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Simple Summary: Mobile applications in clinical treatment are becoming increasingly popular among cancer patients and survivors. The COVID-19 pandemic demonstrated the importance of digital interventions in patient monitoring. We conducted a scoping review and classified Mobile Health (mHealth) trials into sub-groups based on intervention methodologies, lifestyle variables, and their effectiveness on cancer health outcomes. Our study identified the key elements of the mHealth approach for cancer care, including interactive support, personalized suggestions, active participation of users, wearable technology and rigorous theory-based solutions. We also established a taxonomy that can be employed by application developers and medical specialists in developing future mHealth cancer care solutions. Mobile Health (mHealth) has a great potential to enhance the self-management of cancer patients and survivors. Our study aimed to perform a scoping review to evaluate the impact and trends of mobile application-based interventions on adherence and their effects on health outcomes among the cancer population. In addition, we aimed to develop a taxonomy of mobile-app-based interventions to assist app developers and healthcare researchers in creating future mHealth cancer care solutions. Relevant articles were screened from the online databases PubMed, EMBASE, and Scopus, spanning the time period from 1 January 2016 to 31 December 2022. Of the 4135 articles initially identified, 55 were finally selected for the review. In the selected studies, breast cancer was the focus of 20 studies (36%), while mixed cancers were the subject of 23 studies (42%). The studies revealed that the usage rate of mHealth was over 80% in 41 of the 55 studies, with factors such as guided supervision, personalized suggestions, theoretical intervention foundations, and wearable technology enhancing adherence and efficacy. However, cancer progression, technical challenges, and unfamiliarity with devices were common factors that led to dropouts. We also proposed a taxonomy based on diverse theoretical foundations of mHealth interventions, delivery methods, psycho-educational programs, and social platforms. We suggest that future research should investigate, improve, and verify this taxonomy classification to enhance the design and efficacy of mHealth interventions. [ABSTRACT FROM AUTHOR]

Background: Stress and anxiety are psychophysiological responses commonly experienced by patients during the perioperative process that can increase presurgical and postsurgical complications to a comprehensive and positive recovery. Preventing and intervening in stress and anxiety can help patients achieve positive health and well-being outcomes. Similarly, the provision of education about surgery can be a crucial component and is inversely correlated with preoperative anxiety levels. However, few patients receive stress and anxiety relief support before surgery, and resource constraints make face-to-face education sessions untenable. Digital health interventions can be helpful in empowering patients and enhancing a more positive experience. Digital health interventions have been shown to help patients feel informed about the possible benefits and risks of available treatment options. However, they currently focus only on providing informative content, neglecting the importance of personalization and patient empowerment. Objective: This study aimed to explore the feasibility of a digital health intervention called the Adhera CARINAE Digital Health Program, designed to provide evidence-based, personalized stress- and anxiety-management methods enabled by a comprehensive digital ecosystem that incorporates wearable, mobile, and virtual reality technologies. The intervention program includes the use of advanced data-driven techniques for tailored patient education and lifestyle support. Methods: The trial will include 5 hospitals across 3 European countries and will use a randomized controlled design including 30 intervention participants and 30 control group participants. The involved surgeries are cardiopulmonary and coronary artery bypass surgeries, cardiac valve replacement, prostate or bladder cancer surgeries, hip and knee replacement, maxillofacial surgery, or scoliosis. The control group will receive standard care, and the intervention group will additionally be exposed to the digital health intervention program. Results: The recruitment process started in January 2022 and has been completed. The primary impact analysis is currently ongoing. The expected results will be published in early 2023. Conclusions: This manuscript details a comprehensive protocol for a study that will provide valuable information about the intervention program, such as the measurement of comparative intervention effects on stress; anxiety and pain management; and usability by patients, caregivers, and health care professionals. This will contribute to the evidence planning process for the future adoption of diverse digital health solutions in the field of surgery. [ABSTRACT FROM AUTHOR]

Background: COVID-19 pandemic has revealed the weaknesses of most health systems around the world, collapsing them and depleting their available health care resources. Fortunately, the development and enforcement of specific public health policies, such as vaccination, mask wearing, and social distancing, among others, has reduced the prevalence and complications associated with COVID-19 in its acute phase. However, the aftermath of the global pandemic has called for an efficient approach to manage patients with long COVID-19. This is a great opportunity to leverage on innovative digital health solutions to provide exhausted health care systems with the most cost-effective and efficient tools available to support the clinical management of this population. In this context, the SENSING-AI project is focused on the research toward the implementation of an artificial intelligence-driven digital health solution that supports both the adaptive self-management of people living with long COVID-19 and the health care staff in charge of the management and follow-up of this population. Objective: The objective of this protocol is the prospective collection of psychometric and biometric data from 10 patients for training algorithms and prediction models to complement the SENSING-AI cohort. Methods: Publicly available health and lifestyle data registries will be consulted and complemented with a retrospective cohort of anonymized data collected from clinical information of patients diagnosed with long COVID-19. Furthermore, a prospective patient-generated data set will be captured using wearable devices and validated patient-reported outcomes questionnaires to complement the retrospective cohort. Finally, the 'Findability, Accessibility, Interoperability, and Reuse' guiding principles for scientific data management and stewardship will be applied to the resulting data set to encourage the continuous process of discovery, evaluation, and reuse of information for the research community at large. Results: The SENSING-AI cohort is expected to be completed during 2022. It is expected that sufficient data will be obtained to generate artificial intelligence models based on behavior change and mental well-being techniques to improve patients' self-management, while providing useful and timely clinical decision support services to health care professionals based on risk stratification models and early detection of exacerbations. Conclusions: SENSING-AI focuses on obtaining high-quality data of patients with long COVID-19 during their daily life. Supporting these patients is of paramount importance in the current pandemic situation, including supporting their health care professionals in a cost-effective and efficient management of long COVID-19. [ABSTRACT FROM AUTHOR]

