Notes

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roximate time observing the child's PA and SB, the parent's EMA report might be a superior method for measuring PA and SB in young children relative to self-report, given the EMA's strong associations with accelerometer-measured PA and ST.[This corrects the article DOI 10.2196/14914.]. ©Zhilian Huang, Eberta Tan, Elaine Lum, Peter Sloot, Bernhard Otto Boehm, Josip Car. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 29.04.2020.BACKGROUND Chronic pain is associated with poor physical and emotional functioning. Nonpharmacological interventions can help but improvements are small and not sustained. Prior clinical trials do not follow recommendations to comprehensively target objective and performance-based physical function in addition to self-reported physical function. OBJECTIVE To establish feasibility benchmarks and explore improvements in physical (self-report, performance based and objective) and emotional function, pain outcomes and coping through a pilot RCT of a mind-body physical activity program (GetActive) with and without a digital monitoring device (GetActive-Fitbit) which were iteratively refined through mixed methods. METHODS Patients with chronic pain were randomized to GetActive (N=41) or GetActive-Fitbit (N=41) programs, which combine relaxation, cognitive-behavioral, and physical restoration skills and were delivered in person. They completed in-person assessments before and after the intervention. Performance basefindings support a fully-powered efficacy trial of the two programs against an education control group. We present a model for successfully using IMMPACT criteria for comprehensive assessment of physical function and following evidence-based models to maximize feasibility prior to formal efficacy testing. CLINICALTRIAL ClinicalTrials.gov NCT03412916.BACKGROUND Obesity in pregnancy is a growing problem worldwide, with excessive gestational weight gain (GWG) occurring in the majority of pregnancies. This significantly increases risks to mother and child. A major contributor to both prepregnancy obesity and excessive GWG is physical inactivity; however, past interventions targeting maternal weight gain and activity levels during the antenatal period have been ineffective in women who are already overweight. Pedometer-guided activity may offer a novel solution to increasing activity levels in this population. OBJECTIVE This initial feasibility randomized controlled trial aimed to test a pedometer-based intervention to increase activity and reduce excessive GWG in pregnant women. METHODS We supplied 30 pregnant women with obesity a Fitbit Zip pedometer and randomized them into 1 of 3 groups control (pedometer only), app (pedometer synced to patients' personal smartphone, with self-monitoring of activity), or app-coach (addition of a health coach-delivered behn decrease of 7.8 steps/day for each increase in gestation day over the study period (95% CI 2.91 to 12.69, P=.002). CONCLUSIONS Activity data syncing with a personal smartphone is feasible in a cohort of pregnant women with obesity. However, our results do not support a future definitive study in its present form. Recruitment and retention rates were adequate, as was activity data syncing to participants' smartphones. A follow up interventional trial seeking to reduce GWG and improve activity in this population must focus on improving compliance with activity data recording and behavioral interventions delivered. CLINICALTRIAL Australian and New Zealand Clinical Trials Registry ACTRN12617000038392. https//www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370884.BACKGROUND The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings. OBJECTIVE This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirsuch as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.BACKGROUND In the homeless population, barriers to housing and supportive services include a lack of control or access to data. Disparate data formats and storage across multiple organizations hinder up-to-date intersystem access to records and a unified view of an individual's health and documentation history. The utility of blockchain to solve interoperability in health care is supported in recent literature, but the technology has yet to be tested in real-life conditions encompassing the complex regulatory standards in the health sector. OBJECTIVE This study aimed to test the feasibility and performance of a blockchain system in a homeless community to securely store and share data across a system of providers in the health care ecosystem. METHODS We performed a series of platform demonstrations and open-ended qualitative feedback interviews to determine the key needs and barriers to user and stakeholder adoption. Account creation and data transactions promoting organizational efficiency and improved healt cost-effectiveness, scalability, and regulatory frameworks.BACKGROUND A long-acting implant for HIV pre-exposure prophylaxis (PrEP) is in development in the Sustained Long-Action Prevention Against HIV (SLAP-HIV) trial. This could provide an alternative to oral PrEP. OBJECTIVE Our mixed methods study aimed to understand (1) users' experiences with a similar subdermal implant for contraception and (2) factors influencing the likelihood that gay and bisexual men (GBM) would use a proposed PrEP implant. METHODS Work was completed in 4 stages. In stage 1, we conducted a scientific literature review on existing subdermal implants, focusing on users' experiences with implant devices. In stage 2, we reviewed videos on YouTube, focusing on the experiences of current or former contraceptive implant users (as these implants are similar to those in development in SLAP-HIV). In stage 3, individuals who indicated use of a subdermal implant for contraception in the last 5 years were recruited