challenges must be overcome. There are important outstanding questions regarding performance evaluation, as well as data storage, curation, processing, integration, modelling and interpretation. Here, we leverage expertise across neuroscience, clinical medicine, bioengineering, electrical engineering, epidemiology, computer science, mHealth and human-computer interaction to discuss the digitisation of sleep from a inter-disciplinary perspective. We introduce the state-of-the-art in sleep-monitoring technologies, and discuss the opportunities and challenges from data acquisition to the eventual application of insights in clinical and consumer settings. Further, we explore the strengths and limitations of current and emerging sensing methods with a particular focus on novel data-driven technologies, such as Artificial Intelligence.

Greenspace exposure and sleep: A systematic review

Green space is considered a critical environmental factor for sleep quality and quantity. However, no systematic review exploring this relationship exists. The purpose of this systematic review was to 1) explore research related to green space and sleep, and 2) examine the impact of green space exposure on sleep quality and quantity. Papers from eight electronic databases were eligible for inclusion if they met the following criteria: well-designed, any analysis exploring green space and sleep, provided sleep and green space measurement, published in peer-reviewed journals, and written in English. Thirteen eligible studies related to green space and sleep were selected after peer-review procedures. Cross-sectional studies (n = 7) used either a questionnaire or the combination of Geographic Information Systems and remote sensing images for green space measurement, while questionnaires were primarily used to measure both sleep quality and quantity. Intervention studies (n = 5) were categorized into three types: walking program, gardening, and working in a forest. Eleven out of thirteen studies concluded that green space exposure was associated with improvement in both sleep quality and quantity. The findings support the evidence of a positive association between green space exposures and sleep quality and quantity, and also suggest green exercise and therapeutic gardening as possible intervention methods to improve sleep outcomes.

Usefulness of a Lifestyle Intervention in Patients With Cardiovascular Disease

The importance of modifying lifestyle factors in order to improve prognosis in cardiac patients is well-known. Current study aims to evaluate the effects of a lifestyle intervention on changes in lifestyle- and health data derived from wearable devices. Cardiac patients from Spain (n = 34) and The Netherlands (n = 36) were included in the current analysis. Data were collected for 210 days, using the Fitbit activity tracker, Beddit sleep tracker, Moves app (GPS tracker), and the Careportal home monitoring system. Locally Weighted Error Sum of Squares regression assessed trajectories of outcome variables. Linear Mixed Effects regression analysis was used to find relevant predictors of improvement deterioration of outcome measures. Analysis showed that Number of Steps and Activity Level significantly changed over time (F = 58.21, p < 0.001; F = 6.33, p = 0.01). No significant changes were observed on blood pressure, weight, and sleep efficiency. Secondary analysis revealed that being male was associated with higher activity levels (F = 12.53, p < 0.001) and higher number of steps (F = 8.44, p < 0.01). Secondary analysis revealed demographic (gender, nationality, marital status), clinical (co-morbidities, heart failure), and psychological (anxiety, depression) profiles that were associated with lifestyle measures. In conclusion results showed that physical activity increased over time and that certain subgroups of patients were more likely to have a better lifestyle behaviors based on their demographic, clinical, and psychological profile. This advocates a personalized approach in future studies in order to change lifestyle in cardiac patients.

Promoting healthy teenage behaviour across three European countries through the use of a novel smartphone technology platform, PEGASO fit for future: study protocol of a quasi-experimental, controlled, multi-Centre trial

BACKGROUND

Behaviour change interventions targeting physical activity, diet, sleep and sedentary behaviour of teenagers show promise when delivered through smartphones. However, to date there is no evidence of effectiveness of multicomponent smartphone-based interventions. Utilising a user-centred design approach, we developed a theory-based, multi-dimensional system, PEGASO Fit For Future (PEGASO F4F), which exploits sophisticated game mechanics involving smartphone applications, a smartphone game and activity sensors to motivate teenagers to take an active role in adopting and maintaining a healthy lifestyle. This paper describes the study protocol to assess the feasibility, usability and effectiveness (knowledge/awareness and behavioural change in lifestyle) of the PEGASO system.

METHODS

We are conducting a quasi-experimental controlled cluster trial in 4 sites in Spain, Italy, and UK (England, Scotland) over 6 months. We plan to recruit 525, in a 2:1 basis, teenagers aged 13-16 years from secondary schools. The intervention group is provided with the PEGASO system whereas the comparison group continues their usual educational routine. Outcomes include feasibility, acceptance, and usability of the PEGASO system as well as between and within group changes in motivation, self-reported diet, physical activity, sedentary and sleeping behaviour, anthropometric measures and knowledge about a healthy lifestyle.