Pediatric growth hormone (GH) deficiency is a licensed indication for replacement therapy with recombinant human growth hormone (r-hGH). Treatment, consisting of daily subcutaneous injections, extends from the time of diagnosis until cessation of linear growth at completion of puberty. Suboptimal adherence to r-hGH therapy is common and has been well documented to substantially impair the growth response and achievement of the optimal goal which is attainment of adult height within the genetic target range. The causes of poor adherence are complex and include disease-, patient-, doctor-, and treatment-related factors. Interventions for suboptimal adherence are important for a long-term successful outcome and can include both face-to-face and digital strategies. Face-to-face interventions include behavioral change approaches such as motivational interviewing and non-judgmental assessment. Medical and nursing staff require training in these techniques. Digital solutions are rapidly advancing as evidenced by the electronic digital auto-injector device, easypod® (Merck Healthcare KGaA, Darmstadt, Germany), which uses the web-based easypod® connect platform allowing adherence data to be transmitted electronically to healthcare professionals (HCPs), who can then access GH treatment history, enhancing clinical decisions. Over the past 10 years, the multi-national Easypod® Connect Observational Study has reported high levels of adherence (> 85%) from up to 40 countries. The easypod® connect system can be supported by a smartphone app, growlink™, which facilitates the interactions between the patients, their care team, and patient support services. HCPs are empowered by new digital techniques, however, the human–digital partnership remains essential for optimal growth management. The pediatric patient on r-hGH therapy will benefit from these innovations to enhance adherence and optimize long-term response. [ABSTRACT FROM AUTHOR]

Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): it selected random messages from a subset matching the users' demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): it selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one's own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles. [ABSTRACT FROM AUTHOR]

In recent years there has been growing research on the combination of evidence-based behavioral change techniques with mobile-based recommender systems. In this paper, we have focused on understanding the psychological burdens experienced by caregivers of children undergoing growth hormone treatment (GHt) and the perceived barriers to and drivers of the adoption of a digital health solution. This is a mixed-methods formative research study looking into technical acceptance aspects of using digital health for the emotional support of parents of children undergoing GHt. After one month using the ADHERA CARING platform (Adhera Health, Inc., Palo Alto, CA), individual semi-structured interviews were conducted. ADHERA CARING provides tailored emotional and self-management support to caregivers of children undergoing GHt to improve adherence to treatment through positive education, personalized motivational messages, and emotional support. A preliminary thematic analysis and categorization were carried out, based on the Behavioral Intervention Technology (BIT) model. The majority of participants were female. All caregivers positively valued having the tool, especially at the beginning of treatment. Information provided in the educational module was useful and improved self-efficacy. Motivational messages contributed to commitment and reinforced the educational content, thus promoting continuity of treatment and potentially improving treatment efficacy. Most participants (n=10, 80%) accessed all educational units and completed all the 27 quiz questions. Regarding the motivational messages, the overall average rating was 4.55 out of 5.00. ADHERA CARING has the potential to help caregivers to understand the treatment journey. Nevertheless, users have identified that some types of educational content are more valuable at specific stages of the treatment journey, which suggests that personalization of educational content is required to adapt to different stages of the patient journey. [ABSTRACT FROM AUTHOR]

In recent years there has been growing research on the combination of evidence-based behavioral change techniques with mobile-based recommender systems. In this paper, we have focused on understanding the psychological burdens experienced by caregivers of children undergoing growth hormone treatment (GHt) and the perceived barriers to and drivers of the adoption of a digital health solution. This is a mixed-methods formative research study looking into technical acceptance aspects of using digital health for the emotional support of parents of children undergoing GHt. After one month using the ADHERA CARING platform (Adhera Health, Inc., Palo Alto, CA), individual semi-structured interviews were conducted. ADHERA CARING provides tailored emotional and self-management support to caregivers of children undergoing GHt to improve adherence to treatment through positive education, personalized motivational messages, and emotional support. A preliminary thematic analysis and categorization were carried out, based on the Behavioral Intervention Technology (BIT) model. The majority of participants were female. All caregivers positively valued having the tool, especially at the beginning of treatment. Information provided in the educational module was useful and improved self-efficacy. Motivational messages contributed to commitment and reinforced the educational content, thus promoting continuity of treatment and potentially improving treatment efficacy. Most participants (n=10, 80%) accessed all educational units and completed all the 27 quiz questions. Regarding the motivational messages, the overall average rating was 4.55 out of 5.00. ADHERA CARING has the potential to help caregivers to understand the treatment journey. Nevertheless, users have identified that some types of educational content are more valuable at specific stages of the treatment journey, which suggests that personalization of educational content is required to adapt to different stages of the patient journey. [ABSTRACT FROM AUTHOR]