via a web-based questionnaire. Eligible participants (n=12 individuals who liked implantsnd removal. They mainly reported removing or disliking the device due to contraceptive-related side effects (eg, prolonged menstruation). Participants in the stage 4 quantitative survey (N=304) were mainly gay (204/238, 85.7%), white (125/238, 52.5%), cisgender men (231/238, 97.1%), and 42.0% (73/174) of them were on oral PrEP. Not having to take a daily pill increased the likelihood of using PrEP implants (mean 4.13). Requiring >1 device to achieve 1 year of protection (mean range 1.79-2.94) mildly discouraged PrEP implant use. Participants did not mind moderate bruising, a small scar, tenderness, or bleeding after insertion or removal, and an implant with a size slightly larger than a matchstick (mean ratings 3.18-3.69). CONCLUSIONS PrEP implants are promising among GBM. Implant features and insertion or removal-related concerns do not seem to discourage potential users. To ensure acceptability, PrEP implants should require the fewest possible implants for the greatest protection duration.[This corrects the article DOI 10.2196/16496.]. ©Yuanjin Zhang, Dongsheng Fan, Hong Ji, Shudong Qiao, Xia Li. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 29.04.2020.BACKGROUND Social media has become a major resource for observing and understanding public opinions, especially during emergencies such as disease outbreaks. For public health agencies, understanding the driving forces of web-based discussions will help deliver more effective and efficient information to general users on social media and the web. OBJECTIVE The study aimed to identify the major contributors that drove overall Zika-related tweeting dynamics during the 2016 epidemic. In total, 3 hypothetical drivers were proposed (1) the underlying Zika epidemic quantified as a time series of case counts; (2) sporadic but critical real-world events such as the 2016 Rio Olympics and World Health Organization's Public Health Emergency of International Concern (PHEIC) announcement, and (3) a few influential users' tweeting activities. METHODS All tweets and retweets (RTs) containing the keyword Zika posted in 2016 were collected via the Gnip application programming interface (API). We developed an analytical pipeli00 users receiving most RTs, and the top 100 users mentioned were the most highly correlated to and preceded the overall tweeting dynamics, making these groups of users the potential drivers of tweeting dynamics. The top 100 users who retweeted the most were not critical in driving the overall tweeting dynamics. There were very few overlaps among these different groups of potentially influential users. CONCLUSIONS Using our proposed analytical workflow, EventPeriscope, we identified that Zika discussion dynamics on Twitter were decoupled from the actual disease epidemic in the United States but were closely related to and highly influenced by certain sporadic real-world events as well as by a few influential users. This study provided a methodology framework and insights to better understand the driving forces of web-based public discourse during health emergencies. Therefore, health agencies could deliver more effective and efficient web-based communications in emerging crises.BACKGROUND Breast cancer survivors (BCSs) are a growing population with a higher prevalence of insomnia than women of the same age without a history of cancer. Cognitive behavioral therapy for insomnia (CBT-I) has been shown to be effective in this population, but it is not widely available to those who need it. OBJECTIVE This study aimed to better understand BCS's experiences with insomnia and to explore the feasibility and acceptability of delivering CBT-I using a virtual assistant (Amazon Alexa). METHODS We first conducted a formative phase with 2 focus groups, supplemented with 3 in-depth interviews to understand BCS perceptions of insomnia, as well as an interest in and comfort using a virtual assistant to learn about CBT-I. We then developed a prototype incorporating participant preferences and CBT-I components and demonstrated it in group and individual settings to BCSs to evaluate acceptability, interest, perceived feasibility, educational potential, and usability of the prototype. We also collected o rated as feasible and acceptable, suggesting that this prototype should be fully developed and tested for efficacy in the BCS population. If efficacy is shown in this population, the prototype should also be adapted for other high-risk populations. CLINICALTRIALBACKGROUND Roadside observational studies play a fundamental role in designing evidence-informed strategies to address the pressing global health problem of road traffic injuries. Paper-based data collection has been the standard method for such studies, although digital methods are gaining popularity in all types of primary data collection. OBJECTIVE This study aims to understand the reliability, productivity, and efficiency of paper vs digital data collection based on three different road user behaviors helmet use, seatbelt use, and speeding. It also aims to understand the cost and time efficiency of each method and to evaluate potential trade-offs among reliability, productivity, and efficiency. METHODS A total of 150 observational sessions were conducted simultaneously for each risk factor in Mumbai, India, across two rounds of data collection. We matched the simultaneous digital and paper observation periods by date, time, and location, and compared the reliability by subgroups and the productivity usingdigital and paper.BACKGROUND Mass media campaigns for public health are increasingly using digital media platforms, such as web-based advertising and social media; however, there is a lack of evidence on how to best use these digital platforms for public health campaigns. To generate this evidence, appropriate