DISCUSSION

PEGASO F4F will provide evidence into the cross-cultural similarities and differences in the feasibility, acceptability and usability of a multi-dimensional smartphone based behaviour change intervention for teenagers. The study will explore facilitating factors, challenges and barriers of engaging teenagers to adapt and maintain a healthy lifestyle when using smartphone technology. Positive results from this ICT based multi component intervention may have significant implications both at clinical level, improving teenagers health and at public health level since it can present an influential tool against the development of chronic disease during adulthood.

TRIAL REGISTRATION

https://clinicaltrials.gov Registration number: NCT02930148, registered 4 October 2016.

A Narrative Review of the Literature on Insufficient Sleep, Insomnia, and Health Correlates in American Indian/Alaska Native Populations

Insufficient sleep and insomnia promote chronic disease in the general population and may combine with social and economic factors to increase rates of chronic health conditions among AI/AN people. Given that insufficient sleep and insomnia can be addressed via behavioral interventions, it is critical to understand the prevalence and correlates of these disorders among AI/AN individuals in order to elucidate the mechanisms associated with health disparities and provide guidance for subsequent treatment research and practice. We reviewed the available literature on insufficient sleep and insomnia in the AI/AN population. PubMed, PsycINFO, Google Scholar, and ProQuest were searched between June 12th and October 28th of 2018. Prevalence of insufficient sleep ranged from 15% to 40%; insomnia prevalence ranged from 25% to 33%. Insufficient sleep was associated with unhealthy diet, low physical activity levels, higher BMI, worse self-reported health, increased risk for diabetes mellitus, cardiovascular disease, frequent mental distress, smoking, binge drinking, depression, and chronic pain. Insomnia was associated with depression, childhood abuse, PTSD, anxiety, alcohol use, low social support, and low trait-resilience levels. Research on evidence-based treatment and implementation practices targeting insufficient sleep and insomnia was lacking, and only one study described the development/validation of a measure of insufficient sleep among AI/AN people. There is a need for rigorous sleep research including testing and implementation of evidence-based treatment for insufficient sleep and insomnia in this population in an effort to help eliminate health disparities. We present recommendations for research and clinical practice based on the current review.

Exploring User Needs and Preferences for Mobile Apps for Sleep Disturbance: Mixed Methods Study

BACKGROUND

Mobile health (mHealth) apps demonstrate promise for improving sleep at scale. End-user engagement is a prerequisite for sustained use and effectiveness.

OBJECTIVE

We assessed the needs and preferences of those with poor sleep and insomnia to inform the development of an engaging sleep app.

METHODS

We triangulated results from qualitative (focus groups and app reviews) and quantitative (online survey) approaches. A total of 2 focus groups were conducted (N=9). An online survey tested themes identified from the focus groups against a larger population (N=167). In addition, we analyzed 434 user reviews of 6 mobile apps available on app stores.

RESULTS

Common focus group themes included the need to account for diverse sleep phenotypes with an adaptive and tailored program, key app features (alarms and sleep diaries), the complex yet condescending nature of existing resources, providing rationale for information requested, and cost as a motivator. Most survey participants (156/167, 93%) would try an evidence-based sleep app. The most important app features reported were sleep diaries (148/167, 88%), sharing sleep data with a doctor (116/167, 70%), and lifestyle tracking (107/167, 64%). App reviews highlighted the alarm as the most salient app feature (43/122, 35%) and data synchronization with a wearable device (WD) as the most commonly mentioned functionality (40/135, 30%).

CONCLUSIONS

This co-design process involving end users through 3 methods consistently highlighted sleep tracking (through a diary and WD), alarms, and personalization as vital for engagement, although their implementation was commonly criticized in review. Engagement is negatively affected by poorly designed features, bugs, and didactic information which must be addressed. Other needs depend upon the type of user, for example, those with severe insomnia.

Feasibility and effectiveness assessment of a mobile application for subhealth management: Study protocol for a randomized controlled trial

INTRODUCTION

Mibyeongbogam (MBBG) is a mobile application developed for subhealth status self-management in the Republic of Korea. It aims to assess a user's subhealth status, and then to recommend relevant traditional Korean medicine (TKM)-based health-promoting strategies. The purpose of this study is to evaluate the feasibility and effectiveness of MBBG's employment for the subhealth management of general healthy adults.

METHODS

This is a prospective, open-label, parallel group, randomized controlled trial that will seek to enroll 150 healthy adults, aged 30 to 49 years old, from 2 hospitals in the Republic of Korea. The eligible participants will then be randomly allocated to either the MBBG or control group, at a 1:1 allocation ratio. The MBBG group will use the application for 12 weeks, while the control group will undergo no intervention. The awareness of subhealth status will be primarily assessed. Health promoting behaviors, quality of life, TKM-based health questionnaires, and physical examination results will be assessed as secondary outcomes.