Background: A range of factors can reduce the effectiveness of treatment prescribed for the long-term management of chronic health conditions, such as growth disorders. In particular, prescription medications may not achieve the positive outcomes expected because approximately half of patients adhere poorly to the prescribed treatment regimen.Methods: Adherence to treatment has previously been assessed using relatively unreliable subjective methods, such as patient self-reporting during clinical follow-up, or counting prescriptions filled or vials returned by patients. Here, we report on a new approach, the use of electronically recorded objective evidence of date, time, and dose taken which was obtained through a comprehensive eHealth ecosystem, based around the easypod™ electromechanical auto-injection device and web-based connect software. The benefits of this eHealth approach are also illustrated here by two case studies, selected from the Finnish cohort of the easypod™ Connect Observational Study (ECOS), a 5-year, open-label, observational study that enrolled children from 24 countries who were being treated with growth hormone (GH) via the auto-injection device.Results: Analyses of data from 9314 records from the easypod™ connect database showed that, at each time point studied, a significantly greater proportion of female patients had high adherence (≥ 85%) than male patients (2849/3867 [74%] vs 3879/5447 [71%]; P < 0.001). Furthermore, more of the younger patients (< 10 years for girls, < 12 years for boys) were in the high adherence range (P < 0.001). However, recursive partitioning of data from ECOS identified subgroups with lower adherence to GH treatment ‒ children who performed the majority of injections themselves at an early age (~ 8 years) and teenagers starting treatment aged ≥ 14 years.Conclusions: The data and case studies presented herein illustrate the importance of adherence to GH therapy and how good growth outcomes can be achieved by following treatment as described. They also show how the device, software, and database ecosystem can complement normal clinical follow-up by providing HCPs with reliable information about patient adherence between visits and also providing researchers with real-world evidence of adherence and growth outcomes across a large population of patients with growth disorders treated with GH via the easypod™ device. [ABSTRACT FROM AUTHOR]

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Mobile monitoring for health and wellness is becoming more sophisticated and accurate, with an increased use of real-time personalization technologies that may improve the effectiveness of physical activity coaching systems. This study aimed to review real-time physical activity coaching applications that make use of personalization mechanisms. A scoping review, using the PRISMA-ScR checklist, was conducted on the literature published from July 2007 to July 2018. A data extraction tool was developed to analyze the systems on general characteristics, personalization, design foundations (behavior change and gamification) and evaluation methods. 28 papers describing 17 different mobile applications were included. The most used personalization concepts were Feedback (17/17), Goal Setting (15/17), User Targeting (9/17) and Inter-human Interaction (8/17), while the less commonly covered were Self-Learning (4/17), Context Awareness (3/17) and Adaptation (2/17). Few systems considered behavior change theories for design (6/17). A total of 42 instances of gamification-related elements were found across 15 systems, but only 6 explicitly mention its use. Most systems (15/17) were submitted to some type of evaluation. However, few assessed the effects of particular strategies or overall system effectiveness using randomized experimental designs (5/17). Although personalization is thought to improve user adherence in physical activity coaching applications, it is still far from reaching its full potential. We believe that future work should consider the theory and suggestions reported in prior work; leverage the needs of the target users for personalization; include behavior change foundations and explore gamification theory; and properly evaluate these systems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this demo, we provide an overview of the digital platform ADHERA CARING which has been used for an intervention designed for emotional and self-management support of caregivers of children receiving growth hormone treatment (GHt). ADHERA CARING provides tailored emotional and self-management support to caregivers of children undergoing GHt to improve adherence to treatment through positive education, personalized motivational messages, and emotional support. This digital intervention has already been piloted in a clinical setting as part of an ongoing feasibility clinical study (NCT04812665). [ABSTRACT FROM AUTHOR]

In this demo, we provide an overview of the digital platform ADHERA CARING which has been used for an intervention designed for emotional and self-management support of caregivers of children receiving growth hormone treatment (GHt). ADHERA CARING provides tailored emotional and self-management support to caregivers of children undergoing GHt to improve adherence to treatment through positive education, personalized motivational messages, and emotional support. This digital intervention has already been piloted in a clinical setting as part of an ongoing feasibility clinical study (NCT04812665). [ABSTRACT FROM AUTHOR]

Individuals within the Arab world rarely access mental health services. One of the major reasons for this relates to the stigma associated with mental disorders. According to the World Health Organization (WHO), untreated and undiagnosed individuals living with moderate to severe mental health disorders are more likely to die 10-20 years earlier than the estimated life expectancy of the general population. Mental disorders also cause a large amount of costs to economies. Access to mental health services is out of reach for many individuals within in the Arab world due to insufficient planning, inadequate community resources, and military conflicts. Online mental health information and services are growing within the region; however, they are embedded and often sidelined within a wealth of other general health information. The purpose of this paper is to present the conceptual framework of the Mental Health Assistant (MeHA) digital platform being developed for the Arab world. The aim of this platform is to provide mental health information and educational resources through the use of a conversational agent, multi-media information, and to digitally connect patients with mental health service providers. The conceptual framework for the platform is based on mental health and information technology expert feedback, review of both academic and gray literature on mental health, and an examination of leading mental health digital platforms. As a result of this process, we developed a conceptual framework that will guide the development of the MeHA platform. [ABSTRACT FROM AUTHOR]