campaign evaluations are needed, but with the proliferation of digital media-related metrics, there is no clear consensus on which evaluation metrics should be used. Public health campaigns are diverse in nature, so to facilitate analysis, this review has selected tobacco control campaigns as the scope of the study. OBJECTIVE This literature review aimed to examine how tobacco control campaigns that use traditional and digital media platforms have been evaluated. METHODS Medicine and science databases (Medical Literature Analysis and Retrieval System Online [MEDLINE], EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature [CINAHL], and Scopus), and a marketing case study database (World Advertising Rel in campaign evaluations.BACKGROUND Vaccine hesitancy is a growing threat to population health, and effective interventions are needed to reduce its frequency. Digital gamification is a promising new approach to tackle this public health issue. OBJECTIVE The purpose of this scoping review was to assess the amount and quality of outcomes in studies evaluating gamified digital tools created to increase vaccine knowledge and uptake. METHODS We searched for peer-reviewed articles published between July 2009 and August 2019 in PubMed, Google Scholar, Journal of Medical Internet Research, PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection, and SocINDEX. Studies were coded by author, year of publication, country, journal, research design, sample size and characteristics, type of vaccine, theory used, game content, game modality, gamification element(s), data analysis, type of outcomes, and mean quality score. Outcomes were synthesized through the textual narrative synthesis method. RESULTS A total of 7 articles met the inclusion criteria and were critically reviewed. Game modalities and gamification elements were diverse, but role play and a reward system were present in all studies. These articles included a mixture of randomized controlled trials, quasi-experimental studies, and studies comprising quantitative and qualitative measures. The majority of the studies were theory-driven. All the identified gamified digital tools were highly appreciated for their usability and were effective in increasing awareness of vaccine benefits and motivation for vaccine uptake. CONCLUSIONS Despite the relative paucity of studies on this topic, this scoping review suggests that digital gamification has strong potential for increasing vaccination knowledge and, eventually, vaccination coverage.BACKGROUND Coronary heart disease (CHD) is the leading cause of death and disability among American women. The prevalence of CHD is expected to increase by more than 40% by 2035. In 2015, the estimated cost of caring for patients with CHD was US $182 billion in the United States; hospitalizations accounted for more than half of the costs. Compared with men, women with CHD or those who have undergone coronary revascularization have up to 30% more rehospitalizations within 30 days and up to 1 year. Center-based cardiac rehabilitation is the gold standard of care after an acute coronary event, but few women attend these valuable programs. Effective home-based interventions for improving cardiovascular health among women with CHD are vital for addressing this gap in care. OBJECTIVE The ubiquity of mobile phones has made mobile health (mHealth) behavioral interventions a viable option to improve healthy behaviors of both women and men with CHD. First, this study aimed to examine the usability of a prototypic mHealt circumference (P=.048), weight (P=.02), and BMI (P=.01). Furthermore, depressive symptoms, measured with the Patient Health Questionnaire-9, significantly improved from baseline (P=.04). CONCLUSIONS The mHealth prototype was feasible and usable for women with CHD. Participants provided data that were useful for further development of HerBeat. The mHealth intervention is expected to help women with CHD self-manage their health behaviors . A randomized controlled trial is needed to further verify the findings.BACKGROUND There are a range of perceived gaps and shortcomings in the publicly funded Canadian health system. These include wait times for care, lack of public insurance coverage for dental care and pharmaceuticals, and difficulties accessing specialist care. Medical crowdfunding is a response to these gaps where individuals raise funds from their social networks to address health-related needs. OBJECTIVE This study aimed to investigate the potential of crowdfunding data to better understand what health-related needs individuals are using crowdfunding for, how these needs compare with the existing commentary on health system deficiencies, and the advantages and limitations of using crowdfunding campaigns to enhance or augment our understanding of perceived health system deficiencies. METHODS Crowdfunding campaigns were scraped from the GoFundMe website. These campaigns were then limited to those originating in the metropolitan Vancouver region of two health authorities during 2018. These campaigns were then ment of new resources to harness the power of crowdfunding data as a supplementary source of information for Canadian health system stakeholders.BACKGROUND The impact of viewing pornography at a young age on the sexual health of subgroups of young people is an important public health issue. However, the topic is complex and extremely sensitive, and best practices for research and harm reduction are yet to be defined. Drawing on cross-disciplinary approaches, such as co-design, is one way to achieve a better understanding of the issue among vulnerable young people and to create needs-based and evidence-informed digital resources to promote pornography literacy. OBJECTIVE The objective of this study was to co-design a relevant, usable, and acceptable digital prototype to address the pornography