DISCUSSION

The primary endpoint will be tested with a 2-sample t test, or a Wilcoxon rank sum test. Any other continuous variables will be tested via an analysis of covariance, while categorical variables will be tested by a Chi-squared or Fisher exact test. Repeated measure analysis of variance will be performed to explore any in-group differences. The results will be addressed with a 95% confidence interval. We expect that MBBG will be the 1st TKM-based mobile application to be feasible for primary care in subhealth management.

TRIAL REGISTRATION

CRIS (Clinical Research Information Service), KCT0003488, February 11, 2019.

An Activity Tracker and Its Accompanying App as a Motivator for Increased Exercise and Better Sleeping Habits for Youths in Need of Social Care: Field Study

Background

The number of mobile self-tracking devices connected to the Web has exploded in today’s society. With these wearable activity trackers related to Web 2.0 apps and social media have come new ways of monitoring, measuring, representing, and sharing experiences of the human body. New opportunities related to health and new areas of implementation for professionals have appeared, and one identified area that can benefit from mobile health technologies is social work.

Objective

There are still only a small number of papers reporting the results from studying wearable activity trackers and accompanying apps in the context of agency-based social work. This study aimed to contribute to the identified shortage by presenting results from a research project framed by the following overarching question: What effects will the studied youths in need of social care experience in relation to exercise and sleep as the result of using a wearable activity tracker and its accompanying app?

Methods

A field study framed by action research was performed. The study concerned vulnerable youths living in a Swedish municipality’s care and accommodation home that tried out an activity tracker and its accompanying app.

Results

The results from the study confirm previously published research results reporting that instant graphical feedback, sharing information, and being part of a social community can have a positive impact on lifestyle changes. In addition, this study’s main results are that (1) the most important factor for positive health-related lifestyle changes was the establishment of personal long-term goals and (2) professional social workers found the studied technology to function as a valuable counseling tool, opening up avenues for lifestyle talks that otherwise were hard to undertake.

Conclusions

This study demonstrates how an activity tracker and its accompanying app can open up a topic for discussion regarding how vulnerable youths can achieve digital support for changing unhealthy lifestyle patterns, and it shows that the technology might be a valuable counseling tool for professionals in social work.

Parents' Perspectives on the Theoretical Domains Framework Elements Needed in a Pediatric Health Behavior App: A Crowdsourced Social Validity Study

Background

Most pediatric studies do not include parent stakeholders in the design of the intervention itself and many pediatric mobile health (mHealth) interventions are not meaningfully disseminated after the trial period ends. Consequently, the consumer desire for mobile apps targeting pediatric health behavior is likely to be met by commercial products that are not based in theory or evidence and may not take stakeholder preferences into account.

Objective

The aim was to assess parent preference for mobile app features that map onto specific Theoretical Domains Framework (TDF) elements.

Methods

This study was a crowdsourced social validity study of 183 parents who were asked to rate their preferences for mobile app features that correspond to elements of the TDF. The TDF organizes a large number of theoretical models and constructs into three components: (1) capability, (2) motivation, and (3) opportunity. Parents of children were recruited through Amazon Mechanical Turk.

Results

The majority of participants were Caucasian and mean age was 36.9 (SD 8.0) years. Results revealed broad acceptability of communication, motivation, and opportunity domains. However, the degree to which each domain was valued varied within behavioral category. Parents demonstrated a preference for increasing procedural knowledge for physical activity and diet behaviors over sleep (F_2,545=5.18, P=.006). Similarly, parents valued self-monitoring as more important for physical activity than sleep (F_2,546=4.04, P=.02). When asked about the value of features to help children develop skills, parents preferred those features for dietary behavior over sleep (F_2,546=3.57, P=.03). Parents perceived that goal-setting features would be most useful for physical activity over sleep and diet (F_2,545=5.30, P=.005). Incentive features within the app were seen as most useful for physical activity over sleep (F_2,546=4.34, P=.01).

Conclusions

This study presents a low-cost strategy for involving a large number of stakeholders in the discussion of how health behavior theory should be applied in a mHealth intervention. Our approach is innovative in that it took a scientific framework (ie, TDF) and made it digestible to parents so that they could then provide their opinions about features that might appear in a future app. Our survey items discriminated between various health behaviors allowing stakeholders to communicate the different health behaviors that they would like a TDF feature to change. Moreover, we were able to develop a set of consumer opinions about features that were directly linked to elements of the TDF.