Conversational agents are being used to help in the screening, assessment, diagnosis, and treatment of common mental health disorders. In this paper, we propose a bootstrapping approach for the development of a digital mental health conversational agent (i.e., chatbot). We start from a basic rule-based expert system and iteratively move towards a more sophisticated platform composed of specialized chatbots each aiming to assess and pre-diagnose a specific mental health disorder using machine learning and natural language processing techniques. During each iteration, user feedback from psychiatrists and patients are incorporated into the iterative design process. A survival of the fittest approach is also used to assess the continuation or removal of a specialized mental health chatbot in each generational design. We anticipate that our unique and novel approach can be used for the development of conversational mental health agents with the ultimate goal of designing a smart chatbot that delivers evidence-based care and contributes to scaling up services while decreasing the pressure on mental health care providers. [ABSTRACT FROM AUTHOR]

Background: Communication is of paramount importance in responding to health crises. We studied the media messages put forth by different stakeholders in two Ebola vaccine trials that became controversial in Ghana. These interactions between health authorities, political actors, and public citizens can offer key lessons for future research. Through an analysis of online media, we analyse stakeholder concerns and incentives, and the phases of the dispute, to understand how the dispute evolved to the point of the trials being suspended, and analyse what steps might have been taken to avert this outcome.Methods: A web-based system was developed to download and analyse news reports relevant to Ebola vaccine trials. This included monitoring major online newspapers in each country with planned clinical trials, including Ghana. All news articles were downloaded, selecting out those containing variants of the words "Ebola," and "vaccine," which were analysed thematically by a team of three coders. Two types of themes were defined: critiques of the trials and rebuttals in favour of the trials. After reconciling differences between coders' results, the data were visualised and reviewed to describe and interpret the debate.Results: A total of 27,460 articles, published between 1 May and 30 July 2015, were collected from nine different newspapers in Ghana, of which 139 articles contained the keywords and met the inclusion criteria. The final codebook included 27 themes, comprising 16 critiques and 11 rebuttals. After coding and reconciliation, the main critiques (and their associated rebuttals) were selected for in-depth analysis, including statements about the trials being secret (mentioned in 21% of articles), claims that the vaccine trials would cause an Ebola outbreak in Ghana (33%), and the alleged impropriety of the incentives offered to participants (35%).Discussion: Perceptions that the trials were "secret" arose from a combination of premature news reporting and the fact that the trials were prohibited from conducting any publicity before being approved at the time that the story came out, which created an impression of secrecy. Fears about Ebola being spread in Ghana appeared in two forms, the first alleging that scientists would intentionally infect Ghanaians with Ebola in order to test the vaccine, and the second suggesting that the vaccine might give trial participants Ebola as a side-effect - over the course of the debate, the latter became the more prominent of the two variants. The incentives were sometimes criticised for being coercively large, but were much more often criticised for being too small, which may have been related to a misperception that the incentives were meant as compensation for the trials' risks, which were themselves exaggerated.Conclusion: The rumours captured through this research indicate the variety of strong emotions drawn out by the trials, highlighting the importance of understanding the emotional and social context of such research. The uncertainty, fear, and distrust associated with the trials draw from the contemporary context of the Ebola outbreak, as well as longstanding historical issues in Ghana. By analysing the debate from its inception, we can see how the controversy unfolded, and identify points of concern that can inform health communication, suggesting that this tool may be valuable in future epidemics and crises. [ABSTRACT FROM AUTHOR]

Background: Zika virus, an emerging serious infectious disease, is a threat to persons living or travelling to regions where it is currently endemic, and also to contacts of infected individuals. The aim of this study was to assess knowledge about this new public health threat to persons residing in a Middle Eastern country.Methods: We conducted a survey at several international universities in Qatar to assess knowledge and awareness about this disease. An adapted version of the survey was also conducted using online channels from Qatar.Results: The median age of the 446 participants, was 25 years, 280 (63%) were females, and 32% were from Gulf Cooperation Council (GCC) or other Middle East countries. Based upon their knowledge about availability of a vaccine, role of mosquitoes and other modes of transmission, and disease complications, we classified respondent's knowledge as "poor" (66%), "basic" (27%) or "broad" (7%). Forty-five (16%) persons with poor knowledge considered themselves to be well-informed.Conclusions: This report from a sample of persons associated with Middle East educational complex, reveals inadequate knowledge about Zika virus, a serious emerging infectious disease. Although few cases have been reported from the region, future cases are possible, since this area is a transit hub connecting currently infected regions to North America, Europe and Asia. As a preventive measure, an educational program about Zika virus would be valuable, especially for individuals or family members travelling to afflicted regions. [ABSTRACT FROM AUTHOR]