literacy needs of vulnerable young people. METHODS In total, 17 young people aged between 14 and 23 years who were engaged in youth services programs or alternative education programs were recruited to participate in 4 co-design workshops with a multidisciplinary design team. RESULTS Although the participants could identify problems with pornography and critique uality, and healthy relationships. The study findings include important recommendations for the conceptualization of digital pornography literacy programs and opportunities for cross-disciplinary co-design research to address complex and emerging health issues.BACKGROUND Each year, half a million patients with a potential neck (c-spine) injury are transported to Ontario emergency departments (EDs). Less than 1.0% (1/100) of these patients have a neck bone fracture. Even less (1/200, 0.5%) have a spinal cord injury or nerve damage. Currently, paramedics transport all trauma victims (with or without an injury) by ambulance using a backboard, cervical collar, and head immobilizers. Importantly, prolonged immobilization is often unnecessary; it causes patient discomfort and pain, decreases community access to paramedics, contributes to ED crowding, and is very costly. We therefore developed the Canadian C-Spine Rule (CCR) for alert and stable trauma patients. This decision rule helps ED physicians and triage nurses to safely and selectively remove immobilization, without x-rays and missed injury. We successfully taught Ottawa paramedics to use the CCR in the field in a single-center study. OBJECTIVE This study aimed to improve patient care and health system efficiency hat each community will have implemented the CCR by the end of the study. RESULTS Interim results are expected in December 2019 and final results in 2020. If this multicenter trial is successful, we expect the Ontario Ministry of Health will recommend that paramedics evaluate all eligible patients with the CCR in the Province of Ontario. CONCLUSIONS We conservatively estimate that in Ontario, more than 60% of all eligible trauma patients (300,000 annually) could be transported safely and comfortably, without c-spine immobilization devices. This will significantly reduce patient pain and discomfort, paramedic intervention times, and ED length of stay, thereby improving access to paramedics and ED care. This could be achieved rapidly and with lower health care costs compared with current practices (possible cost saving of Can $36 [US $25] per immobilization or Can $10,656,000 [US $7,335,231] per year). CLINICALTRIAL ClinicalTrials.gov NCT02786966; https//clinicaltrials.gov/ct2/show/NCT02786966.BACKGROUND Preeclampsia and intrauterine growth restriction are placental dysfunction-related disorders (PDDs) that require a referral decision be made within a certain time period. An appropriate prediction model should be developed for these diseases. However, previous models did not demonstrate robust performances and/or they were developed from datasets with highly imbalanced classes. OBJECTIVE In this study, we developed a predictive model of PDDs by machine learning that uses features at 24-37 weeks' gestation, including maternal characteristics, uterine artery (UtA) Doppler measures, soluble fms-like tyrosine kinase receptor-1 (sFlt-1), and placental growth factor (PlGF). METHODS A public dataset was taken from a prospective cohort study that included pregnant women with PDDs (66/95, 69%) and a control group (29/95, 31%). Preliminary selection of features was based on a statistical analysis using SAS 9.4 (SAS Institute). We used Weka (Waikato Environment for Knowledge Analysis) 3.8.3 (The University of in the best model were maternal weight, BMI, pulsatility index of the UtA, sFlt-1, and PlGF. The most important feature was the sFlt-1/PlGF ratio. This model used an M5P algorithm consisting of a decision tree and four linear models with different thresholds. Our study was also better than the best ones among recent studies in terms of the class balance and the size of the case class (66/95, 69%, vs 27/239, 11.3%). CONCLUSIONS Our model had a robust predictive performance. It was also developed to deal with the problem of a class imbalance. In the context of clinical management, this model may improve maternal mortality and neonatal morbidity and reduce health care costs.BACKGROUND Over the last century, disruptive incidents in clinical and biomedical research fields have yielded a tremendous change in the health data management system. This is due to the breakthrough in the medical field and the need for big data analytics and the Internet of Things (IoT) to be incorporated in a real-time smart health information management system. In addition, the requirements of patient care have evolved over time, allowing for more accurate prognoses and diagnoses. In this paper, we discuss the temporal evolution of the health data management systems and capture the requirements that led to the development of a given system over a certain period of time. Consequently, we provide insights into those systems and give suggestions and research directions on how they can be improved for a better health care system. OBJECTIVE This study aimed to show that there is a need for a secure and efficient health data management system that will allow physicians and patients to update decentralized media security, (6) patient identity privacy, and (7) public insights. This paper reviews the health data management systems based on these 7 requirements across studies conducted over the years. To our knowledge, this is the first analysis of the temporal evolution of health data management systems giving insights on the system requirements for better health care. CONCLUSIONS There is a need for a comprehensive real-time health data management system that allows physicians, patients, and external users to