The Role of Integrated Primary Care in Increasing Access to Effective Psychotherapies in the Veterans Health Administration

American military veterans have higher rates of psychiatric disorders, and timely access to high-quality mental health treatment in the Veterans Health Administration (VHA) is a persistent challenge. Integrated primary care (IPC) is one of many strategies implemented by VHA to increase access to care. IPC, including collaborative care and primary care behavioral health services, successfully increases access to initial behavioral health services in primary care (e.g., brief psychotherapies, pharmacotherapy) and continued engagement in specialty mental health services. IPC components that drive increased access include population-based care, response to patient preferences, and team-based care. The state of the evidence for IPC interventions for common behavioral health concerns in primary care (depression, anxiety, posttraumatic stress disorder, alcohol use, tobacco use, and insomnia) is reviewed, with areas for future research and implementation discussed, including how technology can assist IPC services and the importance of incorporating evidence-based psychotherapies into IPC.

Evaluation of an Internet-Based Behavioral Intervention to Improve Psychosocial Health Outcomes in Children With Insomnia (Better Nights, Better Days): Protocol for a Randomized Controlled Trial

Background

Up to 25% of 1- to 10-year-old children experience insomnia (ie, resisting bedtime, trouble falling asleep, night awakenings, and waking too early in the morning). Insomnia can be associated with excessive daytime sleepiness and negative effects on daytime functioning across multiple domains (eg, behavior, mood, attention, and learning). Despite robust evidence supporting the effectiveness of behavioral treatments for insomnia in children, very few children with insomnia receive these treatments, primarily due to a shortage of available treatment resources.

Objective

The Better Nights, Better Days (BNBD) internet-based program provides a readily accessible electronic health (eHealth) intervention to support parents in providing evidence-based care for insomnia in typically developing children. The purpose of the randomized controlled trial (RCT) is to evaluate the effectiveness of BNBD in treating insomnia in children aged between 1 and 10 years.

Methods

BNBD is a fully automated program, developed based on evidence-based interventions previously tested by the investigators, as well as on the extant literature on this topic. We describe the 2-arm RCT in which participants (500 primary caregivers of children with insomnia residing in Canada) are assigned to intervention or usual care.

Results

The effects of this behavioral sleep eHealth intervention will be assessed at 4 and 8 months postrandomization. Assessment includes both sleep (actigraphy, sleep diary) and daytime functioning of the children and daytime functioning of their parents. Results will be reported using the standards set out in the Consolidated Standards of Reporting Trials statement.

Conclusions

If the intervention is supported by the results of the RCT, we plan to commercialize this program so that it is sustainable and available at a low cost to all families with internet access.

Trial Registration

ClinicalTrials.gov NCT02243501; https://clinicaltrials.gov/show/NCT02243501 (Archived by WebCite at http://www.webcitation.org/6x8Z5pBui)

Randomised controlled trial using a theory-based m-health intervention to improve physical activity and sleep health in adults: the Synergy Study protocol

INTRODUCTION

There is a need to reduce physical inactivity and poor sleep health in the adult population to decrease chronic disease rates and the associated burden. Given the high prevalence of these risk behaviours, effective interventions with potential for wide reach are warranted.

METHODS AND ANALYSIS

The aim of this two-arm RCT will be to test the effect of a three month personalised mobile app intervention on two main outcomes: minutes of moderate-to-vigorous-intensity physical activity and overall sleep quality. In addition, between-group changes in health-related quality of life and mental health status will be assessed as secondary outcomes. The pre-specified mediators and moderators include social cognitive factors, the neighbourhood environment, health (BMI, depression, anxiety, stress), sociodemographic factors (age, gender, education) and app usage. Assessments will be conducted after three months (primary endpoint) and six months (follow-up). The intervention will provide access to a specifically developed mobile app, through which participants can set goals for active minutes, daily step counts, resistance training, sleep times and sleep hygiene practice. The app also allows participants to log their behaviours daily and view progress bars as well as instant feedback in relation to goals. The personalised support system will consist of weekly summary reports, educational and instructional materials, prompts on disengagement and weekly facts.

ETHICS AND DISSEMINATION

The Human Research Ethics Committee of The University of Newcastle, Australia granted full approval: H-2016-0181. This study will assess the efficacy of a combined behaviour intervention, mechanisms of behaviour change and gather high-quality process data, all of which will help refine future trials. Dissemination of findings will include publication in a peer-reviewed journal and presentation at national or international conferences. Participants will receive a plain English summary report of results.

TRIAL REGISTRATION NUMBER

ACTRN12617000376347; Pre-results.