Background: The Internet, and its popularity, continues to grow at an unprecedented pace. Watching videos online is very popular; it is estimated that 500 h of video are uploaded onto YouTube, a video-sharing service, every minute and that, by 2019, video formats will comprise more than 80% of Internet traffic. Health-related videos are very popular on YouTube, but their quality is always a matter of concern. One approach to enhancing the quality of online videos is to provide additional educational health content, such as websites, to support health consumers. This study investigates the feasibility of building a content-based recommender system that links health consumers to reputable health educational websites from MedlinePlus for a given health video from YouTube.Methods: The dataset for this study includes a collection of health-related videos and their available metadata. Semantic technologies (such as SNOMED-CT and Bio-ontology) were used to recommend health websites from MedlinePlus. A total of 26 healths professionals participated in evaluating 253 recommended links for a total of 53 videos about general health, hypertension, or diabetes. The relevance of the recommended health websites from MedlinePlus to the videos was measured using information retrieval metrics such as the normalized discounted cumulative gain and precision at K.Results: The majority of websites recommended by our system for health videos were relevant, based on ratings by health professionals. The normalized discounted cumulative gain was between 46% and 90% for the different topics.Conclusions: Our study demonstrates the feasibility of using a semantic content-based recommender system to enrich YouTube health videos. Evaluation with end-users, in addition to healthcare professionals, will be required to identify the acceptance of these recommendations in a nonsimulated information-seeking context. [ABSTRACT FROM AUTHOR]

Background: The explosion of consumer electronics and social media are facilitating the rise of the Quantified Self (QS) movement where millions of users are tracking various aspects of their daily life using social media, mobile technology, and wearable devices. Data from mobile phones, wearables and social media can facilitate a better understanding of the health behaviors of individuals. At the same time, there is an unprecedented increase in childhood obesity rates worldwide. This is a cause for grave concern due to its potential long-term health consequences (e.g., diabetes or cardiovascular diseases). Childhood obesity is highly prevalent in Qatar and the Gulf Region. In this study we examine the feasibility of capturing quantified-self data from social media, wearables and mobiles within a weight lost camp for overweight children in Qatar.Methods: Over 50 children (9-12 years old) and parents used a wide range of technologies, including wearable sensors (actigraphy), mobile and social media (WhatsApp and Instagram) to collect data related to physical activity and food, that was then integrated with physiological data to gain insights about their health habits. In this paper, we report about the acquired data and visualization techniques following the 360° Quantified Self (360QS) methodology (Haddadi et al., ICHI 587-92, 2015).Results: 360QS allows for capturing insights on the behavioral patterns of children and serves as a mechanism to reinforce education of their mothers via social media. We also identified human factors, such as gender and cultural acceptability aspects that can affect the implementation of this technology beyond a feasibility study. Furthermore, technical challenges regarding the visualization and integration of heterogeneous and sparse data sets are described in the paper.Conclusions: We proved the feasibility of using 360QS in childhood obesity through this pilot study. However, in order to fully implement the 360QS technology careful planning and integration in the health professionals' workflow is needed.Trial Registration: The trial where this study took place is registered at ClinicalTrials.gov on 14 November 2016 ( NCT02972164 ). [ABSTRACT FROM AUTHOR]

Background: Improving mobility in elderly persons is a primary goal in geriatric rehabilitation. Self-regulated exercises with instruction leaflets are used to increase training volume but adherence is often low. Exergames may improve adherence. This study therefore compared exergames with self-regulated exercise using instruction leaflets. The primary outcome was adherence. Secondary outcomes were enjoyment, motivation and balance during walking.Methods: Design: single center parallel group non-blinded randomized controlled trial with central stratified randomization.Setting: center for geriatric inpatient rehabilitation. Included were patients over 65 with mobility restrictions who were able to perform self-regulated exercise. Patients were assigned to self-regulated exercise using a) exergames on Windows Kinect® (exergame group EG) or b) instruction leaflets (conventional group CG). During two 30 min sessions physical therapists instructed self-regulated exercise to be conducted twice daily during thirty minutes during ten working days. Patients reported adherence (primary outcome), enjoyment and motivation daily. Balance during walking was measured blind before and after the treatment phase with an accelerometer. Analysis was by intention to treat. Repeated measures mixed models and Cohen's d effect sizes (ES, moderate if >0.5, large if > 0.8) with 95% CIs were used to evaluate between-group effects over time. Alpha was set at 0.05.Results: From June 2014 to December 2015 217 patients were evaluated and 54 included, 26 in the EG and 28 in the CG. Adverse effects were observed in two patients in the EG who stopped because of pain during exercising. Adherence was comparable at day one (38 min. in the EG and 42 min. in the CG) and significantly higher in the CG at day 10 (54 min. in the CG while decreasing to 28 min. in the EG, p = 0.007, ES 0.94, 0.39-0.151). Benefits favoring the CG were also observed for enjoyment (p = 0.001, ES 0.88, 0.32 - 1.44) and motivation (p = 0.046, ES 0.59, 0.05-1.14)). There was no between-group effect in balance during walking.Conclusions: Self-regulated exercise using instruction leaflets is superior to exergames regarding adherence, enjoyment and motivation in a geriatric inpatient rehabilitation setting. Effects were moderate to large. There was no between group difference in balance during walking.Trial Registration: ClinicalTrials.gov, NCT02077049 , 6 February 2014. [ABSTRACT FROM AUTHOR]