input their medical and lifestyle data into the system. The incorporation of big data analytics will aid in better prognosis or diagnosis of the diseases and the prediction of diseases. The prediction results will help in the development of an effective prevention plan.BACKGROUND The incidence of obesity among adolescents is increasing. Text messages are a primary communication form for adolescents and potentially a scalable strategy for delivering population health interventions. OBJECTIVE This study aimed to determine the effectiveness of text message interventions in reducing BMI in adolescents and describe characteristics that are common to effective interventions. METHODS This systematic review included randomized controlled trials of text message lifestyle interventions involving adolescents aged 10 to 19 years with outcomes focused on obesity prevention or management. Primary outcome was objective or self-report change in BMI. RESULTS In total, 4362 records were identified, and 215 full-text articles were assessed for eligibility. A total of 8 unique studies were identified, including 767 participants, mean age 14.3 (SD 0.9) years, BMI 29.7 (SD 1.6) kg/m2 and 53.1% (407/767) female (31/101, 30.7%-172/172, 100.0%). All interventions were multicomponent. The median active intervention period was 4.5 months. During the active and extended intervention phases, text messages accounted for >50% (8 studies) and >85% (3 studies) of contact points, respectively. Text messages were heterogeneous, with a median of 1.5 text messages sent per week (range 1-21). A total of 4 studies utilized two-way text message communication with health professionals Of the 8 studies, 7 demonstrated reductions in BMI or BMI z-score in the intervention group compared with the control at the end of the final follow-up. The effect was only statistically significant in 1 study at 6 months. Over 6 months, reductions in BMI (kg/m2) ranged from 1.3% to 4.5% and BMI z-score ranged from 4.2% to 28.1%. Overall quality of the studies was low. CONCLUSIONS Further research is required to elucidate the effectiveness and potential impact of text message interventions on weight and weight-related behaviors in adolescents.BACKGROUND In clinical practice, it is difficult to convey the benefits of sustained physical activity to adult patients with excess weight or obesity. For this purpose, a goal-setting walking prescription may be an effective strategy. OBJECTIVE This study aimed to determine the efficacy of the intervention of a pedometer app in setting a goal to reach 10,000 steps per day in adults. METHODS Overweight adults (n=98; mean body mass index 32.53 [SD 4.92] kg/m2) were randomized to one of two conditions (control or intervention). Both groups downloaded a pedometer app that recorded their daily step counts and were given a daily walking goal of 10,000 steps. Subjects participated in a 24-week in-person behavioral weight control program and were asked to monitor their daily levels using the pedometer app. Baseline data were recorded and followed up weekly. Only the intervention group had structured information delivery, a personalized physical activity prescription, and follow-up on number of steps per day. RESULTS The results show that regardless of sex or age, prescribing walking increased the number of steps per day by 4806 step on average (standardized beta coefficient=-0.813, SE=427.586, t=-11.242, P less then .001). CONCLUSIONS These results could have implications for improving self-monitoring in overweight adults during periods of weight loss. Health professionals should analyze the implementation of tools that permit them to prescribe, follow up, and encourage the achievement of a goal of physical activity in overweight or obese patients. CLINICALTRIAL ClinicalTrials.gov NCT03845478; https//clinicaltrials.gov/ct2/show/NCT03845478.BACKGROUND Chronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program. OBJECTIVE The objective of this paper was to survey the current medical technologies for remote patient monitoring (RPM) tools that forecast COPD exacerbations in order to reduce COPD readmissions. METHODS We searched literature and digital health news to find commercially available RPM devices focused on predicting COPD exacerbations. These technologies were reviewed and compared according to four criteria forecasting ability, cost, ease of use, and appearance. A rating system was developed to facilitate the evaluation process. RESULTS As of June 2019, a list of handheld and hands-free devices was compiled. We compared features and found substantial variations. Devices that ranked higher on all criteria tended to have a high or unlisted price. Commonly mass-marketed devices like the pulse oximeter and spirometer surprisingly fulfilled the least criteria. CONCLUSIONS The COPD RPM technologies with most technological promise and compatibility with daily living appear to have high or unlisted prices. Consumers and providers need better access to product information to make informed decisions.BACKGROUND Consumer-facing digital health interventions provide a promising avenue to bridge gaps in mental health care delivery. To evaluate these interventions, understanding how the target population uses a solution is critical to the overall validity and reliability of the evaluation. As a result, usage data (analytics) can provide a proxy for evaluating the engagement of a solution. However, there is paucity of guidance on how usage data or analytics should be used to assess and evaluate digital mental health interventions. OBJECTIVE This review aimed to examine how usage data are collected and analyzed in evaluations of mental health mobile apps for transition-aged youth (15-29). METHODS A scoping review was conducted using the Arksey and O'Malley framework. A systematic search was conducted on 5 journal databases