Lack of sleep can erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health. In the web extra at https://youtu.be/_zL-t4gk210, guest editor Katarzyna Wac interviews lead author Aarti Sathyanarayana, a PhD student in the University of Minnesota's Department of Computer Science. [ABSTRACT FROM AUTHOR]

Background: Maintaining mobility in elderly persons has become a primary goal within healthcare services. In older adults, exercise programs significantly reduce the risk of falling and death. Long-lasting and high-intensive multi-component exercises are most effective. In a rehabilitation setting, self-regulated exercises are conventionally taught by physiotherapists, using handouts. However, the adherence of elderly persons to executing these self-administered programs varies considerably. They are often considered tedious and boring, and thus prematurely stopped. The primary aim of this clinical trial is to determine whether elderly persons in a rehabilitation setting show higher adherence to self-regulated training when using exergames than when performing conventional exercises. The second objective is to explore which mode of exercise leads to greater improvement in balance performance. Methods/Design: The study consists of a single blind, stratified, randomized control trial with two parallel groups. Once included, study participants will be stratified according to their balance and computer skills and randomly allocated to self-regulated training with conventional exercise programs or with exergames played with the Windows Kinect® sensor and FitBit® pedometer. In both groups, self-administered exercise programs will be taught by experienced physiotherapists and performed at the patient's own discretion during the ten days of intervention. The primary outcome is the performed daily training volume, collected by the participants in a logbook. Secondary outcomes are objective and subjective balance skills measured by an activity tracker and the Fall Efficacy Scale self-administered questionnaire. Both assessments will be performed at pre- and post-intervention. Discussion: According to the available literature, this study is the first to compare conventional self-regulated exercises with exergames among older patients in a rehabilitation setting. Results of this study will contribute to our understanding of its motivational potential on exercise adherence in elderly persons and provide more insight into the potential effectiveness of exergames promoting mobility. [ABSTRACT FROM AUTHOR]

Background: Maintaining mobility in elderly persons has become a primary goal within healthcare services. In older adults, exercise programs significantly reduce the risk of falling and death. Long-lasting and high-intensive multi-component exercises are most effective. In a rehabilitation setting, self-regulated exercises are conventionally taught by physiotherapists, using handouts. However, the adherence of elderly persons to executing these self-administered programs varies considerably. They are often considered tedious and boring, and thus prematurely stopped. The primary aim of this clinical trial is to determine whether elderly persons in a rehabilitation setting show higher adherence to self-regulated training when using exergames than when performing conventional exercises. The second objective is to explore which mode of exercise leads to greater improvement in balance performance. Methods/Design: The study consists of a single blind, stratified, randomized control trial with two parallel groups. Once included, study participants will be stratified according to their balance and computer skills and randomly allocated to self-regulated training with conventional exercise programs or with exergames played with the Windows Kinect® sensor and FitBit® pedometer. In both groups, self-administered exercise programs will be taught by experienced physiotherapists and performed at the patient’s own discretion during the ten days of intervention. The primary outcome is the performed daily training volume, collected by the participants in a logbook. Secondary outcomes are objective and subjective balance skills measured by an activity tracker and the Fall Efficacy Scale self-administered questionnaire. Both assessments will be performed at pre- and post-intervention. Discussion: According to the available literature, this study is the first to compare conventional self-regulated exercises with exergames among older patients in a rehabilitation setting. Results of this study will contribute to our understanding of its motivational potential on exercise adherence in elderly persons and provide more insight into the potential effectiveness of exergames promoting mobility. [ABSTRACT FROM AUTHOR]

Background: Chlamydia is the most common reportable sexually transmitted disease (STD) in Norway, and its incidence in the two northernmost counties has been disclosed to be nearly the double of the Norwegian average. The latest publicly available rates showed that 85.6% of the new cases were diagnosed in people under 29 years old. The information and communication technologies are among the most powerful influences in the lives of young people. The Internet can potentially represent a way to educate on sexual health and encourage young people, and especially youth, to be tested for STDs. If hospital websites include an easy and anonymous system for scheduling appointments with the clinic, it is possible that this could lead to an increase in the number of people tested for STDs. Methods: The purpose of the study is to assess the impact of a game-based appointment system on the frequency of consultations at a venereology unit and on the use of an educational web app. An A/B testing methodology is used. Users from the city of Tromsø, in North Norway, will be randomized to one of the two versions of the game-style web app on sexual health at www.sjekkdeg.no. Group A will have access to educational content only, while group B will have, in addition, access to a game-based appointment system with automatic prioritization. After one year of the trial, it will be analyzed if the game-based appointment system increases the number of consultations at the venereology unit and if health professionals deem the system useful. Discussion: This study will explore if facilitating the access to health services for youth through the use of a game-based appointment system integrated in a game-style web app on sexual health education can have an impact on appointment rates. [ABSTRACT FROM AUTHOR]

Millions of people living with diabetes are using mobile phones, Internet and social media to socialize with other patients, share experience or search information relevant for their self-management. This phenomena is leading towards a new paradigm of hyper-connected diabetes digital self-management. This is also leading towards an explosion on data, a large amount of data is collected on populations around the world. This panel will address the opportunities this data presents, discuss the latest research that uses it, and the limitations and other concerns. [ABSTRACT FROM AUTHOR]

The Internet has become one of the main sources of health information. Today, content generation is no longer limited to the healthcare professionals of the late nineties; Web 2.0 services and platforms have empowered patients to create and interact with various forms of Patient-Generated Content (PGC); these include: videos, blogs, and social networking pages, among others. This investigation evaluated the characteristics of PGC found within YouTube video comments. We selected a random sample of 25 out of 769 Multiple Sclerosis patient-generated videos and analyzed their corresponding 557 comments for health information. 320 comments met the inclusion criteria and 70 contained personal health information (PHI). Comments with PHI were sub-characterized for the type of medical information (i.e., diagnosis, date of diagnosis, medication, among others). In this descriptive study, we present the strata within this content and postulate some of the corresponding patient risks and ethical challenges associated with PGC found in YouTube video comments. [ABSTRACT FROM AUTHOR]

The use of computers in health education started more than a decade ago, mainly for tailoring health educational resources. Nowadays, many of the computer-tailoring health education systems are using the Internet for delivering different types of health education. Traditionally, these systems are designed for a specific health problem, with a predefined library of educational resources. These systems do not take advantage of the increasing amount of educational resources available on the Internet. One of the reasons is that the high availability of content is making it more difficult to find the relevant one. The problem of information overload has been addressed for many years in the field of recommender systems. This paper is focused on the challenges and opportunities of merging recommender systems with personalized health education. It also discusses the usage of social networks and semantic technologies within this approach. [ABSTRACT FROM AUTHOR]

This is of special importance in nursing since nurses are the forefront of the delivery of care to patients. This serves two main objectives,improve the provision of person-centred care and also improve the communication with patients, which is a crucial element in the adoption of person-centredness nursing care. Male L, Noble A, Atkinson J, Marson T. Measuring patient experience: a systematic review to evaluate psychometric properties of patient reported experience measures (PREMs) for emergency care service provision. [Extracted from the article]

A correction to the article "Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar," is presented.

Accurately measuring sleep and its quality with polysomnography (PSG) is an expensive task. Actigraphy, an alternative, has been proven cheap and relatively accurate. However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. We propose the adoption of this publicly available large dataset, which is at least one order of magnitude larger than any other dataset, to systematically compare existing methods for the detection of sleep-wake stages, thus fostering the creation of new algorithms. We also implemented and compared state-of-the-art methods to score sleep-wake stages, which range from the widely used traditional algorithms to recent machine learning approaches. We identified among the traditional algorithms, two approaches that perform better than the algorithm implemented by the actigraphy device used in the MESA Sleep experiments. The performance, in regards to accuracy and F1 score of the machine learning algorithms, was also superior to the device's native algorithm and comparable to human annotation. Future research in developing new sleep-wake scoring algorithms, in particular, machine learning approaches, will be highly facilitated by the cohort used here. We exemplify this potential by showing that two particular deep-learning architectures, CNN and LSTM, among the many recently created, can achieve accuracy scores significantly higher than other methods for the same tasks. [ABSTRACT FROM AUTHOR]

Background: Smoking cessation is the most common preventative for an array of diseases, including lung cancer and chronic obstructive pulmonary disease. Although there are many efforts advocating for smoking cessation, smoking is still highly prevalent. For instance, in the USA in 2015, 50% of all smokers attempted to quit smoking, and only 5-7% of them succeeded - with slight deviation depending on external assistance. Previous studies show that computer-tailored messages which support smoking abstinence are effective. The combination of health recommender systems and behavioral-change theories is becoming increasingly popular in computer-tailoring. The objective of this study is to evaluate patients's smoking cessation rates by means of two randomized controlled trials using computer-tailored motivational messages. A group of 100 patients will be recruited in medical centers in Taiwan (50 patients in the intervention group, and 50 patients in the control group), and a group of 1000 patients will be recruited on-line (500 patients in the intervention group, and 500 patients in the control group). The collected data will be made available to the public in an open-source data portal.Methods: Our study will gather data from two sources. The first source is a clinical pilot in which a group of patients from two Taiwanese medical centers will be randomly assigned to either an intervention or a control group. The intervention group will be provided with a mobile app that sends motivational messages selected by a recommender system that takes the user profile (including gender, age, motivations, and social context) and similar users' opinions. For 6 months, the patients' smoking activity will be followed up, and confirmed as "smoke-free" by using a test that measures expired carbon monoxide and urinary cotinine levels. The second source will be a public pilot in which Internet users wanting to quit smoking will be able to download the same mobile app as used in the clinical pilot. They will be randomly assigned to a control group that receives basic motivational messages or to an intervention group, that receives personalized messages by the recommender system. For 6 months, patients in the public pilot will be assessed periodically with self-reported questionnaires.Discussion: This study will be the first to use the I-Change behavioral-change model in combination with a health recommender system and will, therefore, provide relevant insights into computer-tailoring for smoking cessation. If our hypothesis is validated, clinical practice for smoking cessation would benefit from the use of our mobile solution.Trial Registration: ClinicalTrials.gov, ID: NCT03108651 . Registered on 11 April 2017. [ABSTRACT FROM AUTHOR]