using keywords related to usage and engagement, mental health apps, and evaluation. A total of 1784 papers from 2008 to 2019 were identified and screened to ensure that they included analytics mental health interventions for transition-aged youth. The large proportion of publications from the last 6 years suggests that user analytics is increasingly being integrated into the evaluation of these apps. Numerous gaps related to selecting appropriate and relevant metrics and defining successful or high levels of engagement have been identified for future exploration. Although long-term use or adoption is an important precursor to realizing the expected benefits of an app, few studies have examined this issue. Researchers would benefit from clarification and guidance on how to measure and analyze app usage in terms of evaluating digital mental health interventions for transition-aged youth. Given the established role of adoption in the success of health information technologies, understanding how to abstract and analyze user adoption for consumer digital mental health apps is also an emerging priority.BACKGROUND The use of consumer wearable health devices for fitness tracking has seen an upward trend across the globe. Previous studies have shown that trust is an important factor in the adoption and use of new technologies. However, little is known about the influence of organizational reputation on the trust in and intention to use wearable health devices. OBJECTIVE This study aimed to investigate the mediating role of organizational reputation and trust in intention to use wearable health devices. The study also examined the extent to which the country of residence influenced the effect of organizational reputation on consumers' trust in and intention to use wearable health devices. METHODS We conducted a cross-country survey with participants from Kenya and South Africa using a Google Forms questionnaire derived from previously validated items. A series of mediation regression analyses were carried out using the PROCESS macro with the bootstrap CI procedure. A one-way between-group multivariate analysis health device with indirect effect of 0.42; 95% CI 0.282-0.557. The MANOVA test shows statistically significant differences in all variables for both groups, with the exception of organizational reputation where there is no significant difference between the two cohorts. CONCLUSIONS Organizational reputation has a significant direct influence on participants' trust in, and the intention to use a wearable health device irrespective of their country of residence. Even in the presence of perceived security and perceived privacy, trust has a significant mediating effect on the intention to use a wearable health device.BACKGROUND The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings. OBJECTIVE The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods. METHODS We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) from database inception until November 2019. We included all peer-reviewed studies that compared electronic (any modalityture methods were equivalent or superior to conventional methods. Most (19/23, 83%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method. CONCLUSIONS Electronic pain-related data capture methods are comparable with conventional methods in terms of score equivalence, data completeness, ease, efficiency, and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.BACKGROUND Extracting the interactions between chemicals and proteins from the biomedical literature is important for many biomedical tasks such as drug discovery, medicine precision, and knowledge graph construction. Several computational methods have been proposed for automatic chemical-protein interaction (CPI) extraction. However, the majority of these proposed models cannot effectively learn semantic and syntactic information from complex sentences in biomedical texts. OBJECTIVE To relieve this problem, we propose a method to effectively encode syntactic information from long text for CPI extraction. METHODS Since syntactic information can be captured from dependency graphs, graph convolutional networks (GCNs) have recently drawn increasing attention in natural language processing. To investigate the performance of a GCN on CPI extraction, this paper proposes a novel GCN-based model. The model can effectively capture sequential information and long-range syntactic relations between words by using the dependency structure of input sentences. RESULTS We evaluated our model on the ChemProt corpus released by BioCreative VI; it achieved an F-score of 65.17%, which is 1.07% higher than that of the state-of-the-art system proposed by Peng et al. As indicated by the significance test (P less then .001), the improvement is significant. It indicates that our model is effective in extracting CPIs. The GCN-based model can better capture the semantic and syntactic information of the sentence compared to other models, therefore alleviating the problems associated with the complexity of biomedical literature. CONCLUSIONS Our model can obtain more information from the dependency graph than previously proposed models. Experimental results suggest that it is competitive to state-of-the-art methods and significantly outperforms other methods on the ChemProt corpus, which is the benchmark data set for CPI extraction.BACKGROUND Communicating physical activity information with sufficient details, such as activity type, frequency, duration, and intensity, is vital to accurately delineate the attributes of physical activity that bring positive health impact. Unlike frequency and duration, intensity is a subjective concept that can be interpreted differently by people depending on demographics, health status, physical fitness, and exercise habits. However, activity intensity is often communicated using general degree