Background: Smoking is one of the most avoidable health risk factors, and yet the quitting success rates are low. The usage of tailored health messages to support quitting has been proved to increase quitting success rates. Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items-for instance, motivational messages aimed at smoking cessation-for each user based on his or her profile. The goals of this study are to analyze the perceived quality of an mHealth recommender system aimed at smoking cessation, and to assess the level of engagement with the messages delivered to users via this medium.Methods: Patients participating in a smoking cessation program will be provided with a mobile app to receive tailored motivational health messages selected by a health recommender system, based on their profile retrieved from an electronic health record as the initial knowledge source. Patients' feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. This paper details the implementation and evaluation protocol that will be followed.Discussion: This study will explore whether a health recommender system algorithm integrated with an electronic health record can predict which tailored motivational health messages patients would prefer and consider to be of a good quality, encouraging them to engage with the system. The outcomes of this study will help future researchers design better tailored motivational message-sending recommender systems for smoking cessation to increase patient engagement, reduce attrition, and, as a result, increase the rates of smoking cessation.Trial Registration: The trial was registered at clinicaltrials.org under the ClinicalTrials.gov identifier NCT03206619 on July 2nd 2017. Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: Maintaining mobility in elderly persons has become a primary goal within healthcare services. In older adults, exercise programs significantly reduce the risk of falling and death. Long-lasting and high-intensive multi-component exercises are most effective. In a rehabilitation setting, self-regulated exercises are conventionally taught by physiotherapists, using handouts. However, the adherence of elderly persons to executing these self-administered programs varies considerably. They are often considered tedious and boring, and thus prematurely stopped. The primary aim of this clinical trial is to determine whether elderly persons in a rehabilitation setting show higher adherence to self-regulated training when using exergames than when performing conventional exercises. The second objective is to explore which mode of exercise leads to greater improvement in balance performance.Methods/design: The study consists of a single blind, stratified, randomized control trial with two parallel groups. Once included, study participants will be stratified according to their balance and computer skills and randomly allocated to self-regulated training with conventional exercise programs or with exergames played with the Windows Kinect® sensor and FitBit® pedometer. In both groups, self-administered exercise programs will be taught by experienced physiotherapists and performed at the patient's own discretion during the ten days of intervention. The primary outcome is the performed daily training volume, collected by the participants in a logbook. Secondary outcomes are objective and subjective balance skills measured by an activity tracker and the Fall Efficacy Scale self-administered questionnaire. Both assessments will be performed at pre- and post-intervention.Discussion: According to the available literature, this study is the first to compare conventional self-regulated exercises with exergames among older patients in a rehabilitation setting. Results of this study will contribute to our understanding of its motivational potential on exercise adherence in elderly persons and provide more insight into the potential effectiveness of exergames promoting mobility.Trial Registration: The present clinical study has been registered on ClinicalTrials.gov under the identifier number: NCT02077049. The detailed trial protocol can be accessed online on: NCT02077049. [ABSTRACT FROM AUTHOR]

Background: Chlamydia is the most common reportable sexually transmitted disease (STD) in Norway, and its incidence in the two northernmost counties has been disclosed to be nearly the double of the Norwegian average. The latest publicly available rates showed that 85.6% of the new cases were diagnosed in people under 29 years old. The information and communication technologies are among the most powerful influences in the lives of young people. The Internet can potentially represent a way to educate on sexual health and encourage young people, and especially youth, to be tested for STDs. If hospital websites include an easy and anonymous system for scheduling appointments with the clinic, it is possible that this could lead to an increase in the number of people tested for STDs.Methods: The purpose of the study is to assess the impact of a game-based appointment system on the frequency of consultations at a venereology unit and on the use of an educational web app. An A/B testing methodology is used. Users from the city of Tromsø, in North Norway, will be randomized to one of the two versions of the game-style web app on sexual health at www.sjekkdeg.no. Group A will have access to educational content only, while group B will have, in addition, access to a game-based appointment system with automatic prioritization. After one year of the trial, it will be analyzed if the game-based appointment system increases the number of consultations at the venereology unit and if health professionals deem the system useful.Discussion: This study will explore if facilitating the access to health services for youth through the use of a game-based appointment system integrated in a game-style web app on sexual health education can have an impact on appointment rates.Trial Registration: The trial is registered at clinicaltrials.org under the identifier ClinicalTrials.gov NCT:02128620. [ABSTRACT FROM AUTHOR]

Sexually transmitted diseases (STDs) and especially chlamydia is a worrying problem among North-Norwegian youngsters. Gamified web applications should be valued for sexual health education, and thus STDs prevention, for their potential to get users engaged and involved with their healthcare. Aiming to achieve that youngsters become more aware of STDs we have developed 'sjekkdeg.no', a gamified web application focused on sexual health targeting North-Norwegian youngsters. Gamification techniques like avatars, achievement-based gifts and social network sharing buttons have been implemented in the site that includes educational content on sexual health and a STDs symptom checker. Preliminary results show that the game-style web app could be useful to encourage users to learn more on sexual health and STDs and thus changing their risky behaviors and preventing sexually transmitted diseases. [ABSTRACT FROM AUTHOR]