modifiers, degree of physical exertion, and physical activity examples, which are the expressions that people may interpret differently. Lack of clarity in communicating the intensity level of physical activity is a potential barrier to an accurate assessment of exercise effect and effective imparting of exercise recommendations. OBJECTIVE This study aimed to assess the variations in people's perceptions and interpretations of commonly used intensity descriptions of physical activities and to identify factors thading to respondents' characteristics. Regression analyses showed that those who reported good health or considered regular exercise was important for their health tended to rate the intensity levels of the activity examples significantly higher than their counterparts. The respondents' age and race (white vs nonwhite) were not significant predictors of the intensity rating. CONCLUSIONS This survey showed significant variations in how people perceive and interpret the intensity levels of physical activities described with general severity modifiers, degrees of physical exertion, and physical activity examples. Considering that these are among the most widely used methods of communicating physical activity intensity in current practice, a possible miscommunication in assessing and promoting physical activity seems to be a real concern. We need to adopt a method that represents activity intensity in a quantifiable manner to avoid unintended miscommunication.BACKGROUND The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools. OBJECTIVE This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults. METHODS We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieva(E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E). CONCLUSIONS Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps.BACKGROUND Continuous photoplethysmography (PPG) monitoring with a wearable device may aid the early detection of atrial fibrillation (AF). OBJECTIVE We aimed to evaluate the diagnostic performance of a ring-type wearable device (CardioTracker, CART), which can detect AF using deep learning analysis of PPG signals. METHODS Patients with persistent AF who underwent cardioversion were recruited prospectively. We recorded PPG signals at the finger with CART and a conventional pulse oximeter before and after cardioversion over a period of 15 min (each instrument). Cardiologists validated the PPG rhythms with simultaneous single-lead electrocardiography. The PPG data were transmitted to a smartphone wirelessly and analyzed with a deep learning algorithm. We also validated the deep learning algorithm in 20 healthy subjects with sinus rhythm (SR). RESULTS In 100 study participants, CART generated a total of 13,038 30-s PPG samples (5850 for SR and 7188 for AF). Using the deep learning algorithm, the diagnostic accurv NCT04023188; https//clinicaltrials.gov/ct2/show/NCT04023188.BACKGROUND For the last decade, doctor-patient contradiction in China has remained prominent, and workplace violence toward medical staff still occurs frequently. However, little is known about the types and laws of propagation of violence against medical staff online. OBJECTIVE By using a self-organizing map (SOM), we aimed to explore the microblog propagation law for violent incidents in China that involve medical staff, to classify the types of incidents, and to provide a basis for rapidly and accurately predicting trends in public opinion and developing corresponding measures to improve the relationship between doctors and patients. METHODS For the object of study, we selected 60 violent incidents in China involving medical staff which, caused a sensation on the Sina microblog from 2011 to 2018, searched the Web data of the microblog using crawler software, recorded the amount of new tweets every 2 hours, and used the SOM neural network to cluster the number of tweets. A method using polynomial and exponek was significantly higher than that of incidents caused by nontherapeutic effects.BACKGROUND Specialized training for elite US military units is associated with high attrition due to intense psychological and physical demands. The need to graduate more service members without degrading performance standards necessitates the identification of factors to predict success or failure in targeted training interventions. OBJECTIVE The aim of this study was to continuously quantify the mental and physical status of trainees of an elite military unit to identify novel predictors of success in training. METHODS A total of 3 consecutive classes of a specialized training course were provided with an Apple iPhone, Watch, and specially designed mobile app. Baseline personality assessments and continuous daily measures of mental status, physical pain, heart rate, activity, sleep, hydration, and nutrition were collected from the app and Watch data. RESULTS A total of 115 trainees enrolled and completed the study (100% male; age mean 22 years, SD 4 years) and 64 (55.7%) successfully graduated. Most training withdrawals (27/115, 23.5%) occurred by day 7 (mean 5.5 days, SD 3.4 days; range 1-22 days). Extraversion, positive affect personality traits, and daily psychological profiles were associated with course completion; key psychological factors could predict withdrawals 1-2 days in advance (P=.009). CONCLUSIONS Gathering accurate and continuous mental and physical status data during elite military training is possible with early predictors of withdrawal providing an opportunity for intervention.BACKGROUND Information and communication technology (ICT) use among older adults has been on the rise in recent years. However, the predictors and mechanisms behind older adults' acceptance and use of ICT are not clear. OBJECTIVE This study aimed to systematically describe ICT usage among Czech older adults and to evaluate the factors influencing their ICT use and readiness to use digital technology to promote electronic health (eHealth) readiness. The primary focus was on psychological factors and the role of persons close to older adults. METHODS The research utilized cross-sectional survey data from a quota-based sample of Czech older adults (>50 years) and persons close to them further referred to as close persons (N=250 dyads). A structural equation modeling framework was used to evaluate relationships between psychological factors, ICT use, and eHealth readiness. RESULTS Czech older adults' use of ICT is low with the exception of cell phone usage (cell phone usage by 173/250, 69.2%; other devices used be evaluated and yielded actionable results. More research is needed to clarify the role of persons close to older adults.BACKGROUND HIV pre-exposure prophylaxis (PrEP) is recommended for populations at high ongoing risk for infection. There are noted racial disparities in the incidence of HIV and other sexually transmitted infections (STIs) for African, Caribbean, and Canadian Black (ACB, black) populations in Ontario, Canada. Although blacks represent only 4.7% of the Ontario population, they account for 30% of HIV prevalence and 25% of new infections in the province. The existing clinical public health practice toolkit has not been sufficient to optimize PrEP uptake, despite the overwhelming evidence of PrEP's efficacy for reducing HIV transmission risk. Since its establishment as an effective HIV prevention tool, the major focus in behavioral research on PrEP has been on understanding and improving adherence. To date, there is no known formalized intervention in place designed to support ACB men and women at high risk of making high-quality decisions regarding the adoption of PrEP as an HIV prevention practice. OBJECTIVE We ct size estimates. RESULTS A research award was funded on March 25, 2017. Ethical approval was received on March 25, 2019 (with supplemental approval received on May 10, 2019). Data collection started on April 9, 2019. As of September 30, 2019, we enrolled 29 patients and 24 health care providers for aim 1. We are currently analysing the data collected for aim 1. Aim 2 is scheduled to start in May 2020. CONCLUSIONS This study will provide evidence-based information on the decisional needs of black patients who are at risk of HIV and have been offered PrEP. The study will also test the effect of decision support intervention in reducing decision conflict, adoption of PrEP, and adherence to PrEP.The reported advantage of new dual-cured adhesive agents is that they do not require light curing, resulting in a reduced film thickness and improved seating of bonded all-ceramic restorations. The purpose of this study was to determine the effect of dual-cured adhesives on the bond strength of dual-cured resin cement to dentin under different polymerization conditions with or without light curing of the dual-cured adhesive as well as with or without light curing of the dual-cured resin cement through a lithium disilicate ceramic material. Human molars were sectioned to remove the coronal tooth structure and randomly divided into 3 adhesive groups Clearfil SE Bond 2, ExciTE F DSC, and Universal Primer. The adhesive agents were applied to the dentin surface with or without light activation. A dual-cured resin cement was applied, and discs of lithium disilicate were cemented to the dentin surface. Half of the discs were light cured from the top surface, and the other half were allowed to self-cure. Shear bond strength was tested after storage in distilled water for 24 hours. The effect of light curing of the adhesive or cement on the shear bond strength of the lithium disilicate discs to dentin was product dependent. Clearfil SE Bond 2 performed significantly better with light curing of both the adhesive and cement. Less significant effects of the various light-curing and self-curing combinations were observed with ExciTE F DSC or Universal Primer. When neither the adhesive nor the cement was light cured, all 3 adhesives performed poorly and had a significant loss in bond strength.While telemedicine has been adopted and is used increasingly in patient care, the dental profession is still in the relatively early stages of utilizing technology in similar ways. The number of patients with intellectual and developmental disabilities is increasing in number and complexity, calling for new approaches to assist with access to care. The current article outlines the benefits of new technology in the evaluation of all patients but particularly the more complex population that has been diagnosed with a disability. Three case examples illustrate the value of technology in remote patient observation and offer ideas for use and further research.Dens evaginatus (DE) is a developmental anomaly presenting as an enamel-covered tubercle on the occlusal surface of a premolar, particularly found in people of Asian descent. This case report describes partial pulpotomy in a mandibular premolar with a fractured evaginatus tubercle and endodontic infection. A 10.5-year-old girl of Asian descent was referred for endodontic evaluation and treatment because of local swelling and pain. Clinical examination suggested the presence of DE in a noncarious mandibular right second premolar with a diagnosis of symptomatic irreversible pulpitis and symptomatic apical periodontitis. On access, the pulp was hemorrhagic. A single-appointment mineral trioxide aggregate (MTA) pulpotomy and an immediate composite resin restoration were performed. Recall examinations at 3, 6, and 18 months verified periapical healing and root development without clinical symptoms. This case report suggests that MTA pulpotomy could be a viable alternative option for DE-affected immature teeth with pulpal and periapical